VALIDATION AND DETERMINATION OF CLARITHROMYCIN … Tawfeeq... · ii validation and determination of clarithromycin and metronidazole in rat plasma by using high performance liquid

VALIDATION AND DETERMINATION OF

CLARITHROMYCIN AND METRONIDAZOLE IN RAT

PLASMA BY USING HIGH PERFORMANCE LIQUID

CHROMATOGRAPHY/MASS SPECTROMETRY (HPLC/MS)

IN PRESENCE OF POMEGRANATE JUICE

By

Haifa Tawfeeq Abu Tbeekh

Supervisor

Dr. Eyad Mallah

Co-Supervisor

Dr. Wael Abu Dayyih

A Thesis Submitted in Partial Fulfillment of the Requirements for the

Degree of Master of Science in Pharmaceutical Sciences at

University of Petra

Faculty of Pharmacy and Medical Sciences

Amman-Jordan

October 2013

i

ii




CHROMATOGRAPHY/MASS SPECTROMETRY

(HPLC/MS) IN PRESENCE OF POMEGRANATE JUICE

By


A Thesis Submitted in Partial Fulfillment of the Requirements for the

Degree of Master of Science in Pharmaceutical Sciences at

University of Petra

Faculty of Pharmacy and Medical Sciences

Amman-Jordan

October 2013

Supervisor Signature

Dr. Eyad Mallah

Co-Supervisor Signature

Dr. Wael Abu Dayyih

Examination Committee Signature

1. Prof. Tawfiq Arafat

2. Dr. Nidal Qinna

3. Dr. Kamal Sweidan

iii

Abstract




CHROMATOGRAPHY/MASS SPECTROMETRY

(HPLC/MS) IN PRESENCE OF POMEGRANATE JUICE

By


University of Petra, 2013

Supervisor Co-Supervisor

Dr. Eyad Mallah Dr. Wael Abu Dayyih

Pomegranate juice has been widely consumed around the world especially in the

Middle Eastern countries from the standpoint of its prevention and treatment of common

diseases. Clarithromycin and Metronidazole are widely and concomitantly used drugs. In

addition, both of them are considered as CYP3A4 metabolic enzyme substrates and

inhibitors.

A simple, reproducible and rapid analytical method by using high performance

liquid chromatography-mass spectrometry (HPLC/MS) with high resolution and

sensitivity for simultaneous quantification of Clarithromycin and Metronidazole in

presence of pomegranate juice was validated. A gradient mobile phase system consisting

of methanol and 0.1% of formic acid and ACE 5 C18 column (50 X 2.1 mm, 5µ) were used

with a flow rate of 1.0 ml/ min.

iv

An acceptable recovery was achieved (97.75%) and (96.0%) for Clarithromycin

and Metronidazole, respectively, with good accuracy and precision. Coefficient of

determination (R²) of the standard curves for both drugs ranged between 0.9986 and

0.9998.

According to results obtained, there was no significant effect on pharmacokinetic

parameters of Clarithromycin after pretreatment with single and multiple doses of

pomegranate fresh juice. However, there was two hours-long delay on Tmax after the

single dose of juice which is possibly with no clinically significant. Furthermore, the

changing in t½ and the elimination rate constant of Clarithromycin after single and

multiple pomegranate juice administration give an expectation that pomegranate juice

could affect the hepatic-mediated metabolism of Clarithromycin but with insignificant

manner.

Pharmacokinetic parameters of Metronidazole was not affected by single dose

administration of juice, on the other hand, multiple dose pretreatment with juice

significantly elevating the maximum plasma concentration (Cmax) (P˂0.05) and the area

under the curve (AUC) of Metronidazole (P=0.001). Since there was a very slight

changing on the t½ and the elimination rate constant, the hepatic enzymes could not be

affected. In contrast, concomitant administration of Metronidazole and Clarithromycin

showed no significant interaction.

Since there are different enteric metabolic enzymes involved in the orally

administered drug metabolism, further in vitro and in vivo investigations to study the

mechanism of the pomegranate juice effect on the pharmacokinetic parameters of these

drugs should be established.

v

DEDICATIONS

To my parents, my husband, and my wonderful children.

You are my family which I always proud of. I hope you are proud of me as

well by this work.

vi

ACKNOWLEDGMENTS

First, a great thankful to Allah for helping me without waiting for giving back and all of

people assistances are the grace of him.

I would like to acknowledge my supervisor Dr. Eyad Mallah and co-supervisor Dr. wael

Abu Dayyih for helping me to overcome a lot of difficulties that I faced and urging me to

complete this work.

Special thanks to Prof. Tawfiq Arafat for his keen interest to help all students, without

exception.

Special thanks to Dr. Nidal Qinna for all of his help.

Special thanks to Prof. Khalid Matalka for all of his help.

This acknowledgment will be not complete if I don’t give thanks with respect to Prof.

Tawfiq Al hussainy for his wisdom and for giving me hope and confidence.

I am indebted to Jordan Center for Pharmaceutical Research, special thanks to Ahmad

Abu Awad and Hamza Al Horoub for their assistance.

I would like to thank all members of committee for their time to evaluate this work.

Finally, special thanks to my wonderful husband Dr. Eng Qahtan Abu Tbeekh for his

encouragement and trusting in my successes.

vii

Table of Contents

No. Subject Page

No.

Committee Decision ii

Abstract iii

Dedications v

Acknowledgments vi

Table of Contents vii

List of Tables xi

List of Figures xvii

List of Abbreviations xix

Chapter 1: Introduction 1

1 Introduction 2

1.1 Clarithromycin (CAM) 2

1.1.1 Chemical structure of Clarithromycin 2

1.1.2 Mechanism of action of Clarithromycin 3

1.1.3 Side effects of Clarithromycin 3

1.1.4 Pharmacokinetics of Clarithromycin 3

1.1.5 Metabolism of Clarithromycin 4

1.1.6 Drug interactions of Clarithromycin 4

1.2 Metronidazole (MTZ) 6

1.2.1 Mechanism of action of Metronidazole 6

1.2.2 Side effects of Metronidazole 6

1.2.3 Pharmacokinetics of Metronidazole 7

1.2.4 Metabolism of Metronidazole 7

1.2.5 Drug interactions of Metronidazole 7

1.3 Drug interactions 9

1.3.1 Factors affecting drug interactions 9

1.3.2 Mechanisms involved in pharmacokinetic drug interactions 9

1.3.2.1 Alterations in absorption 9

1.3.2.2 Alteration of distribution 11

1.3.2.3 Affecting of drug metabolism 11

1.4 Drug-food interactions 13

viii

1.4.1 Mechanisms of drug-food interactions 13

1.4.1.1 Physiologic and physicochemical mechanisms 13

1.4.1.2 Biochemical mechanisms 14

1.5 Inhibition of intestinal biochemical processes 14

1.5.1 Intestinal enzymes and transporters involved in drug disposition

that can be affected by certain beverages 15

1.5.1.1 Enzymes 15

1.5.1.2 Transporter-mediated efflux and uptake 15

1.6 Pomegranate juice (PJ) 16

1.7 Grapefruit juice (GFJ) 17

1.8 Seville orange juice 17

1.9 Tea 18

1.10 Chromatography 18

1.10.1 Definition 18

1.10.2 Types of chromatography 18

1.10.3 High performance liquid chromatography (HPLC) advantages 20

1.10.4 High performance liquid chromatography (HPLC) limitations 20

1.10.5 Types of chromatography detectors 21

1.10.6 High performance liquid chromatography/Mass spectrometry 22

1.10.7 Method validation 22

1.10.7.1 Standard calibration curve 22

1.10.7.2 Linearity and range 23

1.10.7.3 Precision 23

1.10.7.4 Accuracy 24

1.10.7.5 Lower limit of detection 24

1.10.7.6 Lower limit of quantification 25

1.10.7.7 Selectivity 25

1.10.7.8 Specificity 25

1.10.7.9 Recovery 25

1.11 Previous analytical studies for quantification of Clarithromycin in

plasma 26

ix

1.12 Previous analytical studies for quantification of Metronidazole in

plasma 29

1.13 Preclinical studies 30

1.14 Objectives of the current study 32

Chapter 2: Materials and Methods 33

2 Materials and Methods 34

2.1 Reagents 34

2.2 Instrumentation 34

2.3 Animals 35

2.4 Preparation of Clarithromycin solution to be injected orally to rats 35

2.5 Preparation of Metronidazole solution to be injected orally to rats 35

2.6 Preparation of pomegranate juice to be injected orally to rats 35

2.7 Preparation of stock solutions for the method validation 35

2.7.1 Preparation of stock solution for Clindamycin as an internal standard

(IS) 35

2.7.2 Preparation of 2 µg/ml Clindamycin IS in methanol (Precipitating

agent) 35

2.7.3 Preparation of stock solutions of Clarithromycin and Metronidazole 36

2.7.4 Preparation of working solution for Clarithromycin and

Metronidazole 36

2.7.5 Preparation of the mobile phase 36

2.7.6 Preparation of Clarithromycin and Metronidazole SCC serial

dilution and spiked serum 36

2.7.7 Preparation of Clarithromycin and Metronidazole QC serial dilution

and spiked serum 36

2.7.8 Method of extraction 38

2.8 Analytical method validation 40

2.8.1 Standard calibration curve and linearity 40

2.8.2 Intra-day accuracy and precision 40

2.8.3 Inter-day accuracy and precision 40

x

2.8.4 Sensitivity 41

2.8.5 Recovery 41

2.9 Preclinical study design 41

Chapter 3: Results and Discussion 43

3 Results and Discussion 44

3.1 HPLC/MS analytical method 44

3.2 Validation 45

3.2.1 Validation of day one, two, and three on linearity, accuracy, and

precision data for Clarithromycin quantification 45

3.2.2 Recovery data for Clarithromycin quantification 63

3.2.3 Validation of day one, two, and three, linearity, accuracy, and

precision data for Metronidazole quantification 65

3.2.4 Recovery data for Metronidazole quantification 82

3.3 The modifying effect of pomegranate fresh juice on Clarithromycin

and Metronidazole pharmacokinetic profile 84

3.3.1 Effect of a single and multiple dose of pomegranate juice on

Clarithromycin 87

3.3.2 Effect of a single and multiple dose of pomegranate juice on

Metronidazole 93

3.4 The modifying effect of concomitantly administered Clarithromycin

and Metronidazole on their pharmacokinetic profiles 99

3.4.1 Effect of combination on Clarithromycin 100

3.4.2 Effect of combination on Metronidazole 103

4 Conclusion 107

5 References 109

6 Appendix (A): HPLC Chromatograms 124

7 Appendix (B): Preclinical Data 135

8 Abstract (In Arabic) 140

xi

List of Tables

Table No.

Caption Page No.

Table 1 Physical and chemical properties of Clarithromycin (CAM) 5

Table 2 Physical and chemical properties of Metronidazole(MTZ) 8

Table 3 Preparation of Clarithromycin & Metronidazole SCC serial


Table 4 Preparation of Clarithromycin & Metronidazole QC serial


Table 5 chromatographic and mass spectrometric conditions 39

Table 6 Standard calibration curve of the first day of validation, intraday

accuracy data for Clarithromycin 46

Table 7 Data of the standard curve with regards to correlation, slope, R²,

and intercept on the first day for Clarithromycin 46

Table 8 Standard calibration curve of the second day of validation,

intraday accuracy data for Clarithromycin 48


and intercept on the second day for Clarithromycin 48

Table 10 Standard calibration curve of the third day of validation, intraday

accuracy data for Clarithromycin 50


and intercept on the third day for Clarithromycin 50

Table 12 Linearity and linear working range of three standard curves of

Clarithromycin data based on the calculated area ratio 52


Clarithromycin data based on the measured concentrations 52

Table 14 Data of three standard curves with regards to correlation, slope,

R², and intercept for Clarithromycin 52

Table 15 Intra-day precision and accuracy data for QC low samples of

Clarithromycin based on the standard calibration curve of the 54

xii

first day of validation

Table 16 Intra-day precision and accuracy data for QC mid samples of

Clarithromycin based on the standard calibration curve of the


54

Table 17 Intra-day precision and accuracy data for QC high samples of



55

Table 18 Intra-day precision and accuracy data for LLOQ samples of



55



second day of validation

56




57




57




58



third day of validation

59




59




60

Table 26 Intra-day precision and accuracy data for LLOQ samples of 60

xiii



Table 27 Inter-day accuracy and precision for the quality control samples

of Clarithromycin in the three days of validation 62

Table 28 Data of Clarithromycin and IS in the mobile phase for the

quality control samples 63

Table 29 Data of Clarithromycin and IS in serum for the quality control

samples 64

Table 30 Recovery % for Clarithromycin 64

Table 31 Recovery % for Clindamycin (IS) 64

Table 32 Standard calibration curve of the first day of validation, intraday

accuracy data for Metronidazole 65


and intercept on the first day for Metronidazole 66

Table 34 Standard calibration curve of the second day of validation,

intraday accuracy data for Metronidazole 67


and intercept on the second day for Metronidazole 67

Table 36 Standard calibration curve of the third day of validation, intraday

accuracy data for Metronidazole 69


and intercept on the third day for Metronidazole 69


Metronidazole data based on the calculated area ratio 71

Table 39 linearity and linear working range of three standard curves of

Metronidazole data based on the measured concentrations 71

Table 40 Data of three standard curves with regards to correlation, slope,

R², and intercept for Metronidazole 71


Metronidazole based on the standard calibration curve of the


73

Table 42 Intra-day precision and accuracy data for QC mid samples of 73

xiv






74




74




75




76




76




77




78




78




79




79

xv

Table 53 Inter-day accuracy and precision for the quality control samples

of Metronidazole in the three days of validation 81

Table 54 Data of Metronidazole in the mobile phase for the quality

control samples 82

Table 55 Data of Metronidazole in the serum for the quality control

samples 83

Table 56 Recovery % for Metronidazole 83

Table 57 Recovery % for Clindamycin (IS) 83

Table 58 Results of Clarithromycin with DW (n=4) 89

Table 59 Results of Clarithromycin with a single dose of pomegranate

juice with a comparison to a Clarithromycin with DW

administration (n=6)

89

Table 60 Comparing Cmax, Tmax, AUC, T½, and the elimination rate

constant between: Clarithromycin + DW and (Clarithromycin +

single dose of juice)

90

Table 61 Results of Clarithromycin with a multiple dose of pomegranate

juice with a comparison to a Clarithromycin with DW


90


constant between Clarithromycin with DW and (Clarithromycin

+ multiple dose of juice)

91

Table 63 Comparison between single and multiple dose effect of PJ on

Clarithromycin 91

Table 64 Results of Metronidazole with DW (n=2) 94

Table 65 Results of Metronidazole with a single dose of pomegranate

juice with a comparison to a Metronidazole with DW


95


constant between: Metronidazole with DW and (Metronidazole

+ single dose of juice)

95

Table 67 Results of Metronidazole with a multiple dose of pomegranate

juice with a comparison to a Metronidazole with DW 96

xvi



constant between: Metronidazole with DW and (Metronidazole

+ multiple dose of juice)

97

Table 69 Comparison between single and multiple dose effect of PJ on

Metronidazole 97

Table 70 Results of Clarithromycin alone (n=7) 101

Table 71 Results of Clarithromycin after combination with Metronidazole

with a comparison to a lone Clarithromycin administration (n=5) 101


constant between: Clarithromycin alone and Clarithromycin

after combination with Metronidazole

102

Table 73 Results of Metronidazole alone (n=6) 114

Table 74 Results of Metronidazole after combination with Clarithromycin

with a comparison to a lone Metronidazole administration (n=5) 114


constant between: Metronidazole alone and (Metronidazole

after combination with Clarithromycin)

115

Table 76 Data measured for Clarithromycin experiments after

administration with DW, single dose of PJ, and multiple dose of

PJ

136

Table 77 Data measured for Metronidazole experiments after

administration with DW, single dose of PJ, and multiple dose of

PJ

137

Table 78 Data measured for Clarithromycin experiments alone and after

concomitant administration with Metronidazole 138

Table 79 Data measured for Metronidazole experiments alone and after

concomitant administration with Clarithromycin 139

xvii

List of Figures

Figure No. Caption Page No.

Figure 1 Chemical structure of Clarithromycin 2

Figure 2 Chemical structure of Metronidazole 6

Figure 3 Plot of calibration curve levels against their analytical response

and regression linear equation on the first day of validation for

Clarithromycin

47


and regression linear equation on the second day of validation

for Clarithromycin

49


and regression linear equation on the third day of validation for

Clarithromycin

51

Figure 6 Plot of linearity of calibration curve levels for Clarithromycin

quantification against their analytical response and regression

linear equation

53


and regression linear equation on the first day of validation for

Metronidazole

66


and regression linear equation on the second day of validation

for Metronidazole

68


and regression linear equation on the third day of validation for

Metronidazole

70

Figure 10 Plot of linearity of calibration curve levels for Metronidazole

quantification against their analytical response and regression

linear equation

72

Figure 11 Line chart showing the changes in mean plasma

Clarithromycin concentration with time after drug

administration with DW, with single dose of juice, and with

92

xviii

multiple dose of juice

Figure 12 Line chart showing the changes in mean plasma Metronidazole

concentration with time after drug administration with DW,

with single dose of juice, and with multiple dose of juice

98

Figure 13 Line chart showing the changes in mean plasma

Clarithromycin concentration with time after separately drug

administration and in combination with Metronidazole

102

Figure 14 Line chart showing the changes in mean plasma Metronidazole

concentration with time after separately drug administration

and in combination with Clarithromycin

115

Figure 15 Clarithromycin blank chromatogram 125

Figure 16 Clarithromycin zero chromatogram 126

Figure 17 Clarithromycin LLOQ chromatogram 127

Figure 18 Clarithromycin SCC7 chromatogram 128

Figure 19 Clarithromycin rat unknown sample chromatogram at 4.00 hr

measured as 0.878 µg/ml 129

Figure 21 Metronidazole blank chromatogram 130

Figure 21 Metronidazole zero chromatogram 131

Figure 22 Metronidazole LLOQ chromatogram 132

Figure 23 Metronidazole SCC7 chromatogram 133

Figure 24 Metronidazole rat unknown sample chromatogram at 4.00 hr

measured as 7.83 µg/ml 134

xix

List of Abbreviations

API Atmospheric-pressure ionization

AUC Area Under the Curve

CAD Collision Gas

CAM Clarithromycin

CE Collision Energy

CEP Collision Empotance Potential

Cmax Mean Maximum concentration

Conc. Concentration

CUR Curtain Gas

CV Coefficient of Variation

CXP Collision cell Exiting Potential

CYP Cytochrome P

DW Distilled Water

DP Declustering Potential

EMA European Medicines Agency

EP Entrance Potential

FA Formic Acid

FDA Food and Drug Administration

fg Femtogram (1/1000000 ng)

GC Gas Chromatography

GIT Gastro-Intestinal Tract

GS1 Ion Source Gas 1

GS2 Ion Source Gas 2

HCL Hydrochloric Acid

HPLC High Performance Liquid Chromatography

H.pylori Helicobacter pylori

hr Hour

IS Internal Standard

xx

ISV Ion Spray Voltage

JCPR Jordan Center for Pharmaceutical Research

Ke Rate of Elimination Constant

LLOQ Lower Limit Of Quantification

M.P.C Mean Plasma Concentrations

µg Microgram

µl Microliter

mM Millimole

µmol Micromole

MRM Multiple Reaction Monitoring

MS Mass Spectrometry

MTZ Metronidazole

n Samples number

ng Nanogram

NEB Nebulizer Gas

PD Pharmacodynamic

PJ Pomegranate Juice

PK Pharmacokinetic

PPIs Proton Pump Inhibitors

Q1 Quadrupole mass analyzer 1

Q3 Quadrupole mass analyzer 2

QC Quality Control

QC samples Low, mid, high

R Correlation Coefficient

R² Coefficient of Determination

r.p.m Rotation per minute

SE Standard Error

Sol. Solution

SRM Single Reaction Monitoring

SCC Standard Calibration Curve

xxi

STDV Standard Deviation

T½ Half Time

TEM Temperature

Tmax Median time to Maximum Plasma Concentration

USFDA United states Food and Drug Administration

USP United State Pharmacopeia

UV Ultraviolet

V/V Volume by Volume

Vol. Volume

Zero-sample Blank with internal standard

xxii

1

Chapter 1

Introduction

2

1. Introduction

1.1 Clarithromycin (CAM)

It is a macrolide antibiotic derived from erythromycin, with an improved side

effect profile, dosing schedule, and microbiological activity relative to its parent

compound, erythromycin (Kanatani M.S. and Guglielmo B.J., 1994). It is 6-o-

methylerythromycin, this chemical modification in erythromycin is responsible for CAM

acid stability, wider spectrum of activity, better pharmacokinetic properties and fewer

gastrointestinal adverse effects than erythromycin (Amsden G.W., 1996). CAM is active

(in vitro) against aerobic and anaerobic Gram-positive and Gram-negative bacteria. It is

used for treatment of Pharyngitis/Tonsillitis, Acute bacterial exacerbation, Acute

Maxillary sinusitis, Skin infections, Pneumonia, and with other drugs (Proton pump

inhibitors and Metronidazole) as a triple therapy for treatment of Helicobacter pylori

infection (Katzung B.G., 2012).

1.1.1 Chemical structure of Clarithromycin

CAM has a 14-membered macrocyclic lactone ring attached to two sugar moieties

a neutral sugar cladinose and amino sugar desosamine and has substituted an O-methyl

group at position C6 with resultant acid stability and improved antimicrobial and

pharmacokinetic properties ( Peters D.H and Clissold S.P., 1992; Zuckerman J.M., 2000).

The chemical structure of CAM is illustrated in (Figure 1) while its physical and

chemical properties are listed in (Table 1).

Figure 1: Chemical structure of Clarithromycin.

O

O

O

O

CH3

OHOH

CH3

H5C

2

O

CH3

CH3

O

CH3

CH3

OMe

O

OHN

CH3

CH3

OHCH

3

CH3

OMe

CH3

3

1.1.2 Mechanism of action of Clarithromycin

CAM is first metabolized to 14-OH CAM, which is active and works

synergistically with its parent compound. Like other macrolides, it then penetrates

bacteria cell wall and reversibly binds to domain V of the 23S ribosomal RNA of the 50S

subunit of the bacterial ribosome. Binding inhibits peptidyl transferase activity and

interferes with amino acid translocation during the translation and protein assembly

process (Katzung B.G., 2012; Zuckerman J.M., 2000). CAM may be bacteriostatic or

bactericidal depending on the species of organism, inoculums size, growth phase, and

drug concentration (Peters D.H and Clissold S.P, 1992; Peters D.H et al., 1992).

1.1.3 Side effects of Clarithromycin

Adverse events that have been reported with CAM are of variable rates of (4–

30%). The most frequently reported events in adults were diarrhea , nausea , abnormal

taste, dyspepsia, abdominal pain/discomfort , and headache. Adverse effects of CAM in

central nervous system (CNS) include CNS depression (confusion and obtundation) or

excitation (agitation, insomnia, delirium and psychosis) (Wallace R.J. et al., 1993).

Patients are at a higher risk of developing neurotoxicity if they are co-prescribed CAM

and other drugs metabolized by cytochrome P450 isoenzymes of the CYP3A family

(Yasui N. et al., 1997; Gelisse P. et al., 2007). In addition, CAM may be associated with

potentially life-threatening cardiac adverse effects (Kamochi H. et al., 1999).

1.1.4 Pharmacokinetics of Clarithromycin

CAM is well-absorbed from GIT (50%± 50), acid stable and may be taken with

food. The mean maximum drug plasma concentrations (Cmax) of CAM after oral

administration of single and multiple 500mg doses ranged from 1.65 to 2.12 mg/L and

2.41 to 2.85 mg/L, respectively (Davey P.G., 1991; Hardy D.G. et al., 1992; Chu S.Y. et

al., 1993). The meal does not have any significant changes in the CAM mean time to

maximum concentration (tmax) or the area under the concentration-time curve (AUC)

values (Peters D.H. and Clissold S.P. 1992; Chu S. et al., 1992). The bioavailability of

CAM 250 mg tablets is 52 to 55% (Chu S.Y et al., 1992). Bioavailability is slightly

increased when CAM tablets are taken with food (Chu S. et al., 1992). As with other

http://www.rxlist.com/script/main/art.asp?articlekey=2985





4

macrolide antibiotics, CAM and its metabolites have exceptional tissue penetration and

accumulation within cells. Concentration of CAM within alveolar cells were 1,700-fold

greater than those in plasma (Chu S. et al., 1992; Fraschini F. et al., 1991). After a 250

mg tablet every 12 hours, approximately 20% of the dose is excreted in the urine as

CAM, while after a 500 mg tablet every 12 hours, the urinary excretion of CAM is

slightly increased, approximately 30%. Half-life is approximately 3 to 4 h (250 mg) and 5

to 7 h (500 mg) (Chu S.Y. et al., 1992).

1.1.5 Metabolism of Clarithromycin

CAM is metabolized in the liver by CYP3A4 and has an active metabolite, 14-

hydroxyclarithromycin which works synergistically with its parent compound. It is

known as a potent inhibitor of CYP3A4. Moreover, it has been suggested that CAM

inhibits the CYP2C19 activity to some extent (Rodrigues A.D. et al., 1997).

1.1.6 Drug interactions of Clarithromycin

Most of CAM interactions are due to its strong CYP3A4 inhibitory effect. For

example: it may interact with tiniposide, tamsulosin, sildenafil, warfarin, rifampicin, and

vinblastine (Recker M.W. et al., 1997; Dresser G.K. et al., 2000; Riss J. et al., 2008.).

5

Table 1: Physical and chemical properties of Clarithromycin.

Chemical formula

C38H69NO13

Molecular weight

747.96 g/mol

Solubility

Soluble in acetone, slightly soluble in

methanol, ethanol, and acetonitrile, and

practically insoluble in water

Appearance

White to off-white crystalline powder

Melting point

220° C

Storage

Store in a well closed container, below 40°

C, protect from sunlight and moisture.

6

1.2 Metronidazole (MTZ)

It is a nitroimidazole (Reynolds J.E.F. 1993), antiprotozoal antibacterial drug

especially against anaerobic bacteria. Metronidazole (MTZ) is the drug of choice for the

treatment of amebiasis (liver or colon), giariasis (small intestine), trichomoniasis (vaginal

infection), and in the treatment of peptic ulcer diseases (PUD) caused by Helicobacter

pylori (H.pylori) when combined with proton pump inhibitors (PPIs) and CAM (Katzung

B.G., 2012). The chemical structure of MTZ is illustrated in (Figure 2) while its physical

and chemical properties are listed in (Table 2).

Figure 2: Chemical structure of Metronidazole.

1.2.1 Mechanism of action of Metronidazole

The antimicrobial activity of MTZ is due to presence of the nitro group which

chemically reduced by anaerobic bacteria and protozoans. The product that results from

this reduction is responsible for MTZ antimicrobial activity (Ewan J. et al., 1980;

Katzung B.G., 2012) and/or to the interaction of MTZ with the DNA of parasite

(Samuelson J., 1999).

1.2.2 Side effects of Metronidazole

Nauses, vomiting, metallic taste in the mouth, diarrhea insomnia, weakness, and

dizziness. Pancreatitis and sever central nervous system toxicity may occur.

Metronidazole is somewhat well tolerated, but it can produce a number of adverse

neurologic effects as peripheral neuropathy, encephalopathy (Kim D.W. et al., 2004),

cerebellopathy, and seizure (Kuriyama A. et al., 2011). Nausea and vomiting can occur if

N

N CH3

O2N

CH2CH

2OH

7

alcohol is ingested with MTZ therapy. MTZ is considered as an animal carcinogen, and

listed as a possible carcinogen for humans (IARC, 2010).

1.2.3 Pharmacokinetics of Metronidazole

MTZ well absorbed from GIT (at least 80%) and extensively distributed in

tissues. Its oral bioavailability is more than 90% and the maximal plasma concentration

(Cmax) is 45-75 µmol/L after an oral dose of 500mg and with multiple doses it could

reach 240 µmol/L. Peak plasma concentrations are achieved after 1-3 hours. It has a low

protein binding (<20%), the unchanged drug half-life is 7.5 hours and excreted mostly in

the urine (McEvoy G.K., 1995).

1.2.4 Metabolism of Metronidazole

MTZ is metabolized in the liver by the cytochrome P450 (CYP) enzymes family.

The biotransformation of MTZ gives two metabolites: a hydroxylated metabolite (40%)

and an acetilated metabolite (15%). CYP2E1 might be involved in the metabolism of

MTZ from the fact that when it was ingested with ethanol (CYP2E1inducer) leading to a

higher hydroxylation of MTZ. CYP 2B, 2C, and 3A may also involved since

phenobarbital (an inducer of these CYP) when administered with MTZ, its metabolism

was elevated (Loft S. et al., 1991, 1990). On the other hand, they found that MTZ is an in

vitro substrate of CYP1A1 and CYP2E1. However, the distinctiveness of the participant

CYPS has not been determined until now. MTZ is considered as a substrate and an

inhibitor to CYP2C9 and CYP3A4 enzymes and as an inhibitor to CYP2C8 enzyme

(Preissner S. et al., 2010).

1.2.5 Drug interactions of Metronidazole

MTZ has reported interactions with coumarin-type anticoagulants, phenytion,

phenobarbital, cimetidine, ethanol, mebendazole, ciprofloxacin, omeprazole, and lithium

(Cina S.J. et al., 1996; Humphries T.J. et al., 1999; Chen K.T. et al., 2003; Juurlink D.N.

et al., 2007).

8

Table 2: Physical and chemical properties of Metronidazole.

Chemical formula

C6H9N3O3

Molecular weight

171.16 g/mol

Solubility

Slightly soluble in alcohol and has a

solubility in water of 10mg/ml at 20°C

Appearance

White to pale yellow crystalline powder

Melting point

161°C

Storage

Store below 40°C and protect from

sunlight

9

1.3 Drug interactions

Interactions may occur between drug-drug, drug-food, and drug-herbs which may

cause increase or decrease the effect of agents, or a production of a new effect that is not

related to any of the interacting entities on its own (Corrie K., 2011). Other than these

interactions, drugs may interact with drinks, minerals and vitamins, excipients in drug

formulations, and laboratory tests (Kays M.B., 2012).

Drug-drug interactions occur by one therapeutic agent either by altering the

concentration (pharmacokinetic interactions) or the biological effect of another agent

synergistically or antagonistically (pharmacodynamic interactions). Pharmacokinetic

drug-drug interactions involve effecting on absorption, distribution by displacement of

drug from protein binding sites, induction or inhibition of the metabolizing enzymes,

and/or clearance of the affected agent through competition for renal excretion

(Venkatakrishnan K. et al., 2001; Wynn G.H., 2009).

1.3.1 Factors affecting drug interactions

There are many factors affecting drug interactions. These factors either drug-

related or patient-related factors. Drug-related factors as drug potency, duration of

treatment, drug dosage, blood and tissue drug concentration, route of administration,

extent and rate of drug metabolism, degree of protein binding, and others. Patient-related

factors as body weight, genetic polymorphism (quantity and activity of specific drug-

metabolizing enzymes, age, gender, diet, smoking, alcohol use (acutely or chronically),

underlying disease (liver, kidney), and polypharmacy (with enzyme inhibitors or

inducers) (Wynn G.H., 2009).

1.3.2 Mechanisms involved in pharmacokinetic drug interactions

1.3.2.1 Alterations in absorption

a. Alteration in gastro intestinal pH: - PPIs elevate gastric pH ≥ 5 for up to 19 hours.

H2-blockers raise gastric pH ≥ 5 for many hours. Antacids transiently increase

gastric pH by 1-2 units. Ketoconazole absorption is decreased when co-

10

administrated with PPIs or H2-blockers or antacids (Chin T.W., 1995 ; Cŕdoba-

Diaz D.et al., 2001).

b. By adsorption of compounds: - It is an ion-binding or hydrogen-binding may

occur between drug and adsorbent. Example, decreasing of drugs absorption by

adsorbing them on Kaoline surface.

c. By chelating of compounds: - A decrease in drug absorption due to the formation

of insoluble compound that is unable to penetrate the intestinal mucosa. Example,

complexation of tetracycline with of calicium, aluminium and zinc in antacids

(Kwon Y., 2001).

d. Alteration of gastric emptying intestinal motility: - drug absorption is affected due

to change in gastric emptying that caused by some drugs as metoclopramide.

e. Effects of intestinal blood flow: - Intestinal blood flow can affect the absorption

of lipophilic compounds, for example: - by vasoactive agents.

f. Alteration of active and passive intestinal transport.

g. Alteration of intestinal cytochrome P450 isozyme activity: - CYP3A4 and

CYP3A5 represent 70% of total intestinal P450 isozymes which are responsible

for phase I oxidative metabolism of orally administered drug and considered the

major determinant of their systemic bioavailability. For example, Grapefruit juice

can increase the maximum concentration (Cmax), area under the curve (AUC),

and bioavailability of some orally administered medications that are metabolized

by cytochrome P-450 3A4 (Honig P.K. et al.,1996; Hukkinen S.K. et al., 1995).

h. Alteration of intestinal P-glycoprotein activity: - P-glycoprotein is an efflux pump

found in many human tissues including the luminal surface of the intestinal

epithelium which has an important role in drug absorption. Therefore, induction

or inhibition of P- glycoprotein activity can lead to significant drug exposure

alterations. Example: - Verapamil is a P-glycoprotein inhibitor.

i. Other mechanisms can enhance drug absorption either by mucoadhesive

properties through ionic interaction with negative charges of the mucus like

chitosan (water soluble polymers) that enhance the absorption of proteins (Thanou

M. et al., 2001), or by hydrophilic property that cause changing the solid surface

property and effecting the tight junction by adsorption on the drug surface,

11

example: sodium lauryl sulphate can enhance the absorption of Cyclosporine (Lee

E. et al., 2001).

1.3.2.2 Alteration of distribution

The distribution of the drug may be affected by plasma protein binding.

Competition for the protein binding sites cause displacement of drugs to each other from

these sites depending on their affinity which result in an increase in free or unbound

fraction of the displaced drug, volume of distribution and the drug clearance which alters

its therapeutic effect. Since the pharmacological activity is related to only the unbound

drug fraction, therefore, such interactions are considered to be of clinical importance

especially when the displaced drug is highly protein bound, so that a small decrease in its

bound fraction cause a large increase in its unbound fraction. Example: - erythromycin

can increase warfarin concentration by this mechanism (Corrie K., 2011).

1.3.2.3 Affecting of drug metabolism

Drug metabolism generally is converting lipophilic compounds to ionized one to

be excreted through kidney. The mechanism of drug metabolism can be classified to

phase I reactions and phase II reactions. Phase I include oxidation, reduction, and

hydrolysis which occur in the membrane of hepatocyte while phase II is a conjugation

reaction that occur in the cytosol of the hepatocyte. The majority of Phase I oxidative

reactions are result from the action of mono-oxygenases called cytochrome P450

enzymes system in liver. There are different types CYP450 enzymes. However, CYP1, 2

and 3 represent 70% of total hepatic CYP450 (Wynn G.H., 2009).

The metabolizing enzymes can be either induced or inhibited by some agents.

Enzyme inducers induce drug metabolism and decrease its effect through decreasing its

plasma concentration and duration of action. On the other hand, enzyme inhibitors inhibit

drug metabolism and increase its effect and/or adverse effect through increasing its

plasma concentration (Wynn G.H., 2009). Induction of the metabolic enzymes occurs

through synthesis of new enzyme protein or decreasing enzyme degradation (Craig C.R.

and Stitzel R.E., 2004). This enzyme induction results in either a loss in the therapeutic

efficacy or increasing the side effects by production of toxic metabolite. On the other

12

hand, enzyme inhibition is due to decreasing of enzyme synthesis or increasing of

enzyme destruction (Corina I. and Mino C., 2005). The co-administered drugs are

competitively inhibiting the metabolic enzymes depending on their affinities. For

example, CAM and lansoprazole compete on CYP450.

The mechanism of metabolic enzyme inhibition can be classified to competitive,

non-competitive, un-competitive and mechanism-based inhibition. Competitive inhibition

between drugs of similar structure and affinity to the metabolic enzymes is dependent on

their concentrations (Coleman M.D., 2005). Example, omeprazole compete with oltipraz

on CYP1A1 & CYP3A2 (Lee D.Y. et al., 2007). In Non-competitive inhibition, the

inhibitor can change the conformation of the enzyme active site and make it unsuitable

for drug binding by its binding to other site on the enzyme which is called the allosteric

site, example, omeprazole and lansoprazole are considered as a non-competitive CYP3A4

inhibitors in different binding sites (Coleman M.D., 2010). Un-competitive inhibition is

performed through the formation of enzyme-substrate complex. This complex is

functionless with a higher affinity to the binding site. Mechanism-based inhibitor can

cause either destruction of the active site or form a covalent bond that delay product

release, example, drug-food interaction as grape fruit juice with many drugs can affect

their bioavailability through CYP3A4 inhibition(Coleman M.D., 2005).

The mechanism of metabolic enzyme inhibition also can be classified into reversible and

irreversible inhibition.

The reversible inhibition occurs by the formation of weak bonds between the

compound and CYP isozymes which can occur competitively and non-competitively.

This type of inhibition depends both on the affinity of substrate and inhibitor of the

enzyme, and on the concentration of the inhibitor at the site of enzyme (Berg J. et al.,

2002).

The irreversible inhibition occurs due to the formation of irreversible covalent

bond by the inhibitor that causes enzyme inactivation. This reaction depends on the total

amount of CYP isozyme, the total amount of inhibitor, and the rate of new enzyme

13

synthesis. For example:- inhibition of Choline esterase (ChE) enzyme by

organophosphorous compounds (Brenner G.M., 2000).

1.4 Drug-food interactions

A food–drug interaction is the outcome of a physical, chemical, or physiologic

relationship between a drug and a product consumed as food or a botanically-derived

nutrient (Santos C.A. and Boullata J.I., 2005; Genser D., 2008). Such an interaction may

affect health status due to altered Pharmacokinetic (PK) and/or pharmacodynamic (PD)

of the drug or dietary substance. A dietary substance can increase the AUC of the drug

increasing the risk of adverse events and toxicity, or decrease its AUC, leading to

therapeutic failure (Santos C.A. and Boullata J.I., 2005). The mechanisms of such effects

generally include physiologic, physicochemical, and/or biochemical processes (Fleisher

D. et al., 1999).

Interactions between medications and dietary substances, as foods or supplements,

remain a relatively understudied and misunderstood area of pharmacotherapy.

1.4.1 Mechanisms of drug-food interactions

1.4.1.1 Physiologic and physicochemical mechanisms

Physiologic and physicochemical mechanisms include altering of drug absorption,

distribution, metabolism, and/or excretion (ADME) by dietary substances.

a. Physiologic (mechanical) mechanisms:

Alterations of some processes can lead to reduced absorption of some drugs (e.g.,

penicillins, angiotensin-converting enzyme inhibitors) (Singh B.N., 1999). Such

processes include delayed gastric emptying, increased bile or splanchnic blood flow, and

changing of GI pH.

b. Physicochemical mechanisms:

By binding of the drug to the food substances. For example, reducing of

phenytoin absorption via it’s binding to proteins and salts in enteral formulations,

(Lourenço R., 2001). Absorption of some tetracyclines and fluoroquinolones can be

reduced through their binding to divalent cation-containing products (e.g., calcium) (Polk

14

R.E., 1989; Jung et al., 2007) and potential therapeutic failure. High fat meals can

increase drug absorption (e.g., antiretroviral protease inhibitors as saquinavir, atazanavir)

by improving their solubility (Plosker G.L. and Scott L.G., 2003; Le Tiec C. et al., 2005).

1.4.1.2 Biochemical mechanisms

Biochemical mechanisms include:

a. Interference with co-factor formation or function. For example, vitamin K-rich

foods interfere with co-factor function. They can increase risk of bleeding when

consumed with the anticoagulant, warfarin by disrupting vitamin K metabolism

(Holbrook A.M. et al., 2005).

b. Potentiation of drug pharmacodynamic. For example, tyramine-rich diet can

potentiate a hypertensive crisis whene consumed with Isoniazid (To treat

tuberculosis) or monoamine oxidase inhibitors (For depression) by inhibition of

the endogenous and dietary amines breakdown (Brown C. et al., 1989; Self T.H.

et al., 1999).

c. Modification of drug metabolizing enzyme/transporter function (Jiang X.L. et al.,

2011).

d. Some beverages contain substances that can influence drug disposition by means

of modulation of drug metabolizing enzymes and transporters in the intestine

(Jang G. and Harris R., 2007; Sergent T. et al., 2009; Nirmala K. et al., 2010).

1.5 Inhibition of intestinal biochemical processes

Many of in vitro and in vivo studies have established inhibitory effects on enzymes

and transporters involved in drug disposition, particularly those in the intestine (Huang

S.M. et al., 2008).

15

1.5.1 Intestinal enzymes and transporters involved in drug disposition that can be

affected by certain beverages

1.5.1.1 Enzymes

a. Cytochrome P450 3A:

The cytochromes P450 are the predominant enzymes involved in phase I

drug metabolism (Shen D.D. et al., 1997). The enteric CYP3A subfamily is the

most common one that has been established to influence drug disposition in vivo

(Lin J.H. and Lu A.Y., 2001; Paine M.F.et al., 2006) and responsible for the

oxidative metabolism of more than half of pharmaceutical agents on the market

(Gibbs M.A. and Hosea N.A., 2003). It is mainly composed of CYP3A4 and

CYP3A5 in adults.

b. Esterase:

Esterases are necessary for prodrugs (e.g., enalapril, lovastatin) to form the

active species through hydrolytic cleavage of the ester bond (Patchett A.A., 1984;

Sabra R., 1988).

Inhibition of enteric esterase activity increase stability of the ester which

leads to higher absorption of the prodrug and higher exposure to active metabolite

due to rapid hydrolysis in plasma (Liederer B.M. and Borchardt R.T., 2006). The

clinical significance of esterase inhibition by GFJ is under investigation.

There are other enteric enzymes may be involved in beverage-drug interaction but

they are still under investigation. Example:

c. Uridine diphosphate glucuronosyltransferase.

d. Sulfotransferase.

1.5.1.2 Transporter-mediated efflux and uptake

a. P-glycoprotein:

The efflux transporter P-glycoprotein (P-gp) located on the apical luminal

membrane of enterocytes is another factor that may alter systemic drug

16

concentrations. Through inhibition of this transporter the substrates are returned

back to the intestinal lumen, as a result, lowering systemic drug concentrations

(Huang S.M. et al., 2010). Therefore, as with CYP3A, enteric P-gp inhibition

thought to increase systemic drug exposure.

b. Organic anion transporting polypeptide:

Organic anion transporting polypeptides (OATPs) are transmembrane

transport proteins that facilitate uptake of a number of endogenous compounds

(e.g., bile acids, hormones) and drugs (Hagenbuch B. and GUI C., 2008). Of the

11 human OATP family members, OATP1A2 and OATP2B1 have been reported

to be expressed on apical membranes of enterocytes (Kim R.B., 2003). For

example: GFJ significantly reduced mean aliskiren AUC by 61% with no change

in half-life, reliable with inhibition of intestinal but not hepatic OATPs

(Tapaninen T. et al., 2010).

1.6 Pomegranate juice (PJ)

The pomegranate (Punica granatum L.) is considered as a popular ‘superfood’

since it has high antioxidant content and disease prevention properties (Tzulker R. et al.,

2007).

Most phytochemicals found in pomegrante juice are ellagitannins, pelargonidin,

punicalin, punicalagin, anthocyanins,cyanidin, and ellagic acid (Nawwar A.M. et al.,

1994; El-Toumy A.A. et al., 2002).The PJ’s therapeutic and prevention activity on many

diseases could be due to the presence of these phytochemicals (Gil M.I. et al., 2000;

Machado T.B. et al., 2002; Aviram M. et al., 2004; Seeram N.P. et al., 2005).

The effect of pomegranate juice on carbamazepine metabolism was studied in

human’s liver (in vitro) and on carbamazepine pharmacokinetic in rats; in the results,

pomegranate juice inhibited hepatic CYP3A-mediated metabolism of carbamazepine in

vitro study and inhibited intestinal CYP3A4 activity after single of pomegranate juice

(Hidaka M. et al., 2005). Another clinical study suggested lack of clinical significance of

the effect of pomegranate juice when it is given with a single oral dose of midazolam

(Farkas D. et al., 2007). A more recent study evaluated the effect of repeated

commercially available pomegranate juice consumption on the CYP3A-mediated

http://www.phytochemicals.info/phytochemicals/anthocyanins.php

http://www.phytochemicals.info/phytochemicals/cyanidin.php

http://www.phytochemicals.info/phytochemicals/ellagic-acid.php

17

metabolism of midazolam (Misaka S. et al., 2011). Pomegranate juice did not

significantly alter midazolam PK. Repeated consumption of pomegranate juice may not

cause a clinically relevant interaction with midazolam. Since there was no information

provided about the composition of the test juice, the enteric CYP3A inhibition potential

of pomegranate juice is not fully addressed yet.

1.7 Grapefruit juice (GFJ)

Grapefruit Juice (GFJ) is one of the most known dietary substances that shown to

inhibit many enteric CYP3A substrates metabolism (Mertens-Talcott S. U. et al., 2006;

Seden K. et al., 2010; Hanley M.J et al., 2011).

GFJ can inhibit CYP3A in the intestine, the pre-systemic (first-pass) drug

metabolism, and increase systemic drug exposure (Paine M.F. and Oberlies N.H., 2007).

It is proved that the Inhibition is in the gut, as there is no effect on the elimination half-

life of orally adminisftered substrates and on the PK of intravenously administered

substrates (Kupferschmidt H.H. et al., 1995). However, some cases are reliable with

inhibition of hepatic CYP3A by GFJ when consumed regularly in abundant uncommon

volumes (Lilja J.J. et al., 2000). For example, GFJ when is consumed with docetaxel

(Valenzuela B. et al., 2011), also intravenous amiodarone administration after regular

GFJ consumption (≥1–1.5 L/day) (Agosti S. et al., 2012).

The enhancement of the systemic drug exposure by GFJ can be sufficient to

produce adverse events (Saito M. et al., 2005). For example, GFJ with some statins can

cause muscle pain and severe hypotension when consumed with some calcium channel

blockers.

The mechanism of intestinal CYP3A inhibition include reversible, mechanism-

based (Schmiedlin-Ren P. et al., 1997; Paine M.F. et al., 2004, 2005), and degradation of

the protein (Lown K.S. et al., 1997).

1.8 Seville orange juice

Seville orange juice has been shown to inhibit enteric CYP3A4 in vitro and in

healthy subjects (Edwards D.J. et al., 1999; Guo L.Q. et al., 2000; Malhotra S. et al.,

2001; Penzak S.R. et al., 2002; Mouly S.J. et al., 2005).For example, Seville orange juice

18

decreased unexpectedly mean AUC of colchicine by 20% and delayed tmax by one hour

(Wason S. et al., 2011).

1.9 Tea

Tea is the most widely consumed beverage in the world, second only to water

(Dreosti I.E., 1996; Vinson J.A. et al., 2004). The majority of controlled clinical studies

to date evaluating the effect of repeated green tea administration (given as extract) on

CYP activity have not demonstrated clinically significant interactions (Donovan J.L. et

al., 2004; Chow et al., 2006). However, a two-fold increase in tacrolimus levels observed

while consuming of green tea (Vischini G. et al., 2011). Another study showed an

increase in the AUC of 5-fluorouracil by ~425% while green tea consumption (Qiao J. et

al., 2011).

1.10 Chromatography

1.10.1 Definition

Chromatography is a physical separation process in which the sample mixture is

distributed between two phases in the chromatographic bed (column or plane). One phase

is stationary whilst the other passes through the chromatographic bed which is the mobile

phase. The separation occurs because of difference in affinity between analytes and

stationary phase (James M.M., 2009; Meyer V., 2010). The stationary phase is either a

solid, porous, surface-active material in small-particle form or a thin film of liquid coated

on a solid support or column wall. The mobile phase is a gas or liquid. If gas is used, the

process is known as gas chromatography; the mobile phase is always liquid in all types of

liquid chromatography (James M.M., 2009).

1.10.2 Types of chromatography

There are different types of chromatography. Gas chromatography (GC), in which

the mobile phase is gas, while in high performance liquid chromatography (HPLC), thin-

layer chromatography, and paper chromatography (PC), the mobile phase is liquid. GC

and HPLC are the most widely used now a day due to their advanced development

(James M.M., 2009).

19

A. Gas chromatography (GC)

(GC) is a more advanced and popular chromatography technique as well as

(HPLC). It is consist of a gas as a mobile phase and non-volatile liquid or solid particles

as a stationary phase. GC is premier technique for analysis of volatile and thermally un-

labile compounds. (GC) is fast analysis, highly accurate quantification (1-5% RSD)

technique with Small samples (µl or µg needed) and relatively simple and cheap (Skoog

D.A., 2007; McNair H.M. and Miller J.M., 1998). (LC) and (HPLC) are not limited to

sample volatility or thermal stability as in (GS). Furthermore, there are two phases

(mobile and stationary) to compete for the analyte not only one phase (stationary) as in

(GC) (Dennis J.R., 1981).

B. liquid chromatography (LC)

Liquid-solid column chromatography is a chromatography technique in which a

liquid mobile phase filters down slowly through the solid stationary phase, bringing

the separated components with it.

Chromatography is effective because different components within a mixture are

attracted to the adsorbent surface of the stationary phase with varying degrees depending

on each components polarity and its unique structural characteristics, and also its

interaction with the mobile phase. The separation that is achieved using column

chromatography is based on factors that are associated with the sample. So, a component

that is more attracted to the stationary phase will migrate down the separating column at a

slower rate than a component that has a higher affinity for the mobile phase. In addition,

the efficacy of the separation is dependent on the nature of the adsorbent solid used and

the polarity of the mobile phase solvent (Skoog D.A. et al., 2007).

C. High performance liquid chromatography (HPLC)

High performance liquid chromatography is a powerful tool in quantitative

analysis (Karen and Liyuan, 2005). It is basically a highly improved form of column

chromatography. Instead of a solvent being allowed to drip through a column under

20

gravity, it is forced through under high pressures of up to 400 atmospheres that makes it

much faster (Drenthe, 2010).

It also allows using a very much smaller particle size for the column packing

material which gives a much greater surface area for interactions between the stationary

phase and the molecules flowing past it. This allows a much better separation of the

components of the mixture (Drenthe, 2010). The other major improvement over column

chromatography concerns the detection methods which can be used. These methods are

highly automated and extremely sensitive. Liquid chromatography inlets are used to

introduce thermally labile compounds not easily separated by gas chromatography.

Because these inlets are used for temperature sensitive compounds, the sample is ionized

directly from the condensed phase.

1.10.3 HPLC advantages

i. Speed of analysis (minutes) with higher resolution (column packing material with

very much smaller particle size gives a much greater surface area for interactions

between the stationary phase and the analyte which means better separation).

ii. Columns can be reused without regeneration or repacking.

iii. Higher sensitivity (ng to fg).

iv. Greater reproducibility (less dependent on the operator proficiency).

v. Automated, precise, and accurate.

vi. Used for various sample types (labile compounds, ions, and biomolecules)

(Hamilton R.J. and Sewell P.A., 1982; Marvin C. 2007; Snyder L. et al., 2011).

1.10.4 HPLC limitations

1- Complexity.

2- Irreversibly adsorbed compounds cannot be detected.

3- Low sensitivity for some compounds.

4- Costly (Marvin C. 2007).

21

1.10.5 Types of chromatography detectors

The chromatographic detector is able to establish both the identity and

concentration of eluting components in the mobile phase. There are different types of

detectors available to meet different sample necessities (Meyer V., 2010) these are some

of them:

1- Ultraviolet (UV) detector: is the most commonly used. Its principle of work depends

on the light absorbing property of the functional groups that are present in the eluting

molecules.

2- Fluorescence detector: Is more sensitive than (UV) detector but it is less universal

since the naturally fluorescent compounds are fewer compared to light absorbing

compounds.

3- Photo Diode Array (PDA) detector: In this detector, a large number of diodes are

incorporated to serve as detector elements so can monitor more than one absorbing

component at different wavelengths. This save time and cost on expensive solvents.

4- Electrochemical detector: This detector depends on the electrochemical oxidation or

reduction of sample on the surface of the electrode. However, it is sensitive for the

mobile phase composition or flow rate (higher possibility of interference) and need

longer time of analysis.

5- Mass spectrometry: In this type the detection is based on three principles:

a- The fragmentation of molecules: This means the conversion of the gaseous

molecules to ions by an ion source.

b- Separation of ions according to their mass to charge ratio by mass analyzer which

is the heart of the mass spectrometer in presence of electromagnetic field.

Finally, after the ions are separated, they are detected.

c- Mass spectrometers should have a vacuum system to keep the low pressure which

necessary to reduce ion-molecule reactions, scattering, and neutralization of the ions.

(Gross J.H., 2004).

22

1.10.6 High performance liquid chromatography/Mass spectrometry

The direct coupling of liquid chromatography with mass spectrometry (LC–MS)

is a technique that was described in 1973 by Baldwin and McLafferty. With The

development of electrospray ionization (ESI) in 1989 this technique becomes the most

powerful analysis tool to analyze large, polar, heat-sensitive molecules (Fenn J.B. et al.,

1989). The power of LC–MS over other techniques revert to its high specificity,

sensitivity, and ability to concurrently measure several analytes in a single assay,

moreover, performing fast, easy and precise assays through a short time (Arpino P.,

1992). Now a day it is used in variable clinical laboratory analysis (Vogeser M., 2003;

Vogeser M. and Seger C., 2008) and in many pharmaceutical, environmental, and

biochemical applications (Niessen W.M.A., 1999).

1.10.7 Method validation

The results obtained from animal toxicokinetic studies and clinical trials support

the safety and efficacy of a medicinal drug substance. Therefore, the bioanalytical

methods used to establish drug pharmacokinetics should be well characterized and

validated in order to give reliable results. According to Guideline on bioanalytical

method validation (EMA, 2011), (USP 29), and (FDA, 2001) the parameters used in the

validation of the analytical HPLC method are:

1.10.7.1 Standard calibration curve

Standard Calibration curve is the response of the instrument with regard to the

concentration of analyte wich should be evaluated over a specified concentration range.

Therefore, the concentration range that expected should be known. This range should be

covered by the calibration curve range, represented by a minimum of six calibration

concentration levels includes the LLOQ and ULOQ in addition to the blank sample

(processed matrix sample without analyte and without IS (internal standard) ) and a zero

sample (processed matrix with IS). A relationship between the response of the instrument

and the concentration of analyte should be applied. The blank and zero samples should

not be taken into consideration to calculate the calibration curve parameters. A minimum

23

of 3 standard calibration curves should be reported. The back calculated concentrations of

the calibration standards should be within ±15% of the supposed value, except for the

LLOQ for which it should be within ±20% (EMA, 2011).

1.10.7.2 Linearity and range

The linearity of an analytical procedure is its ability to elicit test results that are

directly, or by a well-defined mathematical transformation, proportional to the

concentrations of analyte in samples within a given range. It should be established

initially by visual examination of plot of signals as a function of analyte concentration of

content. If there appears to be a linear relationship, test result should be established by

appropriate statistical methods (e.g., by calculation of regression line by the method of

least squares).

Linearity is usually expressed in terms of variance around the slope of the

regression line calculated according to an established mathematical relationship from test

result obtained by the analysis of samples with varying concentrations of analyte.

The range of an analytical method is the interval between the upper and lower

levels of analyte in which it is found to be accurate, precise and linear (USP29).

1.10.7.3 Precision

The precision of the analytical method describes the closeness of repeated

individual measures of analyte. Precision is expressed as the relative standard deviation

(RSD %) or the coefficient of variation (CV %). Precision demonstrated for the LLOQ,

low, medium and high QC samples, within a single run and between different runs

(EMA, 2011). The precision is a measure of the reproducibility of the analytical method

under normal operating circumstances.

CV% =STDV

mean× 100

24

A- Within-run precision

There should be a minimum of five samples per concentration level for the

validation of within-run precision includes LLOQ, low, medium and high QC samples in

the same run. The within-run CV value should not exceed 15% for the QC samples,

except for the LLOQ which should not exceed 20% (EMA, 2011).

B- Between –run precision

LLOQ, low, medium and high QC samples from at least three runs analyzed on at

least two different days should be evaluated for the validation of the between-run

precision. The between-run CV value should not exceed 15% for the QC samples, except

for the LLOQ which should not exceed 20% (EMA, 2011).

1.10.7.4 Accuracy

The accuracy of an analytical method describes the nearness of the determined

value obtained by the method to the nominal concentration of the analyte (expressed in

percentage). Accuracy should be assessed on samples spiked with known amounts of the

analyte (EMA, 2011). It is the measure of exactness of analytical procedure and it is

defined as (determined value/true value) x100%.

Accuracy should be evaluated for the values of the QC samples obtained within

the same run (the within run accuracy) and in different runs (the between-run accuracy)

(EMA, 2011).

1.10.7.5 Lower limit of detection

The lower limit of Detection (LLOD) is the lowest concentration of analyte in a

sample which can be detected, but not necessarily quantitated, under the stated

experimental conditions (USP 29).

25

1.10.7.6 Lower limit of quantification

The lower limit of quantification (LLOQ) is the lowest concentration of analyte in

a sample which can be quantified consistently, with an acceptable accuracy and precision.

Moreover, the analyte signal of the LLOQ sample should be at least 5 times the signal of

a blank sample (EMA, 2011).

1.10.7.7 Selectivity

It is the ability of the analytical method to differentiate the analyte(s) of interest

and IS from endogenous components in the matrix or other components in the sample.

Selectivity should be proved using at least 6 individual sources of the appropriate blank

matrix, which are individually analysed and evaluated for interference. Normally,

absence of interfering components is accepted where the response is less than 20% of the

lower limit of quantification for the analyte and 5% for the internal standard (EMA,

2011).

1.10.7.8 Specificity

Specificity is done to indicate that there is no interference from excipient,

degradation products, and/or impurities (USP 29). It is examined by analyzing blank and

standard zero samples of the biological matrix that obtained from at least six different

sources. Each of the blank and zero standards are tested for interference (FDA, 2001).

1.10.7.9 Recovery

The recovery of an analyte in an assay is the response obtained from the extracted

amount of the analyte from the biological matrix, compared to the response obtained

from the true concentration prepared in mobile phase (out of the extraction method).

Recovery relate to the extraction efficiency of an analytical method. Recovery of the

analyte and the internal standard should be consistent, precise, and reproducible.

Recovery experiments should be performed at three concentrations (low, medium, and

high) (FDA, 2001).

26

1.11 Previous analytical studies for quantification of Clarithromycin in plasma

There are many reported methods for the quantification of CAM in plasma. These are

some examples:

A high-performance liquid chromatographic method was developed for the

quantitative determination of CAM in rat plasma with amperometric detection by

utilizing Roxithromycin as an internal standard. The separation was performed on a

reversed-phase column (YMC-Pack ODS-AP of 25036.0 mm I.D, 5 µm). The mobile

phase consisted of acetonitrile and 0.05 M phosphate buffer (pH 7.2) (43:57, v/v). The

drug was extracted from 150 ml, the linearity of the calibration curves were preserved

over the concentration ranges of 0.03–3.0 mg/ml. Coefficients of variation and relative

error were less than 9% and 67%, respectively (Taninaka C. et al., 2000). Comparing

with the current method, this method has lower sensitivity with greater plasma sample.

Moreover, the detection method has disadvantages of lower specificity and longer time of

analysis.

By Van Rooyen G.F. and others (2002), a sensitive method for the determination

of CAM in plasma is described, using high-performance liquid chromatographic

separation with tandem mass spectrometric detection. Samples were prepared using

liquid-liquid extraction and separated on a C18 column with a mobile phase consisting of

acetonitrile, methanol and acetic acid. Detection was performed by a mass spectrometer

in the multiple reaction monitoring (MRM) mode (LC-MS-MS) using Spray ionization.

The mean recovery of CAM was 87.3%, with a lower limit of quantification of 2.95

ng/ml when using 0.3 ml plasma (van Rooyen G.F. et al., 2002). This method has more

sensitivity but with greater plasma sample size and complicated extraction method

comparing with the protein precipitation method.

In 2003 an analytical method was developed for the simultaneous analysis of

CAM and its 14-hydroxy-clarithromycin metabolite in rat plasma. Samples were

extracted with n-hexane/2-butanol (4:1) and the internal standard was roxithromycin. A

Kromasil ODS 5 mm (7534.6 mm I.D.) column was used with a mobile phase consisting

of acetonitrile/ (aqueous phosphate buffer pH 7, 0.086 M) (45:55 v/v). The analysis time

27

was less than 8 min. The limits of quantitation for CAM were 0.15 µg/ml (Wibawa J.I.D.

et al., 2003). This method has a disadvantage of using phosphate buffer which has

negative effects on HPLC column on the long period run. The analysis time (8 min) is

twicly greater than that for the current method. Moreover, the limit of quantitation for

CAM was higher (0.15µg/ml).

In 2007, by Li W. et al., a novel HPLC method using pre-column derivatization

and UV detection at 275nm for the determination of CAM in rat plasma has been

validated. CAM was extracted from plasma sample spiked with internal standard

(erythromycin) under alkaline condition with ethyl ether and derivatizated with

trimethylbromosilane. The analyses were run on a C18column, maintained at 40◦C during

elution, using a mobile phase comprised of potassium dihydrogen phosphate (50mM, pH

6.8, contained 0.7% triethylamine), acetonitrile, and methanol (30:45:25, v/v/v). The

standard calibration curve for CAM was linear (R²=0.9998) over the concentration range

of 0.1–10µg/ml in rat plasma. The limit of detection (LOD) and limit of quantitation

(LOQ) was 30ng/ml and 0.1µg/ml respectively. The intra- and inter-day assay variability

range was 2.6–7.4% and 3.3–8.5%, respectively. This method has been successfully

applied to a pharmacokinetic study of CAM in rats (Li W. et al., 2007). They used 150 µl

volume of plasma sample with LLOQ of 0.1 µg/ml which means a disadvantage of lower

sensitivity. Moreover, their method has to complete a pre-step of derivatization procedure

which is need 10 min. (longer analysis time) with a retention time of 20 min.

By Jiang Y. et al. (2007), a method has been developed for the determination of

CAM in human plasma with liquid chromatography-tandem mass spectrometry. CAM

and the internal standard, telmisartan were precipitated from the matrix (50 µl) with 200

µl acetonitrile and separated by HPLC using formic acid: 10 mM ammonium acetate:

methanol (1:99:400, v/v/v) as the mobile phase. The assay based on detection by

electrospray positive ionization mass spectrometry in the multiple-reaction monitoring

mode was finished within 2.4 min. Linearity was over the concentration range 10-5000

ng/ml with a limit of detection of 0.50 ng/ml. Intra- and inter-day precision measured as

relative standard deviation were 3.73% and 9.93%, respectively (Jiang Y. et al., 2007).

28

Another method for determination of CAM concentrations in human plasma using

protein precipitation and liquid chromatography-tandem mass spectrometry was

developed and validated by Shin J. et al. (2008). Plasma proteins were precipitated with

acetonitrile and roxithromycin was used as the internal standard. The mobile phase

consisted of water and methanol (30:70 v/v) containing 0.1% formic acid and 5mM

ammonium acetate. The flow rate was 0.22 mL/min and the total run time (injection to

injection) was less than 3 min. Detection of the analytes was achieved using positive ion

electrospray tandem mass spectrometry in selected reaction monitoring (SRM) mode.

The linear standard curve ranged from 100 to 5000 ng/mL and the precision and accuracy

(inter- and intra-run) were within 7.9% and 4.9%, respectively (Shin J. et al., 2008).

In 2009, a method developed is based on the precipitation of proteins in human

serum with precipitation reagent containing the internal standard (cyanoimipramine) and

subsequently high-performance liquid chromatography (HPLC) analysis and tandem

mass spectrometry (MS/MS) detection in an electron positive mode. The mobile phase is

consisted from an aqueous buffer (containing ammonium acetate 10 g/L, acetic acid

35mg/L and trifluoroacetic anhydride 2 mL/L water), water and acetonitrile. The analyses

were run on a C18, 50mm, 2.1 mm, 5 µm). The method validation included selectivity,

linearity, accuracy, precision, dilution integrity, recovery and stability. The calibration

curves were linear in the range of 0.10–10.0 mg/L for CAM and 14-hydroxy CAM and

0.20–5.0 mg/L for rifampicin and 25-desacetylrifampicin (Velde F. et al., 2009). This

method has a disadvantage of lower sensitivity.

Oswald S. et al. (2011) developed a method to measure concentrations

of CAM, rifampicin and their main metabolites in horse plasma. Drugs were measured

after extraction with methyl tert-butyl ether using roxithromycin as internal standard and

liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for

detection. The chromatography was done isocratically using 25 mM ammonium acetate

buffer (pH 4)/acetonitrile (45%/55%, flow rate 200 μl/min). The column used was (C18,

100 mm, 2.1 mm, 3.0 µm). The MS/MS analysis was performed in the positive ion mode.

The method was validated according to selectivity, linearity, accuracy, precision,

http://www.ncbi.nlm.nih.gov/pubmed?term=Shin%20J%5BAuthor%5D&cauthor=true&cauthor_uid=18639501


http://www.ncbi.nlm.nih.gov/pubmed?term=Oswald%20S%5BAuthor%5D&cauthor=true&cauthor_uid=21310577

29

recovery, matrix effects and stability. The validation ranges for all substances were 2.5-

25 for the low and 25-250 ng/ml for the high validation range (Oswald S.et al., 2011).

CAM quantification has been previously determined by ultra-performance liquid

chromatography–tandem mass spectrometry (UPLC–MS/MS) for determination of nano

formulated drug in rat plasma. This method presented satisfactory results in terms of

sensitivity, precision, accuracy, and recovery, for the first time, of quantitatively

analyzing CAM in rat plasma (Wang Y.J. et al., 2012).

1.12 Previous analytical studies for quantification of Metronidazole in plasma

Relatively few reported methods for the determination of MTZ in plasma, examples are:

HPLC-UV method has been developed for the separation and quantitation of

metronidazole and its hydroxylated metabolite in human plasma, saliva and gastric juice.

The limits of quantitation (0.5-ml sample) were at least 0.25µg/ml for metronidazole and

0.20/µg/ml for its hydroxy metabolite. A Hypersil ODS 5 µm (150×4.6 mm I.D.) column

was used with a mobile phase of acetonitrile-aqueous 0.05 M potassium phosphate buffer

(pH 7) containing 0.1% triethylamine (10:90) with a flow-rate of 1.0 ml/min (Jessa M.J.

et al., 1996).

Galmier M.J. et al., developed HPLC method for determination of metronidazole

in human plasma. The separation of compounds was performed on a RP 18 column with

acetonitrile–aqueous 0.01 M phosphate solution (15:85, v/v) as mobile phase. Detection

was performed by UV absorbance at 318 nm. The concentration range was 0.01 to 10 µg/

ml. Within-day and between-day precision and accuracy 4% between 1 and 10 µg ml and

8.3 and 7.2% respectively for the limit of quantitation (Galmier M.J. et al., 1998).

High performance liquid chromatography (HPLC) assay was developed to

quantitate metronidazole, and omeprazole in plasma and gastric fluid. The HPLC system

consisted of a multi-phase column combining anion exchange and reversed phase

separation, and a variable wavelength UV detector set at 254 nm. The mobile phase was a

http://www.ncbi.nlm.nih.gov/pubmed?term=Oswald%20S%5BAuthor%5D&cauthor=true&cauthor_uid=21310577

http://www.sciencedirect.com/science/article/pii/S1570023212001821

30

mixture of 0.1 M sodium phosphate buffer: methanol: acetonitrile (60:20:20) with final

pH adjusted to approximately 7.0. Metronidazole and omeprazole were extracted by

adsorption onto a C2-bonded silica gel solid phase extraction column, and eluted with

methanol. The extract was dried, reconstituted in a solution of acetyl salicylic acid

(ASA), and then injected into the HPLC system. Using 0.3 ml of sample, the assay

sensitivity was less than 0.1 µg/ ml and linear up to 10 µg/ ml. Both intra- and inter-assay

CV were greater than 15% (Yeung P.K. et al., 1998).

Liquid chromatographic–mass spectrometric (LC–MS/MS) method for

simultaneous determination of metronidazole and spiramycin I concentrations in human

plasma, saliva and gingival crevicular fluid (GCF) was developed by Sagan C. and

others. Ornidazole was used as an internal standard, and sample pre-treatment consisted

of a liquid–liquid extraction. A 5 µm Kromasil C18 column (150 mm×4.6 mm i.d.,

particle size 5 µm) was used with acetonitrile, water and formic acid gradient at a flow

rate of 0.9 ml/min (Sagan C. et al., 2005).

Tavakoli N. and others developed and validated reversed phase-HPLC method to

measure simultaneously the amount of amoxicillin and metronidazole at single

wavelength (254nm). C18 column with buffered mobile phase (pH 4.0) and UV detection

at 254 nm was made. The linearity for concentrations between 0.13 and 300 µg/ml for

metronidazole were established. Intra and inter-day precision were less than 2.5%. The

limits of detection (LOD) and quantification were 0.10 and 0.13 µg/ml for metronidazole

(Tavakoli N. et al., 2007).

Most of the analytical methods that were previously used for MTZ quantification

(by Jessa M.J. et al.(1996), Galmier M.J. et al., 1998, Yeung P.K. et al., 1998, and by

Tavakoli N. et al., 2007) based on phosphate buffer solution as a mobile phase with UV

detection. On the other hand, one method was used for MTZ quantification (by Sagan C.

et al., 2005) by using LC-MS/MS method simultaneously with spiramycin but with

liquid-liquid extraction method.

31

According to our knowledge, this is the first time that a single and simple

analytical method by HPLC/MS was used for quantification of both CAM and MTZ

present in the same biological fluid (rat plasma) with a single extraction method using

protein precipitation.

1.13 Preclinical studies

Preclinical studies can be defined under many names, such as nonclinical studies

and preclinical development. A preclinical study is a stage of study that done before

testing on humans or what is called the clinical trials. Most preclinical studies carried out

through using of animals such as mice, chicken, monkeys, and guinea pigs. The

preclinical studies are passed if there is no effect on animal in a dangerous manner and

this gives proof to be tested on humans.

The objectives of the preclinical studies are to identify pharmacological and

toxicological effects not only before doing experiments on human but also for clinical

development. Biopharmaceuticals that are structurally and pharmacologically similar to a

product for which there is broad experience in clinical practice may need less extensive

testing for toxicity. Preclinical safety testing should consider, selection of the applicable

animal species, age, physiological state, the method of delivery, including dose, route of

administration, treatment regimen, and stability of the materials used. (Guidance for

Industry, 1997).

http://www.wisegeek.com/what-are-clinical-trials.htm

32

1.14 Objectives of the current study

1. To validate a simple and simultaneous analytical HPLC/MS method for

quantification of Clarithromycin and Metronidazole in plasma.

2. To study the effect of Pomegranate fresh juice on the pharmacokinetic profile of

Clarithromycin and Metronidazole.

33

Chapter 2

Materials and Methods

34

2. Materials and Methods

2.1 Reagents

a. Deionized Water, Nanopure (Fisher Sientific).

b. Rats Serum, (harvested from Rats).

c. Methanol advanced gradient grade (Fisher scientific).

d. Formic acid advanced gradient grade (Acros).

e. Hydrochloric acid (12 M) (Fisher scientific).

f. Clarithromycin and Metronidazole (was a kind gift from Hikma pharma).

g. Clindamycin (JCPR).

h. Pomegranate fruit (purchased from local supermarket).

2.2 Instrumentation

An API Mass spectrometer was used and consisted from the following:

a. Degasser (Agilent 1260).

b. Solvent delivery systems pump (Agilent 1200).

c. Autosampler (Agilent 1200).

d. Thermostat column compartment (Agilent 1200).

e. API 3200 Mass Spectrometer.

f. ACE 5, C18 (50 x 2.1 mm), 5µm.

g. Computer System, Windows XP, SP3, Data Management Software.

Other instruments

Bath Sonicator Elmasonic PH500EL.

Sartorius pH meter.

Sartorius Balance.

Sartorius Centrifuge.

35

2.3 Animals

Spargue Dawley (S.D) adult male rats supplied by the animal house of University of

Petra with a weigh range between 200 and 250 g were used in the experiments. They

were placed in air-conditioned environment (20-25 C°) and exposed to a photoperiod

cycle (12 hours light / 12 hours dark) daily. The study protocol was approved by the

ethical committee of Graduate Studies at Faculty of Pharmacy and Medical Sciences

(March, 2012).

2.4 Preparation of Clarithromycin solution to be injected orally to rats

0.18 g of CAM raw material was dissolved in 2.0 ml (0.1M HCL), vortex to complete

dissolving then complete the volume to 50.0 ml by DW to give a concentration of 3.6

mg/ml.

2.5 Preparation of Metronidazole solution to be injected orally to rats

0.18 g of MTZ raw material was dissolved in DW to give a total volume of 50.0 ml and a

concentration of 3.6 mg/ml.

2.6 Preparation of pomegranate juice to be injected orally to rats

Pomegranate fruit was cut into two pieces, squeezed by orange squeezer, then filtered to

get clear juice and freshly used.

2.7 Preparation of stock solutions for the method validation

2.7.1 Preparation of stock solution for Clindamycin as an internal standard (IS)

10 mg of Clindamycin working standard was dissolved in 10.0 ml methanol to get

concentration 1.0 mg/ml stock solution.

2.7.2 Preparation of 2 µg/ml Clindamycin IS in methanol (Precipitating agent)

1000.0 µl was taken from Clindamycin 1.0 mg/ml stock solution and complete to 500.0 ml

of methanol in dispenser bottle to obtain 2.0 µg/ml Clindamycin.

36

2.7.3 Preparation of stock solutions of Clarithromycin and Metronidazole

10 mg of CAM working standard was dissolved in 10.0 ml by methanol (100%) to get

concentration of 1.0 mg/ml as stock solution.

60 mg of MTZ working standard was dissolved in 10.0 ml by methanol (100%) to get

concentration of 6.0 mg/ml as stock solution.

2.7.4 Preparation of working solution for Clarithromycin and Metronidazole

0.50 ml was taken from each of CAM and MTZ stock solutions and diluted to 10.0 ml by

50% methanol to obtain a concentration of 50.0 µg/ml for CAM and 300.0 µg/ml for MTZ

as working solution.

2.7.5 Preparation of the mobile phase

The mobile phase consisted from aqueous solvent which was formic acid as buffer and

organic solvent which was absolute methanol. Preparation of 0.1% formic acid by taking

2.50 ml from 100% formic acid completed to 2.50 L deionized water, mixing then

sonicaton for 10 min.

2.7.6 Preparation of Clarithromycin and Metronidazole SCC serial dilution and

spiked serum.

Samples of standard curve in serum were prepared by spiking 500.0 µl from serial solution

into 4.50 ml of serum, using seven concentrations, not including zero to attain SCC

concentrations of: 0.050, 0.100, 0.200, 0.400, 1.000, 2.000 and 3.000 µg /ml for

Clarithromycin in serum and 0.300, 0.600, 1.200, 2.400, 6.000, 12.000, and 18.000 µg /ml

for Metronidazole in serum. Each concentration of the serum sample was divided to 50.0 µl

in 1.50 ml eppendorf tube and kept at (-30°C). Standard samples were given daily together

with the quality control samples. As showed in (Table 3).

2.7.7 Preparation of Clarithromycin and Metronidazole QC serial dilution and spiked

serum.

QC samples in serum were prepared by spiking 500.0 µl from serial solution into 4.50 ml of

serum to attain QC concentrations of: 0.15, 1.50 and 2.40 µg /ml for Clarithromycin in

37

serum and 0.9, 9.0, and 14.4 µg /ml for Metronidazole. Each concentration of the QC serum

sample was divided to 50.0 µl in 1.50 ml eppendorf tube and kept at (-30°C). Quality control

samples were given daily together with the standard samples. As showed in (Table 4).

Table 3: Preparation of Clarithromycin & Metronidazole SCC serial dilution and

spiked serum.

Serial solution of CAM& MTZ from working solution of 50 & 300 µg/mL,

respectively.

Sol. No:

Vol.

taken

(ml)

from

working

sol.

Total

vol.

(ml)

Conc.

of CAM

serial sol.

(µg /ml)

Conc. of

MTZ

serial sol.

(µg /ml)

Conc.

of CAM in

serum (µg

/ml)

Conc.

of MTZ

in serum

(µg /ml)

S1 0.01 1.0 5.0 3.0 0.050 0.300

S2 0.02 1.0 1.0 6.0 0.100 0.600

S3 0.04 1.0 2.5 12.0 0.200 1.200

S4 0.08 1.0 0.5 24.0 0.400 2.400

S5 0.20 1.0 05.5 60.0 1.000 6.000

S6 0.40 1.0 25.5 120.0 2.000 12.000

S7 0.60 1.0 05.5 180.0 3.000 18.000

38

Table 4: Preparation of Clarithromycin & Metronidazole QC serial dilution and

spiked serum.

Serial solution of Clarthromycin & Metronidazole from working solution of 50

µg/mL & 300 µg/mL, respectively.

Sol. No:

Vol.

taken

(ml) from

stock sol.

Total

Vol.(ml)

Conc. of

CAM serial

sol. (µg /ml)

Conc. of

MTZ

serial sol.

(µg /ml))

QC Conc.

of CAM

in serum

(µg /ml)

QC Conc.

of MTZ

in serum

(µg /ml)

S 8 0.03 1.0 1.0 9.0 0.150 0.900

S 9 0.30 1.0 00.5 90.0 1.500 9.000

S 10 0.48 1.0 20.0 144.0 2.400 14.400

2.7.8 Method of extraction

To 0.050 ml of serum sample, 500.0 μl of internal standard (2 µg/ml Clindamycin in

methanol) was added in a 1.50 ml eppendorf tube, vortex-mix for 2.0 min, centrifugation for

15 min at 14000 r.p.m., then the supernatant was transfered into auto-sampler vials.

All of the chromatographic and mass detector conditions are mentioned in (Table 5).

39

Table 5: Chromatographic and mass spectrometric conditions.

Column oven

temp/˚C

Auto-sampler

temp/˚C

Auto sampler

injection volume/

µl

Pump flow rate

mL/ min HPLC

conditions

45 4 5 1.0

Total

Time

FA 0.1% Methanol

Min. A% B%

0.00 100 0

0.50 100 0

0.51 0 100

1.50 0 100

1.51 100 0

3.00 100 0

Mobile phase

Chro

mat

ogra

phy

ACE C18 column (50 X 2.1 mm), 5µ Column type

Clindamycin (IS) MTZ CAM Retention times

(minutes)

1.62 0.27 1.69

CXP CE CEP EP DP Q3 Mass Q1 Mass Analytes MRM

detection

conditions

using

positive ion

mode

5 5 01 61 61 158.2 748.46 CAM

8 8 16 46 46 128.1 172.10 MTZ

5 5 30 71 71 126.3 425.2 Clindamycin

(IS)

TEM IS V GS 2 GS 1 CUR

MS conditions

550.0 5500.0 85 35 45

40

2.8 Analytical method validation

The validation of the method was performed in three separate days. In each day,

seven standard calibration levels (not including zero) was prepared. Serum samples of

method validation represented blank, zero, standard calibration curve, six replicates of

Quality Control (QC) samples (Q.C. Low, Q.C. Mid, and Q.C. High). The validation

parameters should not exceed the limits by the FDA Guidance for Industry.

2.8.1 Standard calibration curve and linearity

The linearity was measured by plotting the peak area ratio (analyte peak area/IS

peak area) versus nominal concentrations. The concentrations of all samples were

measured by fitting the obtained data (area ratio data) to a straight line equation. Three

calibration curves consisting of a blank, zero and seven non-zero standards prepared in

rat serum for each analyte were prepared.

The concentrations of calibration standards cover the range from LLOQ to the

highest expected concentration. The linearity was evaluated by the linear regression

(correlation coefficient, R²).

2.8.2 Intra-day accuracy and precision

Intra-day accuracy and precision was measured by analyzing six replicates for

each of QC level (Low, Mid and High) within the batch for both analytes (CAM and

MTZ).

2.8.3 Inter-day accuracy and precision

Six replicates for each QC levels (Low, Mid and High) in the batch of CAM and

MTZ were analyzed in three different days. Peak areas of all replicates of each

concentration were measured and concentrations were calculated by utilizing the

regression equation established on the corresponding day.

41

2.8.4 Sensitivity

The chromatografic response of LLOQ must be ≥ 5 times that of blank response

with accuracy 80-120% and precision ≤ 20%. Six replicates of LLOQ serum samples

were prepared along with the calibration curve.

2.8.5 Recovery

Serum samples containing concentration of QC Low, QC Mid and QC High

analytes were prepared in triplicate. The absolute peak areas obtained from injections of

the prepared serum standards were compared to the absolute peak areas of equivalent

mobile phase standards, which were prepared to contain a concentration of analytes

standard assuring 100% recovery, and same treatment for the IS. The recovery extent of

analytes and IS should be consistent, precise, and reproducible.

Recovery was performed by preparing triplicates from each QC level of serum

and triplicates from each QC level prepared in the mobile phase (FDA, 2001).

2.9 Preclinical study design

To find out the effect of PJ on CAM, six groups of twelve hour fasted- rats (six

rats for each) were administered by a single dose of PJ (5ml/kg) and other four were

administered with DW as a control, 30 min before CAM administration for both.

In case of multiple dose PJ administration, the same group numbers of rats were

administered with PJ twice daily for two days then treated as well as the single dose

administration at the third day (i.e. day of the experiment). The same thing was carried

out to study the effect of single and multiple dose administration of PJ on MTZ. Four

groups for each study were treated at the same manner with two groups administered with

DW as controls.

To study the effect of CAM-MTZ combination on the pharmacokinetic profile of

each drug, the solutions of the drugs were prepared and mixed to be administered orally

in a single dose.

42

The blood sampling was pooled from the rat’s tails along the experiment at a

specific time intervals (0, 0.50, 1.0, 2.0, 3.0, 4.0, and 6.0 hours). The blood samples were

centrifuged for 5 minutes to obtain the serum (100-125 µl) which was placed in labeled

eppendorf tubes and stored in freezer at (-30C°) until the time of analysis.

43

Chapter 3

Results and Discussion

44

3. Results and Discussion

3.1 HPLC/MS analytical method

The analytical method is one or even the most critical step in the pharmaceutical

research for determination of the drug plasma concentration and identifying its

pharmacokinetic profile (Karen and Liyuan, 2005).

HPLC has a number of advantages over other types of chromatography. Therefore,

almost all class of organic compounds can be separated by HPLC (Dennis J.R., 1981;

Hamilton R.J. and Sewell P.A., 1982) with a better separation (greater resolution) of the

substances in a mixture and much shorter analytical time (much faster) (Hamilton R.J. and

Sewell P.A., 1982).

The other thing that should be mentioned is the detection method. The method

used in this study for the detection of CAM and MTZ is the mass spectrometry which is a

greatly automated and a highly sensitive method of detection.

As a result, the combination between the separation capacity of HPLC along with

the sensitivity and specificity of MS is considered one of the most powerful technologies

for identification and quantification of drug substances (Baldwin M.A. and Mclafferty

F.W., 1973).

In the current study, the analytical method used was validated partially depending

on other previously worked methods (By Jiang Y. and others in 2007, Shin J. et al., 2008,

and Sagan C. et al., 2005). According to our knowledge, this is the first time that a single

and simple analytical method by HPLC/MS was used for quantification of both CAM and

MTZ present in the same biological fluid (rat plasma) with a single extraction method

using protein precipitation, It is sensitive with small plasma sample volume since most of

the published methods used 0.3-1 ml of human plasma and are not verified for preclinical

animal study with rat or mice where less than 0.3 ml is usually obtainable for each

plasma sample. Furthermore, the method has relatively less overall time of analysis and it

passed the validation process according to the European Medicines Agency guideline

2011 and USFDA.


45

3.2 Validation

Validation of this analytical HPLC-MS method was performed in order to be

evaluated in terms of recovery, linearity of response, precision, accuracy, and sensitivity

for quantification of CAM and MTZ.

3.2.1 Validation of day one, two, and three on linearity, accuracy, and precision data

for Clarithromycin quantification

According to USFDA, the coefficient of determination (R²) should be equal or more than

0.98 and for accuracy are 85.00-115.00% except for the LLOQ is 80.00-120% to be

within the accepted criteria

Inter and intraday accuracy, precision and linear response for standard calibration curve

and QC samples of the three days validation are explained in the following tables and

figures:

First day of validation: (Table 6) represents the standard calibration curve and intra-day

accuracy data, shows an accuracy range of 97.8% - 114.0%.

As shown in (Figure 3), R² is 0.998, which represents the strength of the correlation;

therefore, the correlation coefficient of standard calibration curve was consistently

greater than 0.99 during the validation course. Data of the standard curve with regards to

correlation, slope, R², and intercept for day one are showed in (Table 7).

Therefore, first day of validation results passed the required criteria in terms of linearity

and accuracy.

46

Table 6: Standard calibration curve of the first day of validation, intraday accuracy

data for Clarithromycin.

Theoretical Conc.

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured**

Conc. Accuracy%

0.050 17215 5897684 0.0029 0.056 112.0

0.100 37167 6267839 0.0059 0.114 114.0

0.200 74329 6347561 0.0117 0.227 113.5

0.400 140263 6195427 0.0226 0.440 110.0

1.000 351102 6179643 0.0568 1.106 110.6

2.000 647036 6415592 0.1009 1.966 98.3

3.000 964257 6406864 0.1505 2.933 97.8

*AUC Ratio=AUC Drug/AUC IS.

**Measured concentration= (AUC Ratio/0.0513) - (+ 0.000939).

Table 7: Data of the standard curve with regards to correlation, slope, R², and

intercept on the first day for Clarithromycin.

Correlation (R) Slope R² Intercept

0.9990 0.0513 0.998 + 0.000939

47

Figure 3: Plot of calibration curve levels against their analytical response and

regression linear equation on the first day of validation for Clarithromycin.

Second day of validation: (Table 8) represents the standard calibration curve and intra-

day accuracy data, shows an accuracy range of 99.6% - 114.0%.

As shown in (Figure 4), R² is 0.9994. Therefore, the correlation coefficient of standard

calibration curve was consistently greater than 0.99 during the validation course. Data of

the standard curve with regards to correlation, slope, R², and intercept for day two are

showed in (Table 8). Therefore, second day of validation results passed the required

criteria in terms of linearity and accuracy.

Untitled 1 (Clarthromycin): "Linear" Regression ("1 / x" weighting): y = 0.0513 x + 0.000939 (r = 0.9990)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0Analyte Conc. / IS Conc.

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0.12

0.13

0.14

0.15

An

aly

te

A

re

a / IS

A

re

a

Y= 0.0513 X + 0.000939

R² = 0.998

48

Table 8: Standard calibration curve of the second day of validation, intraday

accuracy data for Clarithromycin.

Theoretical Conc.

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.050 15966 5503867 0.0029 0.057 114.0

0.100 36677 6570848 0.0056 0.110 110.0

0.200 74011 6428513 0.0115 0.227 113.5

0.400 131290 6245771 0.0210 0.416 104.0

1.000 316003 6245756 0.0506 1.003 100.3

2.000 646257 6315327 0.1023 2.030 101.5

3.000 963145 6396975 0.1506 2.987 99.6




intercept on the second day for Clarithromycin.


0.9997 0.0504 0.9994 + 0.000723

49


regression linear equation on the second of validation for Clarithromycin.

Third day of validation: As seen in (Table 10) which represents the standard calibration

curve and intra-day accuracy data, shows an accuracy range of 97.4% - 114.0%.

As shown in (Figure 5), R² is 0.9986. The correlation coefficient of standard calibration

curve was consistently greater than 0.99 during the validation course. Data of the

standard curve with regards to correlation, slope, R², and intercept for day three are

showed in (Table 11).

Therefore, third day of validation results passed the required criteria in terms of linearity

and accuracy.



0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0.12

0.13

0.14

0.15

An

aly

te

A

re

a / IS

A

re

a

Y= 0.0504X + 0.000723

R² = 0.9994

50

Table 10: Standard calibration curve of the third day of validation, intraday

accuracy data for Clarithromycin.

Theoretical Conc.

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.050 16791 5661449 0.0030 0.057 114.0

0.100 35950 6516796 0.0055 0.105 105.0

0.200 65591 5697514 0.0115 0.221 110.5

0.400 132613 5646446 0.0235 0.454 113.5

1.000 320902 5983464 0.0536 1.036 103.6

2.000 646257 6072650 0.1064 2.057 102.9

3.000 931803 6168402 0.1511 2.922 97.4




intercept on the third day for Clarithromycin.


0.9993 0.0517 0.9986 + 0.000959

51


regression linear equation on the third day of validation for Clarithromycin.

The linearity and linear working range of three standard curves of CAM data based on

the calculated area ratio (obtained from three days of validation) are showed in (Table

12).

The linearity and linear working range of three standard curves of CAM data based on

the measured concentrations (obtained from three days of validation) are showed in

(Table 13). Data of three standard curves with regards to correlation, slope, R², and

intercept are showed in (Table 14).

The plot of linearity of calibration curve levels for CAM quantification against their

analytical response and regression linear equation that represents the all three days of

validation was done by plotting the calculated mean of the measured concentrations



0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0.12

0.13

0.14

0.150.15

An

aly

te

A

re

a / IS

A

re

a

Y= 0.0517X + 0.000959

R² = 0.9986

52

versus the calculated mean of the AUC ratio for each standard point showed in (Figure

6).

Table 12: Linearity and linear working range of three standard curves of

Clarithromycin data based on the calculated area ratio.

Calibration

curve

AUC Ratio for each Standard Point

0.050 0.100 0.200 0.400 1.000 2.000 3.000

1 0.0029 0.0059 0.0117 0.0226 0.0568 0.1009 0.1505

2 0.0029 0.0056 0.0115 0.021 0.0506 0.1023 0.1506

3 0.003 0.0055 0.0115 0.0235 0.0536 0.1064 0.1511

Mean 0.00293 0.00567 0.01157 0.02237 0.05367 0.10320 0.15073

STDV 0.00005 0.0002 0.00011 0.0012 0.0031 0.0028 0.0003

CV% 1.97 3.67 1.00 5.66 5.78 2.77 0.21

Min 0.0029 0.0055 0.0115 0.021 0.0506 0.1023 0.1505

Max 0.0033 0.0059 0.0117 0.0235 0.0568 0.1064 0.1511


Clarithromycin data based on the measured concentrations.

Calibration

curve Measured Concentrations for each Standard Point (µg/ml)

0.050 0.100 0.200 0.400 1.000 2.000 3.000

1 0.056 0.114 0.227 0.440 1.106 1.966 2.933

2 0.057 0.110 0.227 0.416 1.003 2.030 2.987

3 0.057 0.105 0.221 0.454 1.036 2.057 2.922

Mean 0.057 0.110 0.225 0.437 1.048 2.018 2.947

STDV 0.002 0.0043 0.003 0.018 0.052 0.047 0.035

CV% 3.61 3.95 1.45 4.31 5.05 2.34 1.19

Min 0.056 0.105 0.221 0.416 1.003 1.966 2.922

Max 0.057 0.114 0.227 0.454 1.106 2.057 2.987

Table 14: Data of three standard curves with regards to correlation, slope, R², and

intercept for Clarithromycin.


0.9993 0.0511 0.9986 + 0.0000234

53

Figure 6: Plot of linearity of calibration curve levels for Clarithromycin

quantification against their analytical response and regression linear equation.

(Table 15) represents intra-day precision and accuracy data for QC low samples based on

the standard calibration curve of the first day of validation. Accuracy range and precision

(CV %) for the six replicates of QC low samples was (93.3-112.6%) and (6.96%),

respectively. Six replicates QC mid samples of the first day of validation with accuracy

range and precision (97.5-108.3%) and (3.99%), respectively, are represented in (Table

16), while six replicates QC high samples of the same day with accuracy range and

precision (100.7-111.8%) and (4.31%), respectively, are represented in (Table 17). (Table

18) represents intra-day precision and accuracy data for LLOQ samples based on the

standard calibration curve of the first day of validation which shows accuracy range and

precision of (92.0-112.0%) and (7.23%), respectively.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 0.5 1 1.5 2 2.5 3 3.5

AU

C m

ean

rati

o

Measured mean conc. µg/ml

Y= 0.0511X + 0.0000234

R² = 0.9986

54

Table 15: Intra-day precision and accuracy data for QC low samples of

Clarithromycin based on the standard calibration curve of the first

day of validation.

QC Low

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.150

51764 6220184 0.008322 0.161 107.3

53783 6340189 0.008483 0.164 109.3

46329 6401632 0.007237 0.140 93.3

50328 6534218 0.007702 0.149 99.3

56382 6455893 0.008733 0.169 112.6

47915 6137849 0.007806 0.151 100.6

Mean 51083.5 6348328 0.008047 0.156 103.7

STDV 3715.90 148159 0.00056 0.0108 7.22

CV% 7.27 2.33 6.96 6.96 6.96



Table 16: Intra-day precision and accuracy data for QC mid samples of


day of validation.

QC Mid

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

1.500

476454 5824335 0.0818 1.593 106.2

485998 5830321 0.0834 1.624 108.3

482907 6278512 0.0769 1.498 99.9

381437 5081599 0.0751 1.462 97.5

428523 5483770 0.0781 1.521 101.4

457033 5888404 0.0776 1.511 100.7

Mean 452058 5731157 0.0788 1.535 102.3

STDV 40656 406440 0.0031 0.0612 4.08

CV% 8.99 7.09 3.98 3.99 3.99



55

Table 17: Intra-day precision and accuracy data for QC high samples of

Clarithromycin based on the standard calibration curve of the first day

of validation.

QC High

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

2.400

758735 5750984 0.13193 2.570 107.1

855695 6216832 0.13764 2.682 111.8

874297 6415503 0.13628 2.656 110.6

735505 5929764 0.12404 2.416 100.7

743441 5772968 0.12878 2.509 104.5

772850 6166853 0.12532 2.441 101.7

Mean 790087 6042151 0.1307 2.546 106.1

STDV 54514 266580 0.0081 0.1098 4.58

CV% 6.90 4.41 6.20 4.31 4.32



Table 18: Intra-day precision and accuracy data for LLOQ samples of


day of validation.

LLOQ

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.050

17215 5897684 0.0029 0.056 112.0

18867 6684532 0.0028 0.054 108.0

16668 6998547 0.0024 0.046 92.0

19885 6794469 0.0029 0.056 112.0

20331 6898665 0.0029 0.056 112.0

17955 6442379 0.0028 0.054 108.0

Mean 18932 6765522 0.0028 0.054 107.3

STDV 1404.3 191795.6 0.0002 0.0039 7.76

CV% 7.42 2.83 7.69 7.23 7.23



56

Intra-day precision and accuracy data for QC low samples based on the standard

calibration curve of the second day of validation are represented in (Table 19). Accuracy

range and precision (CV %) for the six replicates of QC low samples was (94.7-106.7%)

and (4.54%), respectively. Six replicates QC mid samples of the second day of validation

with accuracy range and precision (92.0-111.3%) and (7.56%), respectively, are

represented in (Table 20), while six replicates QC high samples of the same day with

accuracy range and precision (100.5-108.8%) and (2.84%), respectively, are represented

in (Table 21). (Table 22) shows intra-day precision and accuracy data for LLOQ samples

based on the standard calibration curve of the second day of validation which shows

accuracy range and precision of (86.0-114.0%) and (12.24%), respectively.


Clarithromycin based on the standard calibration curve of the second

day of validation.

QC Low

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.150

53287 6577321 0.00810 0.160 106.7

52246 6578894 0.00794 0.157 104.7

50955 6643784 0.00767 0.151 100.7

52214 6996458 0.00746 0.147 98.0

50334 6988646 0.00720 0.142 94.7

51134 6445994 0.00793 0.157 104.7

Mean 51695 6705183 0.00772 0.152 101.6

STDV 1079.08 231706 0.000340 0.0069 4.62

CV% 2.09 3.46 4.40 4.54 4.55



57



day of validation.

QC Mid

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

1.500

486322 5965362 0.08152 1.627 108.5

452371 6364186 0.07108 1.415 94.3

399786 5283746 0.07566 1.500 100.0

432873 5477542 0.07903 1.567 104.5

389659 5598234 0.06960 1.380 92.0

457985 5443276 0.08414 1.669 111.3

Mean 436499 5688724 0.07684 1.526 101.8

STDV 36744.7 402446.4 0.00578 0.1154 7.72

CV% 8.42 7.07 7.52 7.56 7.59





day of validation.

QC High

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

2.400

835469 6387239 0.1308 2.594 108.1

834592 6488693 0.1286 2.550 106.3

789215 5994768 0.1317 2.612 108.8

823954 6772398 0.1217 2.413 100.5

788239 6233975 0.1264 2.507 104.5

774853 5993475 0.1293 2.564 106.8

Mean 807720 6311758 0.1281 2.54 105.8

STDV 26675 302334 0.0036 0.0721 3.01

CV% 3.30 4.79 2.83 2.84 2.84



58



day of validation.

LLOQ

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.050

15966 5503867 0.0029 0.057 114.0

17885 8005683 0.00223 0.044 88.0

16657 6774352 0.00246 0.048 96.0

19976 7055211 0.00283 0.055 110.0

17334 7556894 0.00229 0.045 90.0

17722 7999542 0.00222 0.043 86.0

Mean 18242 7398212 0.00248 0.049 97.3

STDV 1372.2 533507 0.00029 0.0060 11.91

CV% 7.52 7.21 11.68 12.24 12.24




the standard calibration curve of the third day of validation. Accuracy range and precision

for the six replicates of QC low samples was (95.3-110.7%) and (5.72%), respectively.

(Table 24) shows six replicates QC mid samples of the third day of validation with

accuracy range and precision (91.7-111.9%) and (7.55%), respectively, while six

replicates QC high samples of the same day with accuracy range and precision (96.5-

107.6%) and (4.12%), respectively showed in (Table 25). (Table 26) represents intra-day

precision and accuracy data for LLOQ samples based on the standard calibration curve of

the third day of validation which shows accuracy range and precision of (89.3-112.82%)

and (8.75%), respectively.

59


Clarithromycin based on the standard calibration curve of the third day of

validation.

QC Low

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.150

56437 6557349 0.0086 0.166 110.7

54332 6653412 0.0082 0.157 104.7

51124 6778431 0.0075 0.145 96.7

50441 6788423 0.0074 0.143 95.3

51784 6577433 0.0079 0.151 100.7

50889 6645986 0.0077 0.147 98.0

Mean 52501.17 6666839 0.0079 0.152 101.0

STDV 2370.53 97808.05 0.00044 0.0087 5.79

CV% 4.52 1.47 5.61 5.72 5.74




Clarithromycin based on the standard calibration curve of the third

day of validation.

QC Mid

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

1.500

486579 6439865 0.07555 1.460 97.3

496647 5779834 0.08592 1.661 110.7

482245 5553783 0.0868 1.678 111.9

459482 6457738 0.07115 1.375 91.7

473387 5985634 0.07908 1.529 101.9

497834 6125655 0.08127 1.571 104.7

Mean 482696 6057085 0.0800 1.546 103.0

STDV 14591.90 359730 0.0060 0.117 7.78

CV% 3.02 5.94 7.55 7.55 7.55



60


Clarithromycin based on the standard calibration curve of the third

day of validation.

QC High

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

2.400

865398 6478397 0.13358 2.583 107.6

794468 6164853 0.12887 2.492 103.8

803894 6048216 0.13291 2.578 107.4

759278 6338941 0.11978 2.316 96.5

783291 6049352 0.12948 2.503 104.3

769935 6166853 0.12485 2.414 100.6

Mean 796044 6207769 0.1282 2.50 103.4

STDV 37604 170009 0.0052 0.100 4.24

CV% 4.72 2.74 4.06 4.12 4.11




Clarithromycin based on the standard calibration curve of the third day of

validation.

LLOQ

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.050

16791 5661449 0.003 0.056 112.0

20563 6974459 0.0029 0.056 112.0

18995 7056942 0.0027 0.051 102.0

16943 6743285 0.0025 0.048 96.0

17056 6630893 0.0026 0.049 98.0

16799 7122894 0.0024 0.045 90.0

Mean 18377 6862394 0.0027 0.051 101.7

STDV 1660 215833 0.0003 0.0044 8.89

CV% 9.04 3.15 9.36 8.75 8.75



61

Comparing with the accepted criteria for QC levels which is 85.0-115% and for LLOQ

range which should be 80-120%, the accuracy and LLOQ range data obtained from the

first, second, and third day of validation for quantification of Clarithromycin are within

the required range. In addition, precision (CV%) is not exceed 20% for LLOQ, and 15%

for the other concentrations which prove the closeness of the measurements when

repeatedly applied the method of analysis to multiple aliquots of a single homogenous

volume of the serum.

(Table 27) represents Inter-day accuracy and precision for the quality control samples of

CAM in the three days of validation. All of the obtained accuracy and precision data are

within the required range.

62

2.4

00 µ

g/m

l Q

C h

igh

Day t

hre

e

2.5

83

2.4

92

2.5

78

2.3

16

2.5

03

2.4

14

2.5

22

0.0

944

3.7

4

105.1

Day t

wo

2.5

94

2.5

50

2.6

12

2.4

13

2.5

07

2.5

64

Day o

ne

2.5

70

2.6

82

2.6

55

2.4

16

2.5

09

2.4

41

1.5

00 µ

g/m

l Q

C m

id

Day t

hre

e

1.4

60

1.6

61

1.6

78

1.3

75

1.5

29

1.5

71

1.5

40

0.0

951

6.2

0

102.7

Day t

wo

1.6

27

1.4

15

1.5

00

1.5

67

1.3

80

1.6

69

Day o

ne

1.5

93

1.6

24

1.4

98

1.4

62

1.5

21

1.5

11

0.1

50 µ

g/m

l Q

C l

ow

Day t

hre

e

0.1

66

0.1

57

0.1

45

0.1

43

0.1

51

0.1

47

0.1

53

0.0

086

5.6

2

102.0

Day t

wo

0.1

6

0.1

57

0.1

51

0.1

47

0.1

42

0.1

57

Day o

ne

0.1

61

0.1

64

0.1

4

0.1

49

0.1

69

0.1

51

Mea

sure

d

con

c.

Mea

n

ST

DV

CV

%

Acc

ura

cy

%

Tab

le 2

7:

Inte

r-d

ay a

ccu

racy

an

d p

reci

sion

for

the

qu

ali

ty c

on

trol

sam

ple

s of

Cla

rith

rom

yci

n i

n t

he

thre

e d

ays

of

vali

dati

on

63

3.2.2 Recovery data for Clarithromycin quantification

The recovery of CAM from its biological matrix in this analytical method showed a high

value and good result.

(Table 28) shows data of triplicate quality control samples of CAM in the mobile phase

while (Table 29) shows data of triplicate quality control samples of CAM in the serum.

Absolute recoveries for CAM and IS were calculated by dividing average peak area of

triplicate from each QC level of serum samples (Table 29) over the same set of QC

samples that were prepared in mobile phase (Table 28) multiplied by 100%.

(Table 30) shows recovery % of CAM and (Table 31) shows recovery % of IS which

shows a high recovery % and acceptable at the studied concentration.

Table 28: Data of Clarithromycin and IS in the mobile phase for the quality

control samples.

concentration

µg/ml

AUC

CAM AUC IS

Mean

CAM

CAM

C.V.% Mean IS

IS

C.V.%

0.150

QC low

51784 6577433

51491

0.84

6587065

0.17

51693 6598835

50997 6584926

1.500

QC mid

398239 5182495

388828

2.37

5171893

1.31

379854 5099386

388392 5233798

2.400

QC high

833528 6966834

839876

0.78

6929894

1.01

846623 6849264

839476 6973584

64

Table 29: Data of Clarithromycin and IS in serum for the quality control

samples.

concentration

µg/ml

AUC

CAM AUC IS

Mean

CAM

CAM

CV% Mean IS

IS

CV%

0.150

QC low

50945 6498694

52563

2.82

6607380

1.80

52889 6589452

53856 6733994

1.500

QC mid

379436 5094758

392445

2.98

5533726

12.23

402116 5193485

395783 6312935

2.400

QC mid

819574 6719845

820975

1.50

6782286

2.00

833964 6692378

809387 6934635

Table 30: Recovery % for Clarithromycin.

concentration

µg/ml Mean serum

Mean mobile

phase

Recovery

%

0.150 QC low 52563 51491 102.1

1.500 QC mid 392445 388828 100.9

2.400 QC high 820975 839876 97.8

Table 31: Recovery % for Clindamycin (IS).

concentration

µg/ml Mean serum

Mean mobile

phase

Recovery

%

0.150 QC low 6607380 6587065 100.3

1.500 QC mid 5533726 5171893 107.0

2.400 QC high 6782286 6929894 97.9

65

3.2.3 Validation of day one, two, and three on linearity, accuracy, and precision data

for Metronidazole quantification

Inter and intraday accuracy, precision and linear response for standard calibration curve

and QC samples of the three days validation are explained in the following tables and

figures:

The first day of validation: (Table 32), which represents the standard calibration curve

and intra-day accuracy data, shows an accuracy range of 91.4% - 113.2%.

As shown in (Figure 7), R² is 0.998 which represents the strength of the correlation;



correlation, slope, R², and intercept for day one are showed in (Table 33).

Therefore, first day of validation results passed the required criteria in terms of linearity

and accuracy.

Table 32: Standard calibration curve of the first day of validation, intraday

accuracy data for Metronidazole.

Theoretical

Concentration(µg/ml)

AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.300 10078 6734583 0.0015 0.327 109.0

0.600 19655 6409582 0.0031 0.679 113.2

1.200 31563 6255687 0.0050 1.097 91.4

2.400 75348 6537849 0.0115 2.525 105.2

6.000 185674 6249211 0.0297 6.525 108.8

12.000 361388 6317961 0.0572 12.569 104.7

18.000 534114 6400159 0.0835 18.349 101.9


**Measured concentration= (AUC Ratio/0.00455)-(+ 0.00223).

66


intercept on the first day for Metronidazole.


0.9997 0.00455 0.9994 + 0.00223


regression linear equation on the first day of validation for Metronidazole.

Second day of validation: (Table 34), which represents the standard calibration curve

and intra-day accuracy data, shows an accuracy range of 95.3% - 111.8%.




correlation, slope, R², and intercept for day two are showed in (Table 35).

Therefore, second day of validation results passed the required criteria in terms of

linearity and accuracy.

Metro.rdb (Metronidazole): "Linear" Regression ("1 / x" weighting): y = 0.00455 x + 0.00223 (r = 0.9997)

1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0Analyte Conc. / IS Conc.

0.000

5.000e-3

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

0.070

0.075

0.080

0.085

An

aly

te

A

re

a / IS

A

re

a

Y= 0.00455X + 0.00223

R² = 0.9994

67

Table 34: Standard calibration curve of the second day of validation, intraday


Theoretical


AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.300 7994 6165389 0.0013 0.286 95.3

0.600 16593 6001875 0.0028 0.616 102.7

1.200 36784 6073088 0.0061 1.341 111.8

2.400 64678 5902473 0.0110 2.418 100.8

6.000 199657 6886542 0.0290 6.374 106.2

12.000 344482 6086392 0.0566 12.440 103.7

18.000 516278 6123078 0.0843 18.528 102.9


**Measured concentration= (AUC Ratio/0.00455)-(-0.000722).


intercept on the second day for Metronidazole.


0.9997 0.00479 0.9994 -0.000722

68


regression linear equation on the second day of validation for Metronidazole.

Third day of validation: (Table 36) represents the standard calibration curve and intra-

day accuracy data with accuracy range of 82.0% - 106.0%.




correlation, slope, R², and intercept for the third day are showed in (Table 37).

Therefore, third day of validation results passed the required criteria in terms of linearity

and accuracy.

Metro.rdb (Metronidazole): "Linear" Regression ("1 / x" weighting): y = 0.00479 x + -0.000722 (r = 0.9997)


0.000

5.000e-3

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

0.070

0.075

0.080

0.085

An

aly

te

A

re

a / IS

A

re

a

Y= 0.00479X -0.000722

R² = 0.9994

69

Table 36: Standard calibration curve of the third day of validation, intraday


Theoretical


AUC

Drug AUC IS

AUC

Ratio*

Measured

Conc.** Accuracy%

0.300 8657 5443797 0.0016 0.318 106.0

0.600 16578 5673489 0.0029 0.576 96.0

1.200 29975 5376784 0.0056 1.112 92.7

2.400 63831 5512811 0.0116 2.302 95.9

6.000 161734 5686025 0.0284 4.921 82.0

12.000 351187 5802255 0.0605 12.004 100.0

18.000 520368 5794392 0.0898 17.818 99.0




intercept on the third day for Metronidazole.


0.9998 0.00504 0.9996 -0.000761

70


regression linear equation on the third day of validation for Metronidazole.

The linearity and linear working range of three standard curves of MTZ data based on the

calculated mean area ratio are showed in (Table 38).

The linearity and linear working range of three standard curves of MTZ data based on the

measured mean concentrations are showed in (Table 39).

Data of three standard curves with regards to correlation, slope, R², and intercept are

showed in (Table 40).

The plot of linearity of calibration curve levels for MTZ quantification against their

analytical response and regression linear equation that represents the all three days of

validation was done by plotting the calculated mean of the measured concentrations

versus the calculated mean of the AUC ratio for each standard point showed in (Figure

10).

Metro.rdb (Metronidazole): "Linear" Regression ("1 / x" weighting): y = 0.00504 x + -0.000761 (r = 0.9998)


0.000

5.000e-3

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

0.070

0.075

0.080

0.085

0.090

An

aly

te

A

re

a / IS

A

re

a

Y= 0.00504 X -0.000761

R² = 0.9996

71


Metronidazole data based on the calculated area ratio.

Calibration

curve

AUC Ratio for each Standard Point

0.300 0.600 1.200 2.400 6.000 12.000 18.000

1 0.0015 0.0031 0.005 0.0115 0.0297 0.0572 0.0835

2 0.0013 0.0028 0.0061 0.011 0.029 0.0566 0.0843

3 0.0016 0.0029 0.0056 0.0116 0.0284 0.0605 0.0898

Mean 0.00147 0.00293 0.00557 0.0113 0.02903 0.05810 0.08587

STDV 0.000153 0.000153 0.000551 0.0003 0.000651 0.0021 0.00343

CV% 10.41 5.21 9.89 2.83 2.24 3.61 3.99

Min 0.0013 0.0028 0.005 0.011 0.0284 0.0566 0.0835

Max 0.0016 0.0031 0.0061 0.0116 0.0297 0.0605 0.0898


Metronidazole data based on the measured concentrations.

Calibration

curve Measured Concentrations for each Standard Point (µg/ml)

0.300 0.600 1.200 2.400 6.000 12.000 18.000

1 0.327 0.679 1.097 2.525 6.525 12.569 18.349

2 0.286 0.616 1.341 2.418 6.374 12.440 18.528

3 0.318 0.576 1.112 2.302 4.921 12.004 17.818

Mean 0.310 0.624 1.183 2.415 5.940 12.338 18.232

STDV 0.0215 0.0519 0.1367 0.1115 0.8857 0.2961 0.3693

CV% 6.94 8.33 11.56 4.62 14.91 2.40 2.03

Min 0.286 0.576 1.097 2.302 4.921 12.004 17.818

Max 0.327 0.679 1.341 2.525 6.525 12.569 18.528

Table 40: Data of three standard curves with regards to correlation, slope, R², and

intercept for Metronidazole.


0.9999 0.00479 0.9998 -0.0000262

72

Figure 10: Plot of linearity of calibration curve levels for Metronidazole

quantification against their analytical response and regression linear equation.


the standard calibration curve of the first day of validation. Accuracy range and precision


Six replicates QC mid samples of the first day of validation with accuracy range and

precision (100.6-113.3%) and (4.71%), respectively, are represented in (Table 42), while

six replicates QC high samples of the same day with accuracy range and precision

(101.0-113.7%) and (4.96%), respectively, are showed in (Table 43). (Table 44)

represents intra-day precision and accuracy data for LLOQ samples based on the standard

calibration curve of the first day of validation which shows accuracy range and precision

of (94.3-116.3%) and (8.33%), respectively.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

0 2 4 6 8 10 12 14 16 18 20

AU

C m

ean

rati

o

Measured mean conc. µg/ml

Y= 0.00479X - 0.0000262

R² = 0.9998

73


Metronidazole based on the standard calibration curve of the first day

of validation.

QC Low

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

0.900

28942 6220408 0.0047 1.030 114.4

26841 6340504 0.0042 0.920 102.2

23951 6396856 0.0037 0.811 90.1

21779 6008885 0.0036 0.789 87.7

22795 6115044 0.0037 0.811 90.1

23889 6148965 0.0039 0.855 95.0

Mean 24700 6205110 0.0040 0.872 96.6

STDV 2682 144983 0.0004 0.0863 10.1413

CV% 10.86 2.34 9.88 9.99 10.50





of validation.

QC Mid

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

9.000

279052 6112169 0.0457 10.041 111.6

256425 6231150 0.0412 9.053 100.6

273837 6448959 0.0425 9.338 103.8

289898 6245967 0.0464 10.196 113.3

268894 6077803 0.0442 9.712 107.9

265766 6289319 0.0423 9.294 103.2

Mean 272312 6234228 0.0437 9.600 106.7

STDV 11523 133161 0.00208 0.4500 5.0442

CV% 4.23 2.14 4.76 4.71 4.72



74



of validation.

QC High

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

14.400

449307 6266837 0.0717 15.756 109.4

459834 6253008 0.0735 16.152 112.2

483341 6486358 0.0745 16.371 113.7

430349 6471578 0.0665 14.613 101.5

430080 6491858 0.0662 14.547 101.0

466339 6652938 0.0701 15.404 107.0

Mean 453208 6437096 0.0704 15.474 107.5

STDV 20962 152367 0.0035 0.768 5.3321

CV% 4.63 2.37 4.96 4.96 4.96





of validation.

LLOQ

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

0.300

8657 5443797 0.0016 0.349 116.3

9077 6285827 0.0014 0.305 101.7

9174 6422908 0.0014 0.305 101.7

7893 5929929 0.0013 0.283 94.3

8435 6401245 0.0013 0.283 94.3

9163 6219142 0.0015 0.327 109.0

Mean 8866 6239309 0.0014 0.309 102.9

STDV 584 180069 0.0001 0.0257 8.5740

CV% 6.59 2.89 5.82 8.33 8.33



75

Intra-day precision and accuracy data for QC low samples based on the standard

calibration curve of the second day of validation are showed in (Table 45). Accuracy

range and precision for the six replicates of QC low samples was (92.8-117.2%) and

(8.25%), respectively. Six replicates QC mid samples of the second day of validation

with accuracy range and precision (95.0-106.5%) and (4.64%), respectively, are

represented in (Table 46), while six replicates QC high samples of the same day with

accuracy range and precision (99.7-111.0%) and (3.40%), respectively, are represented in

(Table 47). (Table 48) represents intra-day precision and accuracy data for LLOQ

samples based on the standard calibration curve of the second day of validation which

shows accuracy range and precision of (95.3-111.0%) and (6.39%), respectively.


Metronidazole based on the standard calibration curve of the second

day of validation.

QC Low

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

0.900

29657 6139753 0.0048 1.055 117.2

26841 6089436 0.0044 0.968 107.5

25883 6388451 0.0041 0.902 100.2

25986 6264377 0.0041 0.902 100.2

24794 6233976 0.0040 0.888 98.7

23446 6116395 0.0038 0.836 92.8

Mean 26101 6205398 0.00421 0.925 102.8

STDV 2098.13 112678 0.0004 0.0763 8.4826

CV% 8.04 1.82 8.56 8.25 8.25



76



day of validation.

QC Mid

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

9.000

265794 6229648 0.0427 9.385 104.2

249854 6329874 0.0395 8.682 96.5

269843 6934754 0.0389 8.550 95.0

273496 6269342 0.0436 9.583 106.5

259356 6196389 0.0419 9.209 102.3

255298 6399573 0.0399 8.779 97.5

Mean 262274 6393263 0.0411 9.031 100.3

STDV 9023 275011 0.00191 0.4191 4.6479

CV% 3.44 4.30 4.66 4.64 4.63





day of validation.

QC High

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

14.400

439758 6332894 0.0694 15.253 105.9

449846 6527491 0.0689 15.144 105.2

488945 6689462 0.0731 15.260 106.0

417889 6398835 0.0653 14.352 99.7

459899 6328997 0.0727 15.979 111.0

473995 6485593 0.0731 15.260 106.0

Mean 455055 6460545 0.0704 15.208 105.6

STDV 25192 137782 0.0031 0.5174 4.5926

CV% 5.54 2.13 4.43 3.40 3.40



77



day of validation.

LLOQ

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

0.300

7994 6165389 0.0013 0.286 95.3

9335 6678943 0.0014 0.308 102.7

9276 6331289 0.0015 0.330 110.0

8903 6756643 0.0013 0.286 95.3

8856 6448957 0.0014 0.308 102.7

9211 6343559 0.0015 0.330 110.0

Mean 9135 6439541 0.0014 0.308 102.7

STDV 203 248879 0.0001 0.0197 6.5741

CV% 2.22 3.86 5.06 6.39 6.40




the standard calibration curve of the third day of validation. Accuracy range and precision


Six replicates QC mid samples of the third day of validation with accuracy range and

precision (91.1-97.4%) and (2.84%), respectively, are represented in (Table 50), while six

replicates QC high samples of the same day with accuracy range and precision (96.9-

107.3%) and (4.09%), respectively, are represented in (Table 51). (Table 52) shows the

intra-day precision and accuracy data for LLOQ samples based on the standard

calibration curve of the third day of validation which shows accuracy range and precision

of (86.3-106.0%) and (8.13%), respectively.

78


Metronidazole based on the standard calibration curve of the third day

of validation.

QC Low

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

0.900

27954 6155874 0.0045 0.893 99.2

28342 6334875 0.0045 0.893 99.2

25934 6118942 0.0042 0.834 92.7

24477 6138749 0.0040 0.794 88.2

30215 6288469 0.0048 0.953 105.8

25279 6089462 0.0042 0.834 92.7

Mean 27033.50 6187729 0.0044 0.867 96.34

STDV 2168.15 99602 0.0003 0.0570 6.3024

CV% 8.02 1.61 6.80 6.58 6.54





of validation.

QC Mid

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

9.000

269834 6103296 0.0442 8.770 97.4

268349 6132784 0.0438 8.691 96.6

266398 6394412 0.0417 8.274 91.9

280673 6398416 0.0439 8.711 96.8

259782 6283395 0.0413 8.195 91.1

279022 6481936 0.0430 8.533 94.8

Mean 270676 6299040 0.0430 8.529 94.8

STDV 7908 154028 0.00121 0.2425 2.6868

CV% 2.92 2.45 2.82 2.84 2.84



79



of validation.

QC High

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

14.400

439351 6152879 0.0714 14.167 98.4

448926 6386934 0.0703 13.949 96.9

490558 6298498 0.0779 15.457 107.3

470378 6339817 0.0742 14.723 102.2

463396 6487936 0.0714 14.167 98.4

480327 6833951 0.0703 13.949 96.9

Mean 465489 6416669 0.0726 14.40 100.0

STDV 19154 232182 0.0030 0.5894 4.0612

CV% 4.11 3.62 4.09 4.09 4.06





of validation.

LLOQ

Concentration

(µg/ml)

AUC

Drug AUC IS

AUC

Ratio

Measured

Conc. Accuracy%

0.300

8657 5443797 0.0016 0.318 106.0

9218 6583392 0.0014 0.279 93.0

9137 6299686 0.0015 0.298 99.3

8859 6733962 0.0013 0.259 86.3

9098 6488931 0.0014 0.279 93.0

8955 6663827 0.0013 0.259 86.3

Mean 9043 6549962 0.0014 0.282 94.0

STDV 132 151460 0.0000 0.0229 7.6507

CV% 1.46 2.31 3.44 8.13 8.14



80

Comparing with the accepted criteria which is for QC levels 85.0-115% and for LLOQ

range which should be 80-120%, the accuracy and LLOQ range data obtained from the

first, second, and third day of validation are within the required range. In addition,

precision (CV%) is not exceed 20% for LLOQ, and 15% for the other concentrations

which prove the closeness of the measurements when repeatedly applied the method of

analysis to multiple aliquots of a single homogenous volume of the serum.

(Table 53) represents Inter-day accuracy and precision for the quality control samples of

MTZ in the three days of validation. All of the obtained accuracy and precision data are

within the required range.

81

14.4

00 µ

g/m

l Q

C h

igh

Day t

hre

e

14.1

67

13.9

49

15.4

57

14.7

23

14.1

67

13.9

49

15.0

28

0.7

578

5.0

4

104.4

Day t

wo

15.2

53

15.1

44

15.2

60

14.3

52

15.9

79

15.2

60

Day o

ne

15.7

56

16.1

52

16.3

71

14.6

13

14.5

47

15.4

04

9.0

00 µ

g/m

l Q

C m

id

Day t

hre

e

8.7

70

8.6

91

8.2

74

8.7

11

8.1

95

8.5

33

9.0

55

0.5

780

6.3

8

100.6

Day t

wo

9.3

85

8.6

82

8.5

50

9.5

83

9.2

09

8.7

79

Day o

ne

10.0

41

9.0

53

9.3

38

10.1

96

9.7

12

9.2

94

0.9

00 µ

g/m

l Q

C l

ow

Day t

hre

e

0.8

93

0.8

93

0.8

34

0.7

94

0.9

53

0.8

34

0.8

87

0.0

768

8.6

6

98.6

Day t

wo

1.0

55

0.9

68

0.9

02

0.9

02

0.8

88

0.8

36

Day o

ne

1.0

30

0.9

20

0.8

11

0.7

89

0.8

11

0.8

55

Mea

sure

d

Con

c.

Mea

n

ST

DV

CV

%

Acc

ura

cy

%

Tab

le 5

3:

Inte

r-d

ay a

ccu

racy

an

d p

reci

sion

for

the

qu

ali

ty c

on

trol

sam

ple

s of

Met

ron

idazo

le i

n t

he

thre

e d

ays

of

vali

dati

on

82

3.2.4 Recovery data for Metronidazole quantification

The recovery of MTZ from its biological matrix in this bioanalytical method showed a

high value and good result.

(Table 54) shows data of triplicate quality control samples of MTZ in the mobile phase

while (Table 55) shows data of triplicate quality control samples of MTZ in the serum.

Absolute recoveries for MTZ and IS were calculated by dividing average peak area of

triplicate from each QC level of serum samples (Table 55) over the same set of QC

samples that were prepared in mobile phase (Table 54) multiplied by 100%.

(Table 56) shows recovery % of MTZ and (Table 57) shows recovery % of IS which

shows a high recovery % and acceptable at the studied concentration.

Table 54: Data of Metronidazole in the mobile phase for the quality control

samples.

concentration

µg/ml

AUC

CAM AUC IS

Mean

CAM

CAM

CV%

Mean

IS

IS

CV%

0.900 26945 6485526

QC low 25973 6599327 25660 5.71 6618102 2.16

24063 6769452

9.000 268396 6396732

QC mid 272264 6489537 273374.3 2.05 6445075 0.72

279463 6448956

14.400 452856 6733985

QC high 463953 6634957 453251.6 2.32 6656193 1.05

442946 6599637

83

Table 55: Data of Metronidazole in the serum for the quality control samples.

concentration

µg/ml

AUC

CAM AUC IS

Mean

CAM

CAM

CV%

Mean

IS

IS

CV%

0.900 26317 6598347

QC low 23951 6639785 25369 4.93 6592400 0.77

25838 6539068

9.000 266945 6439784

QC mid 259745 6501329 262696 1.44 6526986 1.57

261398 6639846

14.400 459355 6598348

QC mid 463995 6549886 462249 0.55 6549366 0.75

463396 6499865

Table 56: Recovery % for Metronidazole.

concentration

µg/ml

Mean

serum

Mean mobile

phase

Recovery

%

0.150 QC low 25369 25660 98.87

1.500 QC mid 262696 273374.3 96.09

2.400 QC high 462249 453251.7 101.99

Table 57: Recovery % for Clindamycin (IS).

concentration

µg/ml

Mean

serum

Mean mobile

phase

Recovery

%

0.150 QC low 6592400 6618102 99.61

1.500 QC mid 6526986 6445075 101.27

2.400 QC high 6549366 6656193 98.40

84

3.3 The modifying effect of pomegranate fresh juice on Clarithromycin and

Metronidazole pharmacokinetic profiles

Food-drug interaction is an important field in the pharmaceutical research. Such

an interaction may affect health status due to altered PK and/or PD of the drug or dietary

substance. A dietary substance can increase the AUC of the drug increasing the risk of

adverse events and toxicity, or decrease its AUC, leading to therapeutic failure (Santos

C.A. and Boullata J.I., 2005).

Foods consumed as beverages give an explanation for a very high proportion of

dietary antioxidant intake (Pulido R. et al., 2003). Increasing facts supporting

cardioprotective benefits give a promotion for moderate beverages consumption as part

of a healthy lifestyle (Kaplan N.M. and Palmer B.F., 2000; Guilford J.M and Pezzuto

J.M., 2011). Several studies have explained the effect of wine, beer, tea, fruit juices, and

their specific constituents on CYP activity in vitro, but still clinical studies are limited.

These beverages have become highly recommended and over-the-counter supplements

for prevention and treatment of common diseases. Some ingredients especially in fruit

juices have been shown to inhibit intestinal metabolism and active efflux/uptake

processes in vitro and in vivo. Inhibition of metabolism and active efflux probably

increase, whereas inhibition of active uptake may be decrease, systemic drug exposure.

Many studies established that cytachrome P450 (CYP450) isoenzymes are

involved and play an important role in food-drug interactions (Rabia B. et al., 2007).

CYP3A4 which is the most considerable CYP450 isoenzymes, in particular, is found at

quite high concentrations in the mucosa of the small intestine with broad substrate

specificity which means that drug substrates for this enzyme are subject to metabolism

during absorption, this explain why it is responsible for about 30-40% of drugs

metabolism (Scott J.G. and Wen Z., 2001; Badyal D.K. and Dadhich A.P., 2001).

Pomegranate fruit extract is a rich source of polyphenols which are flavoring,

coloring, and also has antioxidant effect that they can help protect cells from damage and

may help to lower inflammation. Also pomegranate can provides about 40% of the daily

requirement of vitamin C. Pomegranate is a rich source of crude fibers, pectin, sugars,

85

and several tannins (Gil M.I. et al., 2000). In addition, pomegranate seed oil and juice

contains certain species of lavonoids and anthocyanins.

Recently, pomegranate has been widely consumed around the world especially in

the Middle Eastern countries, Pomegranate juice, according to legend has been used as a

medicine for thousands of years (Langley P., 2000). In laboratory tests, pomegranate

shows antiviral, antibacterial, and antioxidant properties. Some reports talked about a

decreasing effect of pomegranate in cardiovascular diseases by inhibition of low-density

lipoprotein oxidation (Gil M.I. et al., 2000; Aviram M. et al., 2002, 2004; Noda Y. et al.,

2002). Furthermore, therapeutic properties of the fruit have been suggested for use in

cases of breast cancer (Kim N.D. et al., 2002). Based on these findings, pomegranate has

been increasingly consumed. Higher pomegranate consumption allows for an increased

possibility of pomegranate-drug interaction. Therefore, it is important to evaluate the

interaction between pomegranate and medications. In addition, there is some expectation

that pomegranate juice may interact with medications (much like grapefruit juice does).

The effect of pomegranate juice on carbamazepine metabolism was studied in

human’s liver (in vitro); in results, pomegranate juice inhibited the human CYP3A-

mediated metabolism of carbamazepine. On the other hand, short pre-treatment

pomegranate juice inhibited intestinal, but not hepatic, CYP3A4 activity (in vivo) (Hidaka

M. et al., 2005). Another study showed that pre-treatment of rats with pomegranate juice

for longer period (i.e., 7 days) decreased intestinal permeation of carbamazepine which is

supposed to be due to induction of CYP3A4 enzyme (Adukondalu D. et al., 2010).

Further studies are needed to prove their effects in human beings or animals.

Another clinical study suggested lack of clinical significance of the effect of

pomegranate juice when it is given with a single oral dose of midazolam (Farkas D. et al.,

2007).

The ability of pomegranate juice to inhibit the activity of human CYP2C9 was

investigated using human liver microsomes. Pomegranate juice was shown to be a potent

inhibitor of human CYP2C9. The addition of pomegranate juice resulted in almost

complete inhibition of human CYP2C9 activity. In addition, they investigated the effect

of pomegranate juice on the pharmacokinetics of tolbutamide (substrate for CYP2C9) in

86

rats. The results showed that the area under the concentration-time curve was

approximately 1.2-fold greater when pomegranate juice was injected before oral

administration of the tolbutamide. The elimination half-life of tolbutamide was not

altered by pomegranate juice administration. These findings suggest pomegranate juice

ingestion inhibits the intestinal metabolism of tolbutamide without inhibiting the hepatic

metabolism in rats (Nagata M. et al., 2007).

A more recent study evaluated the effect of repeated commercially available

pomegranate juice consumption on the CYP3A-mediated metabolism of midazolam

(Misaka S. et al., 2011). Pomegranate juice did not significantly alter midazolam PK.

Repeated consumption of pomegranate juice may not cause a clinically relevant

interaction with midazolam.

Generally, studies which have been done for the effect of pomegranate juice on

the drugs pharmacokinetic or its enteric CYP3A inhibition potential are still few or

premature. There is no study done for the effect of Pomegranate on CAM or

Metronidazole pharmacokinetics. However, the effect of grapefruit juice on the CAM

pharmacokinetic profile was studied. According to this study, freshly squeezed white

grapefruit delayed the Tmax of both CAM and 14-OH-C by one hour. This finding

interpreted as presence of a competition for intestinal CYP3A4 and/or absorptive sites

(Cheng K.L. et al., 1998).

CAM is widely used with other medications as a triple therapy (e.g. with proton

pump inhibitors and Metronidazole) for the treatment of Helicobacter pylori (H.pylori)

which is one of the main causes of peptic ulcer diseases (PUD). Any significant changes

in the plasma concentration or the pharmacokinetic profile of CAM could lead to a

serious side effects and toxicity (in higher concentrations) or treatment failed (in lower

concentrations). Furthermore, CAM is metabolized in liver by CYP3A4 to an active

metabolite (14-hydroxyclarithromycin), so any substance that induces this enzyme

activity will increase its metabolism and enhance its toxicity. CAM is known as a potent

inhibitor of CYP3A4 (which is mainly expressed in intestine and liver) (Rodrigues A.D.,

1997), so it can affect the absorption and/or metabolism of other drugs which are

substrate for the same enzyme leading to severe drug-drug interactions.

87

According to bacteriological studies, the pharmacokinetic parameters of

antibiotics have been shown to be coordinated with their ability to eradicate bacteria; as a

result any significant changes in such parameters could affect their clinical outcome and

even could be developed to a bacterial resistance (Ball P. et al., 2002). Therefore, it is

very important to take in consideration the food-drug interactions or drug-drug

interactions of antibiotics since these interactions can affect antibiotics pharmacokinetic

parameters.

In the current study, the pharmacokinetic profile of each drug, namely CAM and

MTZ was evaluated on rats with a single dose of PJ administration on a sample size of 6

and 4, respectively, and of the same sample sizes for a multiple dose administration of PJ

comparing with a sample size of 4 administered with DW. Then the pharmacokinetic

profile of each drug was evaluated on rats alone on a sample size of 7 for CAM and 6 for

MTZ, and sample size of 5 when combined together. The range, mean, standard

deviation, standard error, Cohen’s d and paired t-test were calculated by Microsoft Excel.

Cohen’s d a standardized measure of effect size for difference between two means

(Cohen’s d = (mean1-mean2)/pooled STDV. Cohen’s d<0.3 small effect, 0.3-0.7 is

medium effect, finally, 0.8 and greater is a large effect.

3.3.1 Effect of a single and multiple dose of pomegranate juice on Clarithromycin

As shown in (Table 58) and (Figure 11), When CAM administered alone, it

reached its mean maximum plasma level (1.83µg/ml) after one hour and then gradually

declines to reach minimum plasma concentration of (0.56µg/ml) after (6 hours) from the

time of drug administration.

As shown in (Table 59) and (Figure 11) the same drug when administrated half an

hour after a single dose (5 ml /kg) of PJ administration, the mean maximum

concentration increased to reach (2.25µg/ml) but with shifted Tmax since reaching to

mean maximum level was delayed to appear after 3 hours from the point of drug

administration and it is continue to decline until reach the end of follow up period of six

hours with a very narrow gap (difference in mean plasma drug concentration) between a

drug alone and drug with PJ. which is represented by (7.14%) percent change. The

88

maximum change in the mean plasma drug concentration of CAM after giving a single

dose of PJ administration was after three hours from CAM administration which

increased by (1.30µg/ml) with a percent change of (136.84%, compared to administration

with DW. The effect of a single dose of PJ used was evaluated as a strong effect at the

three hours time interval (Cohen’s d =1.18) while it is considered as a moderate to small

effect at the other time intervals. This elevating in plasma CAM pharmacokinetic

parameters when used with a single dose of PJ comparing to singly use, however failed to

reach the level of statistical significance which may be contributed to a very small sample

size or to low dose of PJ. Furthermore, Cmax and AUC were increased by (+22.9%) and

(39.2%), respectively, with decreasing in t½ and increasing in the elimination rate

constant by (45.7) and (50.8), respectively, as explained in (Table 60).

As shown in (Table 61) and (Figure 11), CAM when administered half an hour

after a multiple dose (5ml/kg) of PJ (which administrated for two days two times daily

and one dose at the third day before experiment),the mean plasma concentration

increased to reach a maximum plasma level (1.21 µg/ml) after half an hour from drug

administration. The maximum percent change in mean plasma level of CAM was at time

intervals one hour which was obviously lower than that of drug’s level administered with

DW by (39.97%). However, it returned to increase at three hours by (22.57%). According

to Cohen’s d measurement the effect of a multiple dose of PJ was weak except at one

hour interval (Cohen’s d =1.15) which could be considered as strong lowering effect.

These changes in plasma CAM pharmacokinetic parameters when used with a multiple

dose of PJ comparing to single use, however failed to reach the level of statistical

significance which may be contributed to a very small sample size or to low dose of PJ.

Furthermore, Cmax, Tmax, and AUC were decreased by (33.9%), (50.0%), and (9.7%),

respectively while t½ was increased by (62.0%) with decreasing in the elimination rate

constant by (40.0%), as explained in (Table 62).

89

Table 58: Results of Clarithromycin with DW (n=4).

Time (hr)

Drug

assessed

CAM

+ DW

0.5

1

2

3

4

6

Mean

(µg/ml) 1.05±0.39 1.83±0.34 1.25±0.15 0.95±0.23 0.74±0.21 0.56±0.17

Range 0.19-2.05 0.86-2.31 0.79-1.44 0.52-1.56 0.36-1.32 0.23-1.04

STDV 0.77 0.67 0.31 0.46 0.41 0.34

Table 59: Results of Clarithromycin with a single dose of pomegranate juice with a

comparison to a Clarithromycin with DW administration (n=6).

Time (hr)

Drug

assessed

CAM

+

Single dose

of juice

0.5 1

2

3

4

6

Mean(µg/ml) 1.56±0.32 2.01±0.30 1.33±0.24 2.25±0.71 1.18±0.42 0.61±0.10

Range 0.67-2.94 1.09-2.72 0.67-2.03 0.59-4.5 0.52-3.2 0.25-0.92

STDV 0.78 0.73 0.60 1.75 1.02 0.23

Comparing the M.P.C with CAM + DW

Difference

between 2

means

+0.51 +0.18 +0.08 +1.30 +0.44 +0.04

Cohen’s d +0.66 +0.26 +0.18 +1.18 +0.62 +0.18

Percent

change +48.57 +9.84 +6.40 +136.84 +59.46 +7.14

P(t-test) 0.35* 0.70* 0.79* 0.13* 0.38* 0.84*

*P>0.05 (insignificant).

90

Table 60: Comparing Cmax, Tmax, AUC, T½, and the elimination rate constant

between: Clarithromycin + DW and (Clarithromycin + single dose of juice).

CAM +

DW

CAM +

single dose

of PJ Difference

Percent

change

Cmax(µg/ml) 1.83±0.22 2.25±0.46 +0.42* +22.9

Tmax (hr) 1±0.7 3±0.77 +2.0 +200

AUC͢͢͢͢͢͢͢͢͢ 0→t

(µg/ml*hr) 5.76±1.12 8.02±1.43 +2.26* +39.2

T½ (hr) 2.93 1.59 -1.34* -45.7

Ke 0.236 0.435 +0.12* +50.8


The data shows insignificant effect of single dose of PJ on Cmax and AUC of CAM

(appendix B, Table 74).

Table 61: Results of Clarithromycin with a multiple dose of pomegranate juice with

a comparison to a Clarithromycin with DW administration (n=6).

Time (hr)

Drug

assessed

CAM

+

Multiple

dose of juice

0.5 1

2

3

4

6

Mean(µg/ml) 1.21±0.32 1.10±0.25 1.15±0.15 1.16±0.20 0.72±0.18 0.55±0.20

Range 0.46-2.48 0.46-1.98 0.71-1.66 0.41-1.61 0.3-1.49 0.1-1.32

STDV 0.79 0.60 0.37 0.48 0.45 0.49

Comparing the M.P.C with CAM + DW

Difference

between 2

means

+0.16 -0.73 -0.10 +0.21 -0.02 -0.01

Cohen’s d +0.21 -1.15 -0.29 +0.45 -0.04 -0.02

Percent

change +15.28 -39.97 -7.95 +22.57 -2.60 -1.63

P(t-test) 0.76* 0.13* 0.66* 0.51* 0.95* 0.97*


91


between: Clarithromycin with DW and (Clarithromycin + multiple dose of juice).

CAM+

DW

CAM +

multiple

dose of PJ Difference

Percent

change

Cmax(µg/ml) 1.83±0.22 1.21±0.23 -0.62* -33.9

Tmax (hr) 1±0.7 0.5±0.43 -0.500 -50.00

AUC͢͢͢͢͢͢͢͢͢ 0→t

(µg/ml*hr) 5.76±1.12 5.20±0.58 -0.56* -9.7

T½ (hr) 2.03 3.29 +1.26* +62.0

Ke 0.35 0.21 -0.14* -40.0


The data shows insignificant effect of multiple dose of PJ on Cmax and AUC of CAM


As seen in (Table 63), if we compare between the single and multiple dose effect of PJ on

CAM pharmacokinetics, the data shows insignificant change.

Table 63: Comparison between single and multiple dose effect of PJ on

Clarithromycin.

CAM +

single dose

of P.J

CAM +

multiple dose

of PJ Difference

Percent

change

Cmax(µg/ml) 2.25±0.46 1.21±0.23 -1.13* -50.2

Tmax (hr) 3±0.77 0.5±0.43 -2.5 -83.3

AUC͢͢͢͢͢͢͢͢͢ 0→t

(µg/ml*hr) 8.02±1.43 5.20±0.58 -2.82* -35.2

T½ (hr) 1.59 3.29 +1.7* +106.9

Ke 0.435 0.21 -0.23* -51.7


92

Figure 11: Line chart showing the changes in mean plasma Clarithromycin

concentration with time after drug administration with DW, with single

dose of juice, and with multiple dose of juice.

As shown from the results, when a single dose a day of normal-strength

pomegranate fresh juice was administered to rats half an hour before CAM administration

(In comparison with DW-feed rats), the Cmax and AUC of CAM increased with two

hours lateness (Table 60). This is thought to be within the moderate range of significance

according to Cohen’s d measurement (i.e. there is no significant effect of short pre-

treatment with pomegranate juice on the pharmacokinetic profile of CAM).Two hours-

long delay to the appearance of CAM in serum is possibly not clinically significant, since

CAM has t½ of 5 to 7 hr (Chu S.Y. et al., 1992) and with twice-daily dosing, therapeutic

plasma concentrations of CAM would be maintained. However, two doses a day of

normal-strength pomegranate fresh juice was administered to rats for two days followed

by a single dose on the third day (the day of experiment) showed opposite results since

there was a declining in the pharmacokinetic parameters of CAM that were considered

moderate according to Cohen’s d measurement (Table 62).

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Pla

sma d

rug c

on

cen

trati

on

(µ

g/m

l)

Time (hour)

With D.W

With single dose P.J

With multiple dose P.J

93

The elevation of the pharmacokinetic parameters of Clarithromycin when

administered with single dose of pomegranate juice and the declining of these parameters

after multiple dose of pomegranate juice administration could be due to inhibition then

induction for the enteric metabolism since other studies showed the same results, e.g.

inhibitory effect on intestinal CYP3A4-mediated metabolism of carbamazepine after

single dose of pomegranate juice (Hidaka M. et al., 2005) and induction effect of enteric

CYP3A4 activity on carbamazepine metabolism after a multiple dose of pomegranate

juice (Adukondalu D. et al., 2010). Furthermore, the changing in t½ and the elimination

rate constant of Clarithromycin after single and multiple pomegranate juice

administration give an expectation that pomegranate juice could affect the hepatic-

mediated metabolism of Clarithromycin but with insignificant manner.

Comparing with grape fruit effect on CAM, pomegranate juice did not

significantly change Cmax of CAM but still greater than the effect of grapefruit juice

which was negligible (Cheng K.L. et al., 1998). Furthermore, the Tmax was delayed for

about two hours comparing with one hour lateness when administered with grapefruit

juice. These mild effects of pomegranate juice on the Cmax and Tmax of CAM can be

properly attributed to the inhibition of the intestinal CYP3A4 slightly greater than the

inhibition effect of grapefruit.

3.3.2 Effect of a single and multiple dose of pomegranate juice on Metronidazole

As shown in (Table 63) and (Figure 12), when MTZ administered alone, it reached

its mean maximum plasma level (13.35µg/ml) after one hour and then gradually declines

to reach minimum plasma concentration of (6.12µg/ml) after (6 hours) from the time of

drug administration.

As shown in (Table 64) and (Figure 12) the same drug when administrated 30 min

after a single dose (5 ml /kg) of PJ administration, the mean maximum concentration

increased to reach (12.62µg/ml) after (1 hours) from the point of drug administration then

continue declining until reach a negligible gap (difference in mean plasma drug

concentration) between a drug alone and drug with PJ at the sixth hour from

administration. The mean plasma drug concentration of MTZ after half an hour when a

94

single dose of PJ administered with MTZ was increased by (0.85) and return to decrease

at one hour by (0.73) with a percent change of (7.34%) and (5.4%), respectively

compared to MTZ administration with DW. Moreover, the mean plasma drug

concentration of MTZ decreased continuously reaching to a maximum lowering effect by

(11.8%) and (15.08%) after three and six hours, respectively, from drug administration.

The effect of this single dose of PJ used was evaluated as medium elevating effect

(Cohen’s d =0.37) at the half an hour time interval but this effect decreased with time

with a maximum declining effect at one hour time interval which was evaluated as strong

declining effect (Cohen’s d =1.43) Furthermore, Cmax, AUC, and t½ were decreased by

(5.5%), (7.86%), and (12.5%), respectively, with increasing in the elimination rate

constant by (14.2%) while Tmax was not changed, showed in (Table 65).These percent

changes in plasma MTZ pharmacokinetics when used with a single dose of PJ comparing

to singly use, however failed to reach the level of statistical significance which may be

contributed to a very small sample size or to low dose of PJ.

As shown in (Table 66) and (Figure 12), MTZ when administered 30 min after a

multiple dose (5ml/kg) of PJ (which administrated for two days two times daily and one

dose at the third day before experiment), the mean plasma concentration increased to

reach a maximum plasma level (19.15µg/ml) after an hour from drug administration. At

all time intervals the mean plasma concentrations of MTZ was obviously higher than that

of drug’s level administered with DW. and remain at high levels until reach a wide gap

between a drug alone and drug with PJ at the sixth hour from drug administration. The

mean plasma MTZ concentration when used after a multiple dose of PJ was elevated on

all time intervals by (6.422), (5.79), (8.5), (6.13), (5.8), and (4.26), respectively,

compared to administration with DW. Observing that maximum elevating value was after

two hours from MTZ administration following multiple dose of PJ. The effect of multiple

dose of PJ on elevating plasma MTZ level compared to its single drug use was evaluated

as a highly strong effect in all time intervals. This elevating in plasma MTZ concentration

level when used with a multiple dose of PJ compared to separately use could be clinically

considered as a significant elevating effect. In addition, Cmax, AUC, and t½ were

increased by (43.4%), (132.3%), and (27%), respectively, with decreasing in the

elimination rate constant by (6.25%) while Tmax was not changed, showed in (Table 67).

95

Table 64: Results of Metronidazole with DW (n=2).

Time (hr)

Drug

assessed

MTZ +

DW

0.5 1

2

3

4

6

Mean

(µg/ml) 11.58±0.08 13.35±0.4 10.48±0.49 10.65±0.43 7.77±0.15 6.12±0.38

Range 11.5-11.66 13.7-13.0 10.97-10 10.21-11.08 7.91-7.6 5.74-6.5

STDV 0.113 0.502 0.69 0.615 0.212 0.537

Table 65: Results of Metronidazole with a single dose of pomegranate juice with a

comparison to a Metronidazole with DW administration (n=4).

Time (hr)

Drug

assessed

MTZ

+

Single

dose of

juice

0.5 1

2

3

4

6

Mean

(µg/ml) 12.43±0.52 12.62±0.26 10.84±0.39 9.39±0.28 6.99±0.20 5.27±0.20

Range 11-13.5 12.2-13.3 10.05-11.7 8.83-9.99 6.6-7.4 4.85-5.7

STDV 1.046 0.515 0.781 0.551 0.390 0.397

Comparing the M.P.C with MTZ + DW

Difference

between 2

means

+0.85

-0.73

-0.358

-1.3

-0.77

-0.92

Cohen’s d +0.37 -1.43 -0.49 -0.54 -0.64 -0.49

Percent

change +7.34 -5.4 -3.4 -11.80 -9.95 -15.08

P(t-test) 0.34* 0.17* 0.62* 0.06* 0.065* 0.2*


96


between: Metronidazole with DW and (Metronidazole + single dose of juice).

MTZ+ DW

MTZ +

single dose

of PJ

Difference

Percent

change

Cmax(µg/ml) 13.35±0.35 12.62±0.30 -0.73* -5.5

Tmax (hr) 1 1±0.15 0.00 0.00

AUC0→∞

(µg/ml*hr) 94.13±6.04 86.73±1.09 -7.4* -7.86

T½ (hr) 4.47 3.91 -0.56* -12.5

Ke 0.155 0.177 +0.022* +14.2


The data shows insignificant effect of single dose of PJ on Cmax and AUC of MTZ


Table 67: Results of Metronidazole with a multiple dose of pomegranate juice with a

comparison to a Metronidazole with DW administration (n=4).

Time (hr)

Drug

assessed

MTZ

+

Multiple

dose of

juice

0.5 1

2

3

4

6

Mean

(µg/ml) 18.0±0.5 19.15±0.7 19.06±2.0 16.78±0.7 13.60±0.4 10.38±0.7

Range 16.8-19.3 17.7-21.1 16.3-24.8 15.4-18.4 12.46-14.6 8.97-12.2

STDV 1.021 1.435 4.026 1.325 0.883 1.416

Comparing the M.P.C with MTZ + DW

Difference

between 2

means

+6.42

+5.79

+8.5

+6.13

+5.8

+4.26

Cohen’s d +11.36 +5.96 +3.6 +7.98 +11.05 +5.14

Percent

change +55.47 +43.4 +81.9 +57.6 +75.08 +69.6

P(t-test) 0.001** 0.006** 0.047** 0.004** 0.001** 0.02**

**P˂0.05 (significant).

97


between: Metronidazole with DW and (Metronidazole + multiple dose of juice).

MTZ+

DW

MTZ +

multiple

dose of PJ

Difference

Percent

change

Cmax(µg/ml) 13.35±0.35 19.15±1.60 +5.8** +43.4

Tmax (hr) 1 1±0.35 0.00 0.00

AUC0→∞

(µg/ml*hr) 94.13±6.04 218.68±12.07 +124.55** +132.3

T½ (hr) 4.47 5.68 +1.2* +27

Ke 0.155 0.122 -0.033* -21.2

**P>0.05 (significant), *P> 0.05 (insignificant).

The data shows significant effect of multiple dose of PJ on Cmax, and AUC of MTZ


As seen in (Table 69), if we compare between the single and multiple dose effect of PJ on

MTZ pharmacokinetics, the data shows significant change in Cmax and AUC of MTZ.

Table 69: Comparison between single and multiple dose effect of PJ on

Metronidazole.

MTZ + single

dose of P.J

MTZ +

multiple dose of

PJ

Difference Percent

change

Cmax(µg/ml) 12.62±0.3 19.15±1.60 +6.55** +51.9

Tmax (hr) 1±0.15 1±0.35 0.00 0.00

AUC0→∞

(µg/ml*hr) 86.73±1.09 218.68±12.07 +131.98** +152.2

T½ (hr) 3.91 5.68 +1.77* +45.3

Ke 0.177 0.122 -0.06* -31.0

**P>0.05 (significant), *P> 0.05 (insignificant).

98

Figure 12: Line chart showing the changes in mean plasma Metronidazole

concentration with time after drug administration with DW, with single

dose of juice, and with multiple dose of juice.

The effect of pomegranate juice or even grapefruit juice on Metronidazole has not

been studied previously. In the current study, in comparison with DW-feed rats, a single

dose a day of normal-strength pomegranate fresh juice was administered to rats half an

hour before Metronidazole administration, Metronidazole pharmacokinetic parameters

were very slightly decreased by pre-treatment with single dose of pomegranate juice with

unchanged Tmax (Table 65). In contrast, two doses a day of normal-strength

pomegranate fresh juice was administered to rats for two days followed by a single dose

on the third day, showed a considerable increase in the pharmacokinetic parameters

(Cmax and AUC) (P<0.05) of Metronidazole (Table 67). From this finding we may

conclude that pomegranate juice with a multiple dose pomegranate juice pre-treatment is

a good intestinal enzyme inhibitor. Moreover, there was a slight increase on t½ and very

slight decrease on the elimination rate constant which means that the hepatic enzymes

could be not affected.

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Dru

g p

lasm

a c

on

cen

trati

on

µg/m

l

Time(hour)

With D.W

With single dose P.J

With multiple dose P.J

99

3.4 The modifying effect of concomitantly administered Clarithromycin and

Metronidazole on their pharmacokinetic profiles

In general, drug interactions can be attributed to pharmacodynamic (i.e. due to

synergistic or antagonistic effects) or pharmacokinetic (i.e. during drug absorption,

distribution, metabolism or elimination) processes (Reynolds J.C., 1990). Moreover,

interactions may also be based on biopharmaceutical modifications, e.g. altered solubility

of the active drug ingredient or its release from the dosage form. Pharmacokinetic

interactions can generally be considered in two ways: the influence of a drug on the

pharmacokinetics of a co-administered medication or the influence of a concomitant

medication on the pharmacokinetics of the drug (Vanderhoff B.T. and Tahboub R.M.,

2002).

The major function of drug metabolism is to make drugs more hydrophilic and

more easily excreted in the urine or bile. CYP system responsible for metabolism of

many compounds by phase I metabolism forming biotransformation products that are

either easily eliminated by the kidneys or undergo further step of metabolism in phase II

reactions prior to elimination ( Meyer U.A., 1996).

The CYP system is a large family of isoenzymes that is found chiefly in the

hepatocytes and small intestine enterocytes and, to a lesser extent, in the kidneys, lungs,

brain and other tissues. Most of human drug metabolism is mediated by six CYP

isoenzymes: CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1 and CYP3A4 (Meyer

U.A., 1996).

The majority of drug-drug interactions occur as a result of competitive inhibition

when two compounds compete with each other on the same binding site of a CYP

isoenzyme. In this case, the extent of interaction depends on the compounds affinities for

the CYP enzyme (i.e. the substance with the higher affinity to enzyme will inhibit

biotransformation of the lower affinity substrate) (Shapiro L.E. and Shear N.H., 2002).

Most major drug-drug interactions mediated by competitive inhibition of the

isoenzymes are at two main sites: the intestine and liver. Induction or inhibition of the

activity of CYP isoenzymes in the liver can lead to changes in hepatic clearance.

100

CYP3A4 is the predominant CYP isoenzyme in the human intestine and its activity plays

an important role in altering the first-pass metabolism of drugs (Cummins C.L. et al.,

2002) Therefore, intestinal CYP3A4 inhibition also can affect in a wide extent the

bioavailability of the orally administered CYP3A4-substrates ( Shen D.D et al., 1997)

A triple therapy of a proton pump inhibitor (PPI), anti-secretory drugs for

treatment of gastric acid-related disordered , and two selections of antimicrobial drugs is

commonly used and recommended for Helicobacter pylori (H.pylori), one of the main

causes of peptic ulcer diseases (PUD) (Neville P.M. et al., 2001). (H. pylori)-positive

Patients with long-term PPIs therapy are under the risk for the development of gastric

atrophy. Therefore, eradication of H. pylori is important for preventing the progression of

gastritis when PPI therapy is added (Schenk B.E. et al., 2000). The widely used

antimicrobial drugs for eradication of H. pylori are CAM and MTZ (Megraud F., 1998).

The pharmacokinetic interaction between CAM and MTZ when concomitantly

administered to rats was not studied previously although the H.Pylori-treatment fail is

considered as a serious problem increasingly. Moreover, all previous studies were mostly

done to investigate the interaction between CAM and proton pump inhibitors.

3.4.1 Effect of combination on Clarithromycin

As shown in (Table 68) and (Figure 13), when CAM administered alone, it

reached its mean maximum plasma level (1.27µg/ml) after two hours and then gradually

declines to reach minimum plasma concentration of (0.67µg/ml) after (6 hours) from the

time of drug administration.

As shown in (Table 69) and (Figure 13) the same drug when administrated with

MTZ the mean maximum concentration increased to reach (1.15µg/ml) after an hour

from the moment of drug administration but one hour earlier than that when administered

alone with a very slight reduction, even so, the reduction percentage in the mean

maximum level is not exceed (9.4%(. The mean plasma drug concentration of CAM in

the most time intervals when administered with MTZ was very slightly decreased

compared to its administration alone. According to the values of Cohen’s d the effect of

combination on CAM was evaluated as moderate lowering effect except at four hours

101

time interval was considered as strong lowering effect (Cohen’s d=1.67). (Table 70)

shows the comparison in the pharmacokinetic parameters between CAM when

administered alone and CAM after combination with MTZ. Cmax and AUC decreased by

(9.4%) and (6.7%), respectively, while t½ was very slightly increased by (40%), on the

other hand, Tmax decreased by one hour.

Table 70: Results of Clarithromycin alone (n=7).

Time (hr)

Drug

assessed

CAM

alone

0.5 1

2

3

4

6

Mean

(µg/ml) 1.06±0.19 1.25±0.13 1.27±0.14 1.09±0.18 0.91±0.09 0.67±0.04

Range 0.13-1.58 0.88-1.73 0.80-1.85 0.59-1.96 0.59-1.17 0.54-0.88

STDV 0.50 0.34 0.36 0.48 0.24 0.11

Table 71: Results of Clarithromycin after combination with Metronidazole with a

comparison to a lone Clarithromycin administration (n=5).

Time (hr)

Drug

assessed

CAM

combined

0.5 1

2

3

4

6

Mean

(µg/ml) 1.12±0.06 1.15±0.03 1.10±0.10 0.90±0.05 0.61±0.06 0.54±0.09

Range 0.9-1.3 1.08-1.2 0.92-1.45 0.73-1.07 0.45-0.8 0.34-0.88

STDV 0.14 0.06 0.22 0.12 0.13 0.21

Comparing the M.P.C with CAM alone

Difference

between 2

means

+0.05 -0.10 -0.18 -0.19 -0.30 -0.14

Cohen’s d +0.17 -0.50 -0.61 -0.61 -1.67 -0.8

Percent

change +5.10 -7.95 -13.91 -17.09 -33.10 -20.28

P(t-test) 0.82* 0.54* 0.35* 0.43* 0.03** 0.17*


102


between: Clarithromycin alone and Clarithromycin after combination with

Metronidazole.

CAM

alone

CAM

Combined Difference

Percent

change

Cmax(µg/ml) 1.27±0.13 1.15±0.06 -0.12* -9.4

Tmax (hr) 2.0±0.41 1.000±0.3 -1.000 -50.00

AUC0→∞

(µg/ml*hr) 9.03±0.62 8.42±0.8 -0.61* -6.7

T½ (hr) 3.25 4.55 +1.3* +40

Ke 0.213 0.151 -0.062* -29.1


The data shows insignificant change on Cmax and AUC of CAM after combination with

MTZ (Appendix B, Table 76).

Figure 13: Line chart showing the changes in mean plasma Clarithromycin

concentration with time after separately drug administration and in

combination with Metronidazole.

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Dru

g p

lasm

a c

on

cen

trati

on

µg/m

l

Time (hour)

CAM alone

CAM combined

103

3.4.2 Effect of combination on Metronidazole

As shown in (Table 71) and (Figure 14), when MTZ administered alone, it reached

its mean maximum plasma level (12.96µg/ml) after one hour and then gradually declines

to reach minimum plasma concentration of (5.62 µg/ml) after (6 hours) from the time of

drug administration. The same drug when administrated with CAM, the mean maximum

concentration increased to reach (12.32 µg/ml) and also gradually declines to reach

minimum plasma concentration of (6.24 µg/ml) after (6 hours) with a very narrow gap

(difference in mean plasma drug concentration) between a drug alone and drug with

MTZ.

As shown in (Table 72), the mean plasma drug concentration of MTZ after half an

hour, and after the last hour (six hours) from administration with CAM was increased by

(0.094) and (0.624), respectively compared to administration alone. However, the mean

plasma drug concentration of MTZ after the remaining four hours (1, 2, 3 and 4 hours)

from administration with CAM was decreased by (0.643), (0.224), (0.03), and (0.716),

respectively, compared to administration alone. The effect of drug combination on

lowering plasma MTZ level on the first hour and the forth hour after concomitantly MTZ

administration with CAM was evaluated as strong lowering effect (Cohen’s d =1.30 and

Cohen’s d =1.28), respectively. However, the effect was considered strong elevating

effect (Cohen’s d =0.94) at the last time interval. These changes in plasma MTZ

concentration when used with CAM comparing to singly use failed to reach the level of

statistical significance (P>0.05).

(Table 73) shows a slight decreasing in Cmax and AUC by (4.94%) and (2.13),

respectively. On the other hand, there was a slight increasing in t½ by (19.78%) with

decreasing of elimination rate constant by (16.51%) while there was no change in the in

Tmax.

104

Table 73: Results of Metronidazole alone (n=6).

Time (hr)

Drug

assessed

MTZ

alone

0.5 1

2

3

4

6

Mean

(µg/ml) 11.14±0.23 12.96±0.18 11.28±0.34 9.42±0.20 8.00±0.19 5.62±0.20

Range 10.32-11.5 12.5-00.8 10.3-12.5 8.8-9.97 7.4-8.8 4.8-6.2

STDV 0.562 0.452 0.822 0.484 0.475 0.501

Table 74: Results of Metronidazole after combination with Clarithromycin with a

comparison to a lone Metronidazole administration (n=5).

Time (hr)

Drug

assessed

MTZ

combined

0.5 1

2

3

4

6

Mean

(µg/ml) 11.24±0.40 12.32±0.24 11.06±0.27 9.39±0.48 7.29±0.29 6.24±0.37

Range 9.99-12 11.6-13 10.5-11.8 8.45-11.1 6.47-7.85 5.01-7.05

STDV 0.894 0.540 0.611 1.066 0.643 0.823

Comparing the M.P.C with MTZ alone

Difference

between 2

means

+0.094

-0.643

-0.224

-0.03

-0.7

+0.624

Cohen’s d +0.13 -1.30 -0.31 -0.04 -1.28 +0.94

Percent

change 0.84 -4.96 -1.99 -0.32 -8.95 11.10

P(t-test) 0.84* 0.06* 0.63* 0.95* 0.062* 0.16*


105


between: Metronidazole alone and (Metronidazole after combination with

Clarithromycin).

MTZ

alone

MTZ

Combined Difference

Percent

change

Cmax(µg/ml) 12.96±0.18 12.32±0.2 -0.64* -4.94

Tmax (hr) 1.000 1.000±0.09 0.000 0.00

AUC0→t

(µg/ml*hr) 53.621±0.6 52.480±0.55 -1.141* -2.13

T½ (hr) 3.991 4.780 +0.789* +19.78

Ke 0.174 0.145 -0.0298 -16.51


The data shows insignificant change on pharmacokinetic parameters of MTZ after

combination with CAM (Appendix B, Table 77).

Figure 14: Line chart showing the changes in mean plasma Metronidazole

concentration with time after separately drug administration and in

combination with Clarithromycin.

0

2

4

6

8

10

12

14

16

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Dru

g p

lasm

a c

on

cen

trati

on

µg/m

l

Time (hour)

MET alone

MET combined

106

According to the results obtained in this study, there was no interaction between

CAM and MTZ since Cmax, Tmax, and AUC were calculated for both drugs and showed

no change comparing with each one alone.

One of the aims of this study was to investigate the pharmacokinetic profile of

the interested drugs when concomitantly administered in the presence of pomegranate

juice. This step of the study was not performed due to following reasons:

1- According to the results obtained, there was no significant effect of a single

pomegranate juice dose on CAM and MTZ pharmacokinetic parameters when

administered separately. In addition, there was no drug-drug interaction between them.

This make us to assume that single dose of pomegranate juice will not affect their

pharmacokinetic parameters when combined together.

2- If we suppose that multiple dose of pomegranate juice could affect the

pharmacokinetic of the combination, this supposition is still unscientific since CAM

was not affected by multiple pomegranate juice doses and also was not affected by

concomitant administration with MTZ, and therefore it couldn’t be affected by them if

combined together. Moreover, for MTZ, also there will be no change in its

pharmacokinetic behavior from that obtained (when administered with multiple

pomegranate juice doses) since it was not affected by CAM.

3- Other reasons that should be considered, in any scientific research. In addition to

wasting of time, cost, and labor. There should be ethical considerations represented by

the three R’s which are defined as the replacement of animals, a reduction in the

numbers used or a refinement of techniques that may reduce or replace animals or

reduce the pain, stress or distress of the animals (Farnaud S., 2009).

107

4. Conclusion

A simple, reproducible analytical method with high resolution and sensitivity was

used for simultaneous quantification of Clarithromycin and Metronidazole. An acceptable

recovery was achieved in this method which was with a minimum value of (97.75 and

96.09) % for Clarithromycin and Metronidazole, respectively. The method was partially

validated and all of obtained data was within the acceptance criteria according to United

State Food and Drug Administration and European Medicines Agency guidelines.

The effect of single and multiple doses of fresh pomegranate juice on the

pharmacokinetics profile for each of Clarithromycin and Metronidazole was investigated.

In comparison with distilled water-feed rats the results showed insignificant elevation

effect of single dose pre-treatment with pomegranate juice on the pharmacokinetic profile

of Clarithromycin which could be due to inhibition of the enteric metabolic enzymes

(Same results for the effect of pomegranate juice on carbamazepine, Hidaka M. et al.,

2005). Furthermore, two hours-long delay to the appearance of Clarithromycin in serum

is possibly not clinically significant, since Clarithromycin has t½ of 5 to 7 h and with

twice-daily dosing, therapeutic plasma concentrations of Clarithromycin would be

maintained. This shifting on Cmax of Clarithromycin in presence of single dose of

pomegranate juice could be due to changing on the absorption rate, releasing after

accumulation of the drug in some organs of the body, or manipulation on the metabolic

enzymes. In addition, the multiple dose administration of pomegranate juice showed

insignificant declining in the pharmacokinetic parameters of Clarithromycin which could

be due to induction of the enteric metabolic enzymes (Same effect on carbamazepine

metabolism after a multiple dose of pomegranate juice, Adukondalu D. et al., 2010).

Moreover, the changing in t½ and the elimination rate constant of Clarithromycin after

single and multiple pomegranate juice administration give an expectation that

pomegranate juice could affect the hepatic-mediated metabolism of Clarithromycin but

with insignificant manner.

In case of Metronidazole, single dose pre-treatment with pomegranate juice

showed negligible effect on its pharmacokinetic parameters. In contrast, multiple doses of

normal-strength pomegranate fresh juice administration showed a considerable increase

in the pharmacokinetic parameters (Cmax and AUC) (P<0.05) of Metronidazole. From

108

this finding we may conclude that pomegranate juice with a multiple dose pre-treatment

is a good intestinal enzyme inhibitor, as well as grapefruit juice (Veronese M.L. et al.,

2003, Paine M.F. and Oberlies N.H., 2007). Since there was a slight increase on the t½

and very slight decrease on the elimination rate constant, we can conclude that the

hepatic enzymes could not be affected.

The effect of concomitant administration on the pharmacokinetic profile of each

drug also was investigated since these drugs are commonly used in a regimen with proton

pump inhibitors as a triple therapy for treatment of peptic ulcer disease caused by

Helicobacter pylori infection. The results showed no significant interaction between them

that is why we didn’t continue to investigate for the effect of pomegranate juice on such

combination. The absence of the pharmacokinetic interaction between Clarithromycin

and Metronidazole gives some indication that they have different metabolic pathways and

they do not compete at the same metabolic enzymes.

Since multiple dose of pomegranate juice affected significantly the enteric

metabolism of Metronidazole (as mentioned above) and as concluded that the later has

other than CYP3A4-Clarithromycin mediated metabolism, therefore these findings let us

to conclude that pomegranate juice could affect Metronidazole-mediated enteric

metabolic enzymes other than CYP3A4.

From previous studies on the effect of pomegranate juice on other medications,

e.g. lack of the clinical and pharmacokinetical significance of the effect of pomegranate

juice when it is given with CYP3A4-mediated metabolism of midazolam (Farkas D. et

al., 2007; Misaka S. et al., 2011) and its significant inhibitory effect on enteric CYP2C9-

mediated metabolism of tolbutamide in rats (Nagata M. et al., 2007), we can expect that

pomegranate juice could affect CYP2C9-mediated metabolism of Metronidazole.

On the other hand, there are different enteric metabolic enzymes involved in the

orally administered drug metabolism; therefore, we cannot confirm these findings unless

further in vitro and in vivo investigations are established.

109

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Appendix (A):

HPLC Chromatograms

125

Figure 15: Clarithromycin blank chromatogram.

126

Figure 16: Clarithromycin zero chromatogram.

Clindamycin

127

Figure 17: Clarithromycin LLOQ chromatogram.

Clindamycin

Clarithromycin

128

Figure 18: Clarithromycin SCC7 chromatogram.

Clindamycin

Clarithromycin

129

Figure 19: Clarithromycin rat unknown sample chromatogram at 4.00 hr measured

as 0.878 µg/ml.

Clarithromycin Clindamycin

130

Figure 20: Metronidazole blank chromatogram.

131

Figure 21: Metronidazole zero chromatogram.

Clindamycin

132

Figure 22: Metronidazole LLOQ chromatogram.

Clindamycin

Metronidazole

133

Figure 23: Metronidazole SCC7 chromatogram.

Clindamycin

Metronidazole

134

Figure 24: Metronidazole rat unknown sample chromatogram at 4.00 hr measured

as 7.83 µg/ml.

Clindamycin

Metronidazole

135

Appendix (B):

Preclinical Data

136

Table 76: Data measured for Clarithromycin experiments after administration with

DW, single dose of PJ, and multiple dose of PJ.

*P>0.05 (insignificant), **P˂0.05 (significant).

Plasma concentrations µg/ml

After Pharmacokinetic Parameters

A) CAM

With

DW

30

min.

1 hr 2hr 3hr 4hr 6hr Cmax

(µg/ml)

AUC͢͢͢͢͢͢͢͢͢ 0→t

(µg/ml*hr)

T1/2

(hr) Ke

1 1.11 2.25 1.40 1.02 0.68 0.43 2.25 6.11 2.10 0.33

2 2.05 2.31 1.44 1.56 1.32 1.04 2.31 8.78 4.33 0.16

3 0.86 0.86 1.36 0.52 0.36 0.23 1.36 3.73 1.58 0.44

4 0.19 1.91 0.79 0.68 0.59 0.55 1.91 4.43 2.77 0.25

Total N 4 4 4 4 4 4 4 4 4 4

B) With Single dose PJ

1 2.94 2.61 1.91 1.62 3.21 0.92 2.94 7.84 0.58 1.2 2 1.55 1.93 1.62 4.30 0.93 0.60 1.93 10.83 1.05 0.66 3 1.66 2.54 2.03 1.67 0.87 0.60 2.54 6.95 2.39 0.29 4 0.95 1.18 0.92 0.74 0.53 0.78 1.18 13.88 8.66 0.08 5 0.67 1.09 0.67 4.56 0.52 0.25 4.56 5.47 0.71 0.97 6 1.59 2.72 0.82 0.59 0.99 0.48 2.72 3.15 1.98 0.35

Total N 6 6 6 6 6 6 6 6 6 6

P(t-test)

between

A and B

0.35

*

0.70

*

0.79

*

0.13

*

0.38

*

0.84

*

0.22

*

0.28

* 0.94

*

0.22

*

C) With Multiple dose PJ

1 1.64 1.41 1.17 1.47 0.83 0.55 1.64 6.18 6.30 0.11 2 2.48 1.98 1.66 1.51 1.49 0.95 2.48 5.67 3.85 0.18 3 1.45 1.44 1.05 1.22 0.86 1.32 1.45 6.63 4.62 0.15 4 0.57 0.77 0.82 1.61 0.37 0.19 1.61 6.20 0.98 0.71 5 0.68 0.54 1.48 0.73 0.30 0.1 1.48 3.67 1.03 0.67 6 0.46 0.46 0.71 0.41 0.46 0.21 0.71 2.86 2.31 0.3

Total N 6 6 6 6 6 6 6 6 6 6

P(t-test)

between

A and C

0.76* 0.13* 0.66* 0.51* 0.95* 0.97* 0.25* 0.68* 0.69* 0.70*

P(t-test)

between

B and C

0.46* 0.04** 0.54* 0.17* 0.34* 0.82* 0.06* 0.13* 0.69* 0.28*

137

Table 77: Data measured for Metronidazole experiments after administration with

DW, single dose of PJ, and multiple dose of PJ.



After

Pharmacokinetic Parameters

A) MTZ

With

DW

30

min.


(µg/ml)

AUC0→∞

(µg/ml*hr)

T1/2

(hr) Ke

1 11.66 13.71 10.97 11.08 7.92 6.50 13.71 100.17 4.62 0.15

2 11.50 13.0 10.00 10.21 7.62 5.74 13.0 88.09 4.33 0.16

Total N 2 2 2 2 2 2 2 2 2 2

B) With Single dose PJ

1 11.13 12.31 10.35 9.02 7.38 5.71 12.31 88.27 4.62 0.15

2 12.86 12.51 11.19 9.71 6.60 5.32 12.86 85.18 4.33 0.16

3 13.59 12.29 10.05 8.84 6.73 4.85 13.59 75.78 3.65 0.19

4 12.15 13.38 11.76 10.00 7.28 4.92 13.38 78.31 3.47 0.20

Total N 4 4 4 4 4 4 4 4 4 4

P(t-test)

between

A and B

0.34

*

0.17

*

0.62

*

0.06

*

0.065

*

0.20

*

0.54

*

0.1

*

0.34

*

0.33

*

C) With Multiple dose PJ

1 16.84 18.62 16.28 18.37 14.61 12.22 18.64 235.74 8.66 0.08

2 17.75 17.70 16.28 15.39 13.73 10.71 17.75 201.61 7.70 0.09

3 18.11 21.11 24.81 17.30 13.61 9.63 24.81 137.70 2.89 0.24

4 19.31 19.15 18.89 16.05 12.46 8.98 19.30 151.09 4.95 0.14

Total N 4 4 4 4 4 4 4 4 4 4

P(t-test)

between

A and C

0.001 **

0.002 **

0.021**

0.002 **

0.0004 **

0.006 **

0.02 **

0.027 **

0.47*

0.77*

P(t-test)

between

B and C

0.0002**

0.0001**

0.007 **

0.00005**

0.00001**

0.0004**

0.0047 **

0.0048 **

0.18*

0.37*

138

Table 78: Data measured for Clarithromycin experiments alone and after

concomitant administration with Metronidazole.



After


CAM

alone

30

min.


(µg/ml)

AUC0→∞

(µg/ml*hr)

T1/2

(hr) Ke

1 0.13 1.06 1.10 1.35 1.13 0.70 1.35 8.99 3.15 0.22

2 1.24 1.01 1.10 0.80 1.17 0.60 1.24 8.45 5.33 0.13

3 1.12 1.27 1.47 0.78 0.64 0.54 1.47 7.79 2.77 0.25

4 1.03 1.09 0.80 0.59 0.83 0.65 1.09 7.67 6.93 0.1

5 0.79 0.88 1.06 0.80 0.59 0.68 1.06 7.67 6.30 0.11

6 1.58 1.73 1.53 1.96 1.09 0.66 1.96 10.97 3.65 0.19

7 1.54 1.69 1.85 1.33 0.95 0.88 1.85 11.65 3.65 0.19

Total N 7 7 7 7 7 7 7 7 7 7

After combination with MTZ

1 1.28 1.22 0.92 0.89 0.46 0.35 1.28 6.67 2.89 0.24

2 0.89 1.20 1.14 0.94 0.81 0.88 1.20 11.34 11.55 0.06

3 1.14 1.09 1.05 1.07 0.56 0.58 1.14 8.72 4.95 0.14

4 1.12 1.08 0.92 0.73 0.64 0.45 1.12 7.39 4.08 0.17

5 1.15 1.15 1.45 0.89 0.61 0.44 1.45 7.99 2.31 0.3

Total N 5 5 5 5 5 5 5 5 5 5

P(t-test) 0.82

*

0.54

*

0.35

*

0.43

*

0.03

**

0.17

*

0.22

*

0.57

*

0.74

*

0.81

*

139

Table 79: Data measured for Metronidazole experiments alone and after

concomitant administration with Clarithromycin.



After


MTZ

alone

30

min.


(µg/ml)

AUC͢͢͢͢͢͢͢͢͢ 0→t

(µg/ml*hr)

T1/2

(hr) Ke

1 11.52 12.94 10.84 8.76 7.37 5.36 12.94 51.48 3.85 0.18

2 11.38 12.94 11.02 9.56 8.09 4.87 12.94 52.98 3.47 0.20

3 11.55 13.81 12.53 9.80 7.87 5.58 13.81 55.85 3.85 0.18

4 10.32 12.83 10.35 9.50 8.82 6.23 12.83 54.09 4.62 0.15

5 11.55 12.46 12.03 8.92 7.82 5.53 12.46 53.33 4.33 0.16

6 10.54 12.81 10.94 9.98 8.08 6.13 12.81 54.05 4.62 0.15

Total N 6 6 6 6 6 6 6 6 6 6

After combination with CAM

1 11.70 12.60 10.90 11.10 6.47 5.01 12.60 52.02 3.85 0.18

2 9.99 13.00 11.60 8.54 7.83 6.26 13.00 52.89 4.62 0.15

3 11.90 11.60 10.50 8.45 6.74 7.05 11.90 50.76 4.33 0.16

4 10.60 12.00 10.50 9.49 7.85 6.92 12.00 52.99 6.30 0.11

5 12.00 12.40 11.80 9.35 7.56 5.96 12.40 53.75 4.62 0.15

Total N 5 5 5 5 5 5 5 5 5 5

P(t-test) 0.84* 0.06* 0.63* 0.95* 0.062* 0.16* 0.06* 0.18* 0.18* 0.18*

140

الملخص

بوجود ن الفئرادراسة تحليلية ذات مصداقية لمعايرة الكالريثرومايسن والميترونايدازول في دم

عصير الرمان

إعداد

هيفاء توفيق ابو طبيخ

المشرف المشارك المشرف

هديا الدكتور وائل ابو ح الدكتور إياد مالا

درة على اإلعتقاد بأن له القاستهالك عصير الرمان اصبح شائعا اليوم وخصوصا في دول الشرق األوسط نتيجة

ايدازول هي الكالريثرومايسين و الميترون مثل المضادات الحيوية وأن بعض ، العالج والوقاية من األمراض الشائعة

ي على خاصة في عالج القرحة المعدية الناتجة عن اإللتهاب البكتيرمعا قد تعطىمن األدوية شائعة اإلستعمال و

ي على نفس . إضافة لذلك ، كال الدوائين لهما التأثير المثبط واأليضفشل العالج بصورة متزايدة الرغم من مشكلة

اإلنزيم.

ائين معا في دم ب مستوى الدولحسا وتم التحقق منها وذلك حساسة، و سريعة، يلية بسيطة لقد تم استخدام طريقة تحل

ون من وقد كان الطور المتحرك يتك ، باستخدام جهاز اإلستشراب المائي عالي اإلنجاز والطيف الكتليالفئران

معدل وكان ، مايكروميتر 0بقطر 01 كربونفصل نوع بعمود ( %5.0) (الفورميك) النمليك الميثانول وحمض

. مل/دقيقة 50.بحدود التدفق

ايسن بة استخالص الكالريثرومحيث ان نس ، على درجة عالية من الجودة البالزما منانت طريقة اإلستخالص ك

. مع وجود مقدار دقة جيد جدا لكال الدوائين (51.5%) وكانت نسبة استخالص الميترونايدازول(%57.70كانت )

ير الرمان على حركية ران بعصفئمسبقة القصيرة والطويلة األمد للالنتائج تبين عدم وجود تأثير للمعالجة الباستعراض

اهمية كون له وهذا التأثير قد ال ت ،الكالريثرومايسن ماعدا تأخر الدواء ساعتين للوصول إلى أعلى تركيز له في الدم

تأثير أظهر إعطاء عصير الرمان لمدة طويلة نسبيا قبل جرعة الميترونايدازول ، من ناحية اخرىواضحة سريريا.

وائيد خلأيضا لم يظهر اي تدا)بجرعة واحدة( عطاء الدوائين بنفس الوقتإ. أما الفأر جسمواضح على حركيته في

بينهما.

VALIDATION AND DETERMINATION OF CLARITHROMYCIN … Tawfeeq... · ii validation and determination of clarithromycin and metronidazole in rat plasma by using high performance liquid

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