Formulation and evaluation of enalapril maleate sustained ...shodhganga.inflibnet.ac.in/bitstream/10603/90306/14/22_appendix v... · release formulations have been developed to improve
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
International Journal of PHARMACEUTICAL AND BIOMEDICAL
RESEARCH
Research article
Formulation and evaluation of enalapril maleate sustained release matrix tablets
Received: 06 Dec 2012 / Revised: 30 Dec 2012 / Accepted: 10 Jan 2013 / Online publication: 31 Jan 2013
ABSTRACT
The aim of the present research work was to develop and evaluate the sustained release matrix tablets of enalapril maleate. The tablet was formulated using HPMC KM and HPMC K15 M polymers by wet granulation method. In vitro drug release study was carried out in simulated gastric fluid (0.1 N HCl) for the first 2h and in phosphate buffer (pH 6.8) for the next 3h following USP apparatus II paddle method. An independent model method, Lin Ju and Liaw’s similarity factor (ƒ2) were used to compare various dissolution profiles. In order to describe the enalapril maleate release kinetics from individual tablet formulations, the corresponding dissolution data were fitted in various kinetic dissolution models: zero order, first order, Higuchi, Korsmeyer Peppas and Hixon Crowell. The results indicated that the drug release characteristics from HPMC polymer matrices follow Higuchi square root time kinetics and the mechanism of drug release was both diffusion and erosion.
Key words: Oral dosage form, Controlled drug release, Half-life, HPMC KM, Release kinetics
1. INTRODUCTION
Oral dosage forms has long been the most popular and convenient route of drug delivery. Various types of modified release formulations have been developed to improve the patient compliance and also clinical efficacy of the drug. The sustained release oral dosage forms have been demonstrated to improve therapeutic efficacy by maintaining steady state drug plasma concentration.
Nonionic cellulose ethers and hydroxypropyl methyl cellulose (Hypromellose, HPMC) have been widely studied for their application in oral sustained release formulations [1]. Such hydrophilic polymers are most popular because of their flexibility to get a desirable drug release profile, cost effectiveness and broad regulatory acceptance [2]. HPMC has always been a first choice for formulation of hydrophilic matrix systems, because of providing robust mechanism, choice of viscosity grades, nonionic nature, consistent reproducible release profiles, cost effectiveness and
utilization of existing conventional equipment and methods [3]. HPMC most widely used as the gel forming agent in the formulations of solid, liquid, semisolid and controlled release dosage forms. The adjustment of the polymer concentration, the viscosity grades and the addition of different types and levels of excipients to the HPMC matrix can modify the drug release rates [4].
Drug release from dosage form like tablets capsules, and granules shows complex interaction between mechanisms like wetting, capillary penetration, swelling, disintegration diffusion, dissolution, erosion etc. These processes are mainly depends on type, quantity and properties of the drug and excipients as well as manufacturing processes. Polymer dissolution, erosion in solvent is an important area in drug delivery system, which allows for optimization of design and processing of drug dosage form as well as selection of suitable excipients. The ideal drug delivery system is one which provides the drug only when and where required and in minimum dose is required to give the desired therapeutic.
When the dosage form introduced into the solvent, swelling occur allowing increased mobility of drug and it diffuses out of polymer in the surrounding fluid. Various mathematical models can be applied to the dissolution profile
Somnath Sakore and Bhaswat Chakraborty, Int J Pharm Biomed Res 2013, 4(1), 21-26
22
to describe the mechanism and kinetics of dissolution process, whereas, it is quite difficult to create mathematical equations due to different dissolution curves shows very different shapes.
The hypertensive patients are more prone to morning surge in blood pressure and hypertensive attacks during morning hours between 5 a.m. to 9 a.m. The development sustained release tablets of enalapril are expected to avoid acute overdose, and to prevent morning hypertension [5]. The other advantages of sustained release dosage forms are patient compliance, reduction of local and systemic side effects, minimization of peaks and valleys in drug blood levels [6].
Enalapril, an orally-active, long-acting, nonsulphydryl angiotensin-converting enzyme (ACE) inhibitor, is extensively hydrolyzed in vivo to enalapril at its bioactive form. Bio activation probably occurs in the liver. Metabolism beyond activation to enalapril is not observed in man. Administration with food does not affect the bioavailability of enalapril; excretion of enalapril and enalapril at is primarily renal. Enalapril reduces blood pressure in hypertensive patients by decreasing systemic vascular resistance. The blood pressure reduction is not accompanied by an increase in heart rate. Furthermore, cardiac output is slightly increased and cardiovascular reflexes are not impaired [7].
In the present work, enalapril maleate sustained release matrix system has been developed using HPMC KM and HPMC K15 M polymers by wet granulation method. In order to compare the dissolution profiles, Lin Ju and Liaw’s similarity factor (ƒ2) was used. In order to describe the release kinetics and the mechanism of drug release, dissolution data were fitted in various kinetic dissolution models: zero order, first order, Higuchi, Korsmeyer Peppas and Hixon Crowell.
2. MATERIALS AND METHODS
2.1. Chemicals and reagents
Enalapril maleate was a gift sample from Cadila Pharmaceuticals, Ahmedabad. All other chemicals used were of analytical reagent grades.
2.2 Preparation of tablets
Different tablets formulations were prepared by wet granulation technique. All powders were passed through 60 mesh. Required quantities of drug and polymers were mixed thoroughly, and sufficient quantity of isopropyl alcohol and methylene dichloride was added slowly as granulating fluid. Dummy granules were added to improve flow property of granules. The granules were passed through 22/44 mesh and dried at room temperature for 12h. Magnesium stearate was added as lubricant. Lactose was used as diluents, Starch paste is used as binder for granules. Finally were subjected to
compression. Prior to compression, the granules were evaluated for several tests. In all formulations, the amount of the active ingredient is equivalent to 20mg of enalapril maleate (Table 1).
Table 1 Formulation of HPMC K4M and K15 M based enalapril maleate sustained release matrices Formulation code
The angle of repose of granules was determined by the funnel method. The accurately weighed granules were taken in funnel. The height of the funnel was adjusted in such a way that the tip of the funnel just touched the apex of the heap of the granules. The granules were allowed to flow from the funnel on the surface. The diameter and height of the heap formed from the granules were measured. The angle of repose was calculated using following formula [8]: Tan Ѳ= h/r ………………………………………. Eqn.(1) Where, “h” is height of the heap and “r” is the radius of the heap of granules.
2.4. Carr’s compressibility index
The Carr’s compressibility Index was calculated from Bulk density and tapped density of the granules. A quantity of 2g of granules from each formulation, filled into a 10mL of measuring cylinder. Initial bulk volume was measured, and cylinder was allowed to tap from the height of 2.5cm. The tapped frequency was 25±2 per min to measure the tapped volume of the granules. The bulk density and tapped density were calculated by using the bulk volume and tapped volume. Carr’s compressibility index was calculated by using following formula [9]: Carr’s compressibility index (%) = [(Tapped density-Bulk density) X100]/Tapped density
……….. Eqn.(2)
2.5. Evaluation of tablets
The weight of tablets was evaluated on 20 tablets using an electronic balance. The flow properties were measured by Carr’s compressibility index, Friability was determined using
Somnath Sakore and Bhaswat Chakraborty, Int J Pharm Biomed Res 2013, 4(1), 21-26
23
6 tablets in Roche friability tester at 25rpm. Hardness of the tablets was evaluated using an ERWEKA hardness tester (Erweka GmbH, Germany). The hardness of all the formulation was between 4-6kg/cm2.
2.6. In vitro dissolution studies
In vitro drug release studies from the prepared matrix tablets were conducted using USP type II apparatus at 37°C at 50rpm. Dissolution mediums used were 900mL of 1.0N HCl and phosphate buffer of pH 6.8. The release rates from matrix tablets were conducted in HCl solution (pH 1.2) for 2h and changed to phosphate buffer (pH 6.8) for further time periods. The samples were withdrawn at desired time periods from dissolution media and the same were replaced with fresh dissolution media of respective pH. The samples were analyzed by HPLC. The amounts of drug present in the samples were calculated with the help of appropriate calibration curves constructed from reference standards. Drug dissolved at specified time periods was plotted as percent release versus time curve.
2.7. Dependent-model method (Data analysis)
In order to describe the enalapril maleate release kinetics from individual tablet formulations, the corresponding dissolution data were fitted in various kinetic dissolution models: zero order, first order, Higuchi, Korsmeyer Peppas and Hixon Crowell. When these models are used and analyzed in the preparation, the rate constant obtained from these models is an apparent rate constant. The release of drugs from the matrix tablets can be analysed by release kinetic theories [10-14].
To study the kinetics of drug release from matrix system, the release data were fitted into Zero order as cumulative amount of drug release vs. time (Eqn.3), first order as log cumulative percentage of drug remaining vs. time (Eqn.4), Higuchi model as cumulative percent drug release vs. square root of time (Eqn.5), Hixon-Crowell cube root law as cube root of percent drug remaining vs time (Eqn.6). To describe the release behavior from the polymeric systems, data were fitted according to well known exponential Korsmeyer –Peppas equation as log cumulative percent drug release vs log of time equation (Eqn.7).
(i) Zero order kinetics Qt=K0t……………………………Eqn.(3) Where, Q= Amount of drug release in time t K0 = Zero order rate constant expressed in unit of concentration /time t = Release time (ii) First order kinetics Log Q=Log Q0-kt/2.303…………Eqn.(4) Where,
Q0= is the initial concentration of drug k= is the first order rate constant t =release time (iii) Higuchi kinetics Q=kt1/2………………………...…Eqn.(5) Where, k= Release rate constant t=release time, Hence the release rate is proportional to the reciprocal of the square root of time. (iv) Hixon Crowell cube root law Q 01/3- Q t1/3=K HC t………...……Eqn.(6) Q t= the amount of drug release at time t Q 0= initial amount of drug in tablets K HC= rate constant for Hixon Crowell. (v) Korsmeyer-Peppas First 60% in vitro release data was fitted in equation of Korsmeyer et al. to determine the release behavior from controlled release polymer matrix system. The equation is also called as power law, Mt /M∞ =Kt n …………………… Eqn.(7) Where, Mt = amount of drug released at time t M∞ = amount of drug released after infinite time Mt /M∞ = fraction solute release t = release time K = kinetic constant incorporating structural and geometric characteristics of the polymer system n = diffusional exponent that characterizes the mechanism of the release of traces.
The magnitude of the release exponent “n” indicates the release mechanism (i.e. Fickian diffusion, Non Fickian, supercase II release). For matrix tablets, values of n of near 0.5 indicates Fickian diffusion controlled drug release, and an n value of near 1.0 indicates erosion or relaxational control (case II relaxational release transport, non Fickian, zero order release) [15-16].
Values of n between 0.5 and 1 regarded as an indicator of both diffusion and erosion as overall release mechanism commonly called as anomalous release mechanism [17]. The values of n and k are inversely related. A very high k values may suggest a burst drug release from the matrix [18,19].
2.8. Independent-model method (Data analysis)
The dissolution profile was statistically analyzed by using dissolution similarity factor (f2), which was calculated by the following formula:
ƒ2 = 50 × log {[1 / (1 + (Σ (Rt - Tt) 2) / n)] 1/2 × 100}…Eqn.(8) Where, n=Number of dissolution time points.st that Rt=Reference dissolution value at time t
Somnath Sakore and Bhaswat Chakraborty, Int J Pharm Biomed Res 2013, 4(1), 21-26
24
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 2 4 6
Log % Drug Re
maining
Time (h)
F1
F2
F3
F4
F5
F6
F7
F8
F9
F10
F11
Tt = Test dissolution value at time t In vitro release profile of test formulation was compared
with the desired theoretical dissolution profile. The f2 value between 50-100 ensures sameness and equivalence between two dissolution profiles.
3. RESULTS AND DISCUSSION
3.1. Physical characteristics of granules and tablets
The granules of different formulations were evaluated for angle of repose, Carr’s compressibility index etc (Table 2). The results of Angle of repose and Carr’s compressibility Index (%) ranged from 22-27 and 16-24, respectively. Which showed that granules from all the formulations having good flow property. The hardness and percentage friability ranged from 4-6kg/cm2 and 0.64-0.81% respectively.
Enalapril maleate sustained release tablets were prepared by using HPMC polymers. The release profiles of enalapril maleate sustained release tablets were plotted as Fig.1-5. The release rate of enalapril maleate mainly controlled by the hydration and swelling properties of HPMC which forms a gel layer that controls the water penetration and drug diffusion. The effect of polymer concentration on drug release could be clearly seen from the variation of the dissolution profiles. It was found that drug release from F1 and F2 composed of HPMC single polymer was no longer than 2.5h, and significantly higher drug release rate than other formulation which were prepared by using combination of HPMC K4M and HPMC K15 M. Formulations F3 to F11 shows different release rate profile up to 5h period. Formulation F3 and F8 shows less than 70% drug release in 2h. However other formulation shows more than 80% of drug release within first 2h, which is due to higher amount of drug release retarding polymers. The release rate decreased significantly and the drug release prolonged as the polymer concentration was increased. The release profiles were compared with target release profiles. The release profiles of
F1, F2, F3, F4, F5, F6, F7, and F8 were found to be out of the target release profile during first 1h. The drug release was comparatively slower than the target profile. This might be due to use of higher proportion of HPMCK4M to HPMCK15M polymers. However F9 and F10 showed the proper dissolution profiles which were required for target release profile of enalapril maleate for 5h.
Fig.1. Zero order release plot for enalapril maleate matrix tablets
Fig.2. First order release plot for enalapril maleate matrix tablets
Fig.3. Higuchi release plot for enalapril maleate matrix tablets
Somnath Sakore and Bhaswat Chakraborty, Int J Pharm Biomed Res 2013, 4(1), 21-26
25
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
‐1.5 ‐1 ‐0.5 0
Log % Release
Log time
F1
F2
F3
F4
F5
F6
F7
F8
F9
F10
F11
Fig.4. Hixon Crowell release plot for enalapril maleate matrix tablets
Fig.5. Korsmeyer Peppas release plot for enalapril maleate matrix tablets The hydration rate of HPMC depends on the nature of the
substituent like hydroxypropyl group contents. HPMC K4M and HPMC K15M are having viscosity 4000cps and 15000cps respectively, which forms a strong viscous gel in contact with aqueous media, which controls the release rate of enalapril maleate. For formulation F3, F4, F8 containing highest amount of polymer shows more controlled release of drug in both pH 1.2 and distilled water. This may be owing to a more rigid complex formed by presence of higher proportion of HPMC K4M and HPMC K15M which helped in retaining the drug in matrix and did not allow rapid diffusion of drug from matrix.
The rate and amount of drug release were decreased with increasing the amount of HPMC polymers. This polymers ability to retard the drug release rate is depends on its viscosity. The increase in polymer content decreases the total porosity therefore drug release extended for prolonged period because decreased porosity have lower lateral area. The release rate decreased significantly and drug release retarded as the polymer proportion was increased.
The drug release became sustained with increasing HPMC concentration because of poorer wetability, slower hydration and formation of gelatinous layer. Another important factor is
viscosity of the polymers which is higher as the molecular weight polymer increases. If the viscosity of the polymer increases the gel layer viscosity also increases so that the gel layer becomes resistant to diffusion and erosion. The release rate therefore decreases. Different levels of methyl and hydroxypropoxy substitution resulted in intrinsically different hydration rates, which affected the performance of the polymer in the initial stages of tablet hydration.
When glassy polymer comes into contact with water or any other medium with which it is thermodynamically compatible, the solvent penetrates into the free spaces on the surface between macromolecular chains. When enough solvent has entered into the matrix, the glass transition temperature of the polymer drops to the level of the experimental temperature (which is usually 37°C). The presence of solvent in the glassy polymer causes stresses, which are then accommodated by an increase in the radius of the gyration and end to end distance of the polymer molecules. i.e., the polymer chains get solvated. The solvent molecules move into the glassy polymer matrix. The thickness of the swollen or rubbery region increases with time in the opposite direction. This phenomenon is a characteristic for that particular polymer/solvent system.
3.3. Influence of ionic strengths on drug release
The release rate of drug is known to be affected by changing the pH of dissolution medium although HPMC hydration and gel formation is not affected by changes in pH. Bravo et al [20], studied the effect of pH on diclofenac sodium release from HPMC matrices. Study showed the release rate of diclofenac sodium was extremely slow in acidic pH, since after 2h only 1% of drug was released and showed faster drug dissolution rates at pH 6.8.
Various attempts have been made to quantify the influence of the solution containing phosphate and chloride ions at different ionic strengths on dissolution rates from HPMC SR tablets. In this study effect of phosphate buffer on drug release from HPMC matrices have been studied. No significant changes in drug dissolution in buffer compared to water medium observed for enalapril maleate.
3.4. Release kinetics
The best fit with higher correlation coefficient was found with Higuchi model which indicates that the amount of drug release is proportional to the square root of total amount of drug in tablet and solubility of drug in polymer matrix and time. (Fig.3) The rate of release can be altered by increase or decrease in the drug solubility and concentration of drug in matrix system. The drug release mechanism based upon entrance of the surrounding medium into a polymer matrix where it dissolves and leaches out the soluble drug, leaving a shell of polymer and empty pores. Depletion zone moves to the centre of the tablet as the drug released. Since the boundary between the drug matrix and the drug depleted
Somnath Sakore and Bhaswat Chakraborty, Int J Pharm Biomed Res 2013, 4(1), 21-26
26
matrix recedes with time and the thickness of the empty matrix through which drug diffuses also increases with time. As the drug passes out of a homogeneous matrix, the boundary of the drug moves to the inside by an infinitesimal distance.
Table 3 Release kinetics of enalapril maleate sustained release tablet formulations Formulation Zero
To confirm the mechanism of drug release, dissolution
data was fitted into Korsmeyer Peppas equation (Fig.5). All formulations showed good linearity. The correlation coefficient was found to be 0.988-0.994 with diffusional coefficient n values between 0.552-0.839, which indicates both mechanisms as drug diffusion and erosion, so called anomalous diffusion. (Table 3) All formulations showed Mathematical modeling of drug release from dosage form has two major benefits: first, elucidation of the underlying transport mechanism and second the possibility to predict the resulting drug release kinetics as a function of the design of the formulation. Swellable matrix tablets are activated by water, and the drug release is controlled by the interaction among the water, the polymer, and the drug. Due to the water penetration, the gel layer is exposed to continuous changes in its structure and thickness.
Similarity factor f2 analysis is used to ensure the sameness and equivalence in drug release between two profiles. Formulation F9 showed the highest value of f2 i.e. 77.22 which confirms that the release of drug from prepared formulation is similar with desired target release profile.
4. CONCLUSIONS
The sustained release tablets of enalapril maleate were prepared successfully using HPMC polymer of different viscosity. According to in vitro release studies, the release rate was decreased with increasing viscosity and amount of polymer. The results of the study clearly demonstrated that HPMC matrix tablet formulation is an effective and promising drug delivery system for once daily administration of enalapril maleate.
The analysis of the release profiles in the light of distinct kinetic models (zero order, first order, Higuchi, Korsmeyer Peppas and Hixon Crowell) led to the conclusion that, the drug release characteristics from HPMC polymer matrices follows Higuchi square root time kinetics and the mechanism of drug release was both diffusion and erosion.
REFERENCES
[1] Rajabi-Siahboomi, A.R., Jordan, M.P., Eur Phar Rev 2000, 5, 21-23. [2] Lordi, N.G., Sustained release dosage form. In: The Theory and
Practice of Industrial Pharmacy, 3rd Edn., Lea and Febiger, Philadelphia, USA, 1986.
way cross over, single dose comparative Bioavailability study in
healthy, adult, male, human, Indian subjects under fasting condition.
Various pharmacokinetic parameters as AUC0-t, AUC0- Kel, Tmax,
Cmax were computed using non-compartmental model of Win-Nonlin
Professional softwar. In vitro and In vivo data was compared using
deconvolution method and found to be highly correlative. To
demonstrate the correlation; a plot was generated with the percentage
absorbed in vivo versus the percentage released in vitro at the same
time. The r-squared value obtained by deconvolution method was
0.9789 and correlation coefficient was 0.9894 supports the extremely
significant correlation.
Pharmaceutical Sciences
International Standard Serial Number (ISSN): 2249-6793
38 Full Text Available On www.ijupls.com
1. INTRODUCTION
Drug regulatory authorities must ensure that all pharmaceuticals products, including generic drug products, conform to the same standards of quality, efficacy and safety required of innovator drug products. Therefore, regulatory frameworks must be established to prove that the generic drug products are therapeutically equivalent and interchangeable with their associated innovator’s product. Such regulatory frameworks would necessitate the proof of bioequivalence. [1, 2]
In vitro–In vivo Correlation (IVIVC) plays a key role in pharmaceutical development of dosage forms. This tool hastens the drug development process and leads to improve the product quality. It is an integral part of the immediate release as well as modified release dosage forms development process. IVIVC is a tool used in quality control for scale up and post-approval changes e.g. to improve formulations or to change production processes & ultimately to reduce the number of human studies during development of new pharmaceuticals and also to support the biowaivers.[3,4] An in vivo in vitro correlation (IVIVC) is defined as a “predictive mathematical model describing the relationship between an in vitro property of an extended release dosage forms and a relevant in vivo response, e.g. plasma drug concentration or amount of drug absorbed”. The main objective of such a mathematical model is to use data collected in vitro to predict the in vivo response without having to conduct in vivo studies. [5,6]The in vitro release data of a dosage form containing the active substance serve as characteristic in vitro property, while the in vivo performance is generally represented by the time course of the plasma concentration of the active substance. These In vitro & In vivo data are then treated scientifically to determine correlations. For oral dosage forms, the in vitro release is usually measured and considered as dissolution rate. The relationship between the in vitro and in vivocharacteristics can be expressed mathematically by a linear or nonlinear correlation. However, the plasma concentration cannot be directly correlated to the in vitro release rate; it has to be converted to the in vivo release or absorption data, either by pharmacokinetic compartment model analysis or by linear system analysis.There are four levels of IVIVC that have been described in the FDA guidance, which include levels A, B, C, and multiple C. [7,8] Level A correlation reflect the complete plasma drug level-time profile which will result from administration of the given dosage form and has a regulatory relevance .This level of correlation is the highest category of correlation and represents a point-to-point relationship between in vitro dissolution rate and in vivo input rate of the drug from the dosage form.Omeprazole belongs to a new class of anti-secretory compounds, the substituted benzimidazoles, that do not exhibit anti-cholinergic or H2 histamine antagonistic properties, but that suppress gastric acid secretion by specific inhibition of the H+/K+ ATP’ase enzyme system at the secretory surface of the gastric parietal cell. Because this enzyme system is regarded as the acid
International Standard Serial Number (ISSN): 2249-6793
39 Full Text Available On www.ijupls.com
(proton) pump within the gastric mucosa, Omeprazole has been characterized as a gastric acid-pump inhibitor, in that it blocks the final step of acid production. This effect is dose-related and leads to inhibition of both basal and stimulated acid secretion irrespective of the stimulus. [9]After oral administration, the onset of the anti-secretory effect of omeprazole occurs within one hour, with the maximum effect occurring within two hours. Inhibition of secretion is about 50% of maximum at 24 hours and the duration of inhibition lasts up to 72 hours. The anti-secretory effect thus lasts far longer than would be expected from the very short (less than one hour) plasma half-life, apparently due to prolonged binding to the parietal H+/K+ ATP’ase enzyme. When the drug is discontinued, secretory activity returns gradually, over 3 to 5 days. The inhibitory effect of omeprazole on acid secretion increases with repeated once-daily dosing, reaching a plateau after four days. Results from numerous studies of the anti-secretory effect of multiple doses of 20 mg and 40 mg of omeprazole in normal volunteers and patients are shown below. The "max" value represents determinations at a time of maximum effect (2-6 hours after dosing), while "min" values are those 24 hours after the last dose of omeprazole.[9, 10]
Omeprazole Delayed-Release Capsules contain an enteric-coated granule formulation of omeprazole (because omeprazole is acid-labile), so that absorption of omeprazole begins only after the granules leave the stomach. Absolute bioavailability (compared to intravenousadministration) is about 30–40% at doses of 20-40 mg, due in large part to pre-systemic metabolism. In healthy subjects the plasma half-life is 0.5–1 hour, and the total body clearance is 500-600 mL/min. Protein binding is approximately 95%. The bioavailability of omeprazole increases slightly upon repeated administration of Delayed-Release Capsules.
2. MATERIALS AND METHODS:
2.1 Materials
All materials used for analysis are of analytical grade. The test product for In vivo study used was Omeprazole Capsules 20 mg (Omeprazole) manufactured by Cadila Pharmaceuticals Ltd, Dholka, India. Reference Product used was Losec Capsules 20 mg (Omeprazole) manufactured by Laboratorio Tau, S.A. Madrid, Spain.
2.2 In vitro Evaluation
The dissolution of Omeprazole Capsule was carried out using USP Type II Dissolution apparatus. Taking 900 ml of Dissolution medium into each of the six different vessels, oneOmeprazole capsule was dropped into each of the Vessels and the apparatus was operated for exactly two hours. At the end of two hours 0.1 N HCL was decanted and 900 ml of pH 6.8 Phosphate buffer was transferred to the vessels at 37ºC ± 0.5ºC and rotated at a speed of 100 rpm. The solution was withdrawn at an interval of 2 min for the first 20 min then at an interval of10 min for 1 hour and sink conditions were maintained by constantly replenishing with the same volume of fresh buffer solution. The sample is withdrawn from the zone midway between
International Standard Serial Number (ISSN): 2249-6793
40 Full Text Available On www.ijupls.com
the surface of the medium and top of the rotating basket not less than 1 cm from the vessel wall. The solution is then filtered through the what- man filter paper o.1 discarding the first few mL of the filtrate. Immediately 5 ml of this sample was taken to test tubes containing 1 mL of 0.25 N Sodium hydroxide.
Analysis of Omeprazole was performed using a validated Ultra Performance liquid chromatographic (UPLC) assay.
The sample preparation was injected into the Chromatograph. Then the sample was analyzed using Variable wavelength, UV Detector at 302 nm using the same buffer solution of pH 6.8 blank. The Chromatograms are recorded and the responses for the principle peak are was measured.
2.3 In vivo Absorption
2.3.1 Title:
A randomized, two-treatment, two-period, two-sequence, single-dose, two-way crossover comparative bioavailability study on Omeprazole 20 mg (Containing Omeprazole HCl 20 mg) Capsules (Cadila Pharmaceuticals Ltd, India) with Losec 20 mg (Containing Omeprazole HCl 20 mg) Capsules (Laboratorio Tau, S.A. Madrid, Spain) in 37 healthy, adult, male, human Indian subjects under fasting condition.
2.3.2 Screen Procedure
During screening procedure Demography data, standard physical examination with Vital signs, Clinical laboratory tests on blood and urine samples, Electrocardiogram (ECG) and Chest X-raywere done.
2.3.3 Study Design
The protocol was approved by the “Ethique”- Independent Ethics committee. The study was carried out in accordance with the principles of the Declaration of Helsinki and its amendments(World Medical Association, 2008) and the International Conference on Harmonisation Guideline for Good Clinical Practice (59th WMA General Assembly, Seoul, October 2008)
The study was a randomized, open-level, balanced, two-treatment, two-sequence, two-way cross over, single dose comparative Bioavailability study in healthy, adult, male, human, Indian subjects under fasting condition with at least 7 days wash-out period between each administration. Each subject was given one capsule of either product i.e. test or reference after an overnight fast for 10 hours with 200 ml of drinking water at room temperature. The subjects received each treatment once according to the randomization schedule.
International Standard Serial Number (ISSN): 2249-6793
41 Full Text Available On www.ijupls.com
2.3.4 Administration: Single dose of 20 mg capsule of Omeprazole (Test) or Losec 20 mg Capsules (Reference)products was administered along with 200 mL of drinking water after an over night fasting of at least 10 hours in each Period.
2.3.5 Study endpoints:The endpoints was 90% confidence intervals of the ratio of least-squares means of the
Pharmacokinetic parameters AUC0-t, AUC0- and Cmax of the Omeprazole 20 mg Capsules (Test) and Losec 20 mg Capsules (Reference) products formulation for bioequivalence assessment.
2.3.6 Blood Sampling:5 ml blood samples were taken from a cubical vein into heparinized tubes at the following time points: 0 hr prior to administration of dose and at 0.333, 0.667 ,1.0, 1.336, 1.667, 2, 2.333, 2.667, 3.0, 3.5, 4.0, 5.0, 7.0, 9.0, 12.0, 16.0, 24.0 hours volume of blood drawn including 10 mL for screening, 5 mL for post safety assessment and 18 mL of ‘ discarded ’ anti coagulant mixed blood prior to each sampling from 0.0 hours to 24.0 hour samples during both Periods, will not exceed 213.0 mL.
2.3.7 Bio-analysis of Plasma sample:The Plasma sample was then analyzed to find out the Omeprazole in plasma concentrations by a validated UPLC method at Cadila Pharmaceuticals Ltd. After receiving the plasma concentration from the Bio analytical lab we carried out data analysis in Win-Nonlin software to get the Cmax,
AUC 0-t, AUC 0- and Kel.
2.3.8 Statistical AnalysisStatistical analysis was performed on the data obtained from subjects (completing both the periods) using WinNonlin software. Linear regression analysis, regression correlation was performed in NCSS, WinNonlin and Microsoft Excel Sheet.
3. RESULTS AND DISCUSSION
3.1 Confidence IntervalConfidence Interval was calculated for log-transformed Cmax, AUC0-t and AUC0-inf. The confidence interval was expressed as a percentage relative to the LSM of the reference treatments. To be considered as bioequivalent the 90% confidence intervals of these parameters for Omeprazole should be in the interval 80-125% for the log- transformed data of AUC0-t and AUC0-∞. For Cmax confidence intervals should be in the interval of 75-133% for the log –transformed data.The 90% confidence Interval Omeprazole was calculated and it showed that the Cmax having lower limit (%) 76.30 and upper limit 97.40. The Lower limit (%) and the Upper limit (%) of AUC0-t was 89.22 and 117.54 respectively.
42
The lower and upper limit of 90% confidence interval for AUC0respectively. Thus we can say that the drug is bioequivalent as the data are within the ratio of 80125%.
3.2 In vitro Dissolution: The mean % dissolved is calculated on the basis of min, 90.5% of the Omeprazole drug had dissolved. As observed that 90.5% dissolved within the first 18 min, we separated the time points in the increments of 2 min for the first 20 min followed by the increment of 10 min till 60 min. It was observed that 94.7 % of Omeprazole dissolved within 60 min.
Percent dissolved versus in vitrocurve as shown below in Figure 1
Fig. 1. In vitro
The above figure shows that 93% of Omeprazole capsule dissolved in 20 min at pH 6.8.
The measure or units of time for achieve uniformity of time unit, carried out in WinNonlin software.
3.3 In vivo absorption: After Bioanalytical study is over data is worked on by biostatistics department where data analysis is performed in PK/PD/NCA Analysis Wizard of WinNonlin for determination of Cmax, Kel, AUC0-t and AUC0-∞.
The Omeprazole molecule shows Cmax of 381.484 ± 48.737, elimination rate constant (Kel) of
0.564 ± 0.054, AUC0-t around 1306.932 ± 328.105 a
International Standard Serial Number (ISSN): 2249
Full Text Available On
upper limit of 90% confidence interval for AUC0-∞ was 96.84 and 122.60 respectively. Thus we can say that the drug is bioequivalent as the data are within the ratio of 80
The mean % dissolved is calculated on the basis of time and it showed that within the first 18 min, 90.5% of the Omeprazole drug had dissolved. As observed that 90.5% dissolved within the first 18 min, we separated the time points in the increments of 2 min for the first 20 min followed
10 min till 60 min. It was observed that 94.7 % of Omeprazole dissolved
in vitro dissolution time (in min) plotted generates a dissolution profile 1
In vitro Percent dissolved Vs. Time plot
The above figure shows that 93% of Omeprazole capsule dissolved in 20 min at pH 6.8.
The measure or units of time for in vitro and in vivo are minutes and hours, respectively. achieve uniformity of time unit, in vitro time unit was converted to hours and deconvolution was carried out in WinNonlin software.
After Bioanalytical study is over data is worked on by biostatistics department where data nalysis is performed in PK/PD/NCA Analysis Wizard of WinNonlin for determination of
∞.
The Omeprazole molecule shows Cmax of 381.484 ± 48.737, elimination rate constant (Kel) of
t around 1306.932 ± 328.105 and AUC0- of 1622.962 ± 414.656.
Serial Number (ISSN): 2249-6793
Full Text Available On www.ijupls.com
∞ was 96.84 and 122.60 respectively. Thus we can say that the drug is bioequivalent as the data are within the ratio of 80-
time and it showed that within the first 18 min, 90.5% of the Omeprazole drug had dissolved. As observed that 90.5% dissolved within the first 18 min, we separated the time points in the increments of 2 min for the first 20 min followed
10 min till 60 min. It was observed that 94.7 % of Omeprazole dissolved
dissolution time (in min) plotted generates a dissolution profile
The above figure shows that 93% of Omeprazole capsule dissolved in 20 min at pH 6.8.
are minutes and hours, respectively. So to time unit was converted to hours and deconvolution was
After Bioanalytical study is over data is worked on by biostatistics department where data nalysis is performed in PK/PD/NCA Analysis Wizard of WinNonlin for determination of
The Omeprazole molecule shows Cmax of 381.484 ± 48.737, elimination rate constant (Kel) of
of 1622.962 ± 414.656.
International Standard Serial Number (ISSN): 2249-6793
43 Full Text Available On www.ijupls.com
Table 1 summarizes the Pharmacokinetic parameters of the Omeprazole molecule.
Cmax 381.484 ± 48.737Kel 0.564 ± 0.054
AUC0-t 1306.932 ± 328.105
AUC0- 1622.962 ± 414.656
Table 1. Summary of Pharmacokinetic parameters
Mean plasma concentration of the 37 subjects was determined. Mean plasma concentration was plotted against time to produce mean plasma concentration time graph. The lower limit of Quantification (LLQ) was established at 20.17 ng/mL for Omeprazole in Human Plasma.
3.3.1 Mean plasma concentration of test drug In vivo mean plasma concentration data were obtained up to 24 hrs, after administration of Omeprazole 20 mg capsule to 37 healthy human volunteers and was subjected to deconvolution analysis to obtain percentage in vivo absorbed profiles. Mean plasma concentration of test drug shown in Figure 2
Fig.2. Mean Plasma drug Concentration vs. Time
3.4 Development and evaluation of Level A IVIVC Model:A preliminary inspection of the % in vivo absorption time profile indicated that in vivoabsorption of Omeprazole occurred for 24 hrs for some subjects after dose administration. Since the in vitro dissolution data was available only for 1 hr, and in vivo absorption data for 24 hrs, a time scaling factor (i.e., intensity factor) was calculated using the formula:-
I = time for 50% absorption in vivo / time for 50% dissolution in vitro The obtained time scaling factor, I, was then used to compare the in vivo and in vitro data. From the in vivo deconvoluted profile we found that the 50% absorption was between 0.72 and 0.96 hrs. For accurate
Plasma concentration
1.0
10.0
100.0
1000.0
0 4 8 12 16 20 24
Time in Hours
Cp (n
g/ml)
International Standard Serial Number (ISSN): 2249-6793
44 Full Text Available On www.ijupls.com
determination of time points of 50% in vivo absorption we considered 0.84 hr, average of 0.72 and 0.96 hrs. In vitro 50% dissolution was observed at 0.32 hr. Thus by applying the above formula an intensity factor (I) = 2.625 was obtained.
Intensity factor was then applied to convert the time difference between in vitro and in vivo data from minutes to hours. In vitro–in vivo concentration was subsequently calculated for each transformed time points.The in vitro % dissolved and in vivo % absorbed data considered for correlation is given in table 2:
Table 2. In vivo % absorbed vs. In vitro % dissolved
3.4.1 Correlation calculationOn entering in vitro and in vivo data to the NCSS (statistical and power analysis software 2007) a Linear Regression plot section was obtained along with summary output. The output results are shown in Table 3 and the linear regression plot is given in figure 3
International Standard Serial Number (ISSN): 2249-6793
45 Full Text Available On www.ijupls.com
Fig.3. The linear regression plot of % absorbed and % dissolved.
3.5 Summary statement:The equation of the straight line relating C1 in vivo absorbed at time t (%) and C2 in vitrodissolved at time t/I (%) was estimated as: C1 in vivo absorbed at time t (%) = (-0.0522) + (1.0923) C2 in vitro dissolved at time t/I (%) using the 9 observations in this dataset. The y-intercept, the estimated value of C1 in vivo absorbed at time t (%) when C2 in vitro dissolved at time t/I (%) was zero, was -0.0522 with a standard error of 0.0424. The slope, the estimated change in C1 in vivo absorbed at time t (%) per unit change in C2 in vitro dissolved at time t/I (%), was 1.0923 with a standard error of 0.0606. The value of R-Squared, the proportion of the variation in C1 in vivo absorbed at time t (%) that can be accounted for by variation in C2 in vitro dissolved at time t/I (%), was 0.9789. The correlation between C1 In vivo absorbed at time t (%) and C2 in vitro dissolved at time t/I (%) was 0.9894.
A significance test that the slope was zero resulted in a t-value of 18.0161. The significance level of this t-test was far less than 0.05. Since 0.00 < 0.05, the hypothesis that the slope was zero is rejected.
The estimated slope was 1.0923. The lower limit of the 95% confidence interval for the slope was 0.9490 and the upper limit was 1.2357. The estimated intercept was -0.0522. The lower limit of 95% confidence interval for the intercept was -0.1524 and the upper limit was 0.0480.
3.6 Calculation on Excel Sheet:On inputting the in vitro and in vivo data to the Excel sheet, a Linear Regression plot was obtained along with the summary output. The output results shows in Table 4:
C1 In vivo absorbed at time t (%) vs C2 Invitro dissolved at time t/I (%)
C2 Invitro dissolved at time t/I (%)
C1
In v
ivo
abso
rbed
at t
ime
t (%
)
International Standard Serial Number (ISSN): 2249-6793
46 Full Text Available On www.ijupls.com
The results obtained from excel spread sheet were reconfirmed using NCSS module/tool of Win stat software. Results obtained from both the methods were given in the following table 5:
Software Used R-squared Correlation CoefficientNCSS 0.9789 0.9894
Excel spread sheet 0.9788 0.9893
Table 5 Correlation of NCSS and Excel spread sheet results
In a linear correlation, in vitro dissolution and in vivo input curves may be directly super imposable or may be made to be super imposable by the use of appropriate scaling factor (time corrections). Time scaling factor should be the same for all formulations and different time scales for each formulation indicate absence of an IVIVC.
In cases where the dissolution rate depends on the experimental factors mentioned above the deconvoluted plasma concentration-time curves constructed following administration of batches of product with different dissolution rates (at least two formulations having significantly different behavior), are correlated with dissolution data obtained under the same dissolution condition. If there is no one-to-one correlation other levels of correlation can be evaluated.
The in vitro dissolution methodology should be able to adequately discriminate between the study formulations. Once a system with most suitable discrimination is developed, dissolution conditions should be the same for all formulations tested in the bio-study for development of the correlation.
During the early stages of correlation development, dissolution conditions may be altered to attempt to develop a one-to-one correlation between the in vitro dissolution profile and the in vivo dissolution profile.
An established correlation is valid only for a specific type of pharmaceutical dosage form (tablets, gelatin capsules, etc.) with a particular release mechanism (matrix, osmotic system, etc.) and particular main excipients and additives. The correlation is true and predictive only if modifications of this dosage form remain within certain limits, consistent with the release mechanism and excipients involved in it.
Extrapolation of IVIVC established in healthy subjects to patients has to be taken into account. Drugs are often taken just before, with or after meal. All these factors may increase variability. A posterior correlation might be established using the patients' data only to increase the knowledge of the drug.
The release rates, as measured by percent dissolved, for each formulation studied, should differ adequately (e.g., by 10%).
International Standard Serial Number (ISSN): 2249-6793
47 Full Text Available On www.ijupls.com
4. CONCLUSIONThe present study shows a good correlation between in vivo and in vitro PK profiles of the formulation used as the test drug in the study. In vitro and In vivo data was compared using deconvolution method and found to be highly correlative.
The r-squared value obtained by deconvolution method was 0.9789 the correlation coefficient value obtained was 0.9894 supports the extremely significant correlation.
In vitro-In vivo Correlation is scientifically accurate tool to predict and to design release pattern of a formulation in vivo. These can be utilized in designing of a generic formulation in order to make it bio-equivalent to the innovator. This implies that it can be effectively utilized for the formulation development of a bio-batch of generic formulation.
The established IVIVC was of level ‘A’ which confirms the accuracy of this in vitro model in simulating in vivo concentration. This type of correlation is important since it represents point-to-point relationship between in vitro dissolution and in vivo input rate of the drug from the dosage form. It was shown to be sensitive, effective and reliable in predicting in vivo performance of the drug formulation.
ACKNOWLEDGMENTWe gratefully acknowledge Mrs. Sangita Sakore & Mrs. Darshini Desai for their valuable inputsduring manuscript preparation.
REFERENCES
1. Leeson, L.J., Drug Information Journal 1995, 29, 903-915.2. Modi, N.B., Lam, A., Lindemulder, E., Wang, B., Gupta, S.K., Biopharm Drug Dispos
2001, 21,321-326. 3. Sirisuth, N., Eddington, D.N., Int J Generic Drugs 1999, 3(6).4. Chilukuri, D.M., Sunkara, G., Drug Delivery Technology 2003,3(4).5. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulations6. Uppoor, V.R.S., J Control Rel 2001, 72,127-132.7. Jaber, E., J Pharm Pharmaceut Sci (www. cspsCanada.org) 2006, 9 (2),169-189.8. Qureshi, S.A., The Open Drug Delivery Journal 2010, 4, 38-47.9. Available from: URL: http://www.micromedex.com10. Available from: URL: http://www.rxlist.com
Research Article Open Access
Sakore and Chakraborty, J Bioequiv Availab 2011, S3http://dx.doi.org/10.4172/jbb.S3-001
Review Article Open Access
Bioequivalence & Bioavailability
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
Abbreviations: IVIVC: In Vitro In Vivo correlation; FDA: Food and Drug Administration; AUC: Area Under Curve; MDT vitro: Mean in vitro Dissolution Time; MRT: Mean Residence Time; BCS: Biopharmaceutical Classification System
Introduction In vitro in vivo correlations (IVIVC) play a key role in the drug
development and optimization of formulation which is certainly a time consuming and expensive process. Formulation optimization requires alteration in formulation, composition, equipments, batch sizes and manufacturing process. If such types of one or more changes are applied to the formulation, the in vivo bioequivalence studies in human may required to be done to prove the similarity of the new formulation which will not only increase the burden of carrying out a number of bioequivalence studies but eventually increase the cost of the optimization process and ultimately marketing of the new formulation. To overcome these problems it is desirable to develop in vitro tests that reflect can bioavailability data. IVIVC can be used in the development of new pharmaceuticals to reduce the number of human studies during the formulation development. Thus, the main objective of an IVIVC is to serve as a surrogate for in vivo bioavailability and to support biowaivers.
IVIVC is a mathematical relationship between in vitro properties of a dosage form with its in vivo performance. The In vitro release data of a dosage form containing the active substance serve as characteristic in vitro property, while the In vivo performance is generally represented by the time course of the plasma concentration of the active substance. These In vitro & In vivo data are then treated scientifically to determine correlations. For oral dosage forms, the in vitro release is usually measured and considered as dissolution rate. The relationship between the in vitro and in vivo characteristics can be expressed mathematically by a linear or nonlinear correlation. However, the plasma concentration cannot be directly correlated to the in vitro release rate; it has to be converted to the in vivo release or absorption data, either by pharmacokinetic compartment model analysis or by linear system analysis [1].
IVIVC definitions
United state pharmacopoeia (USP) definition of IVIVC
The establishment of a rational relationship between a biological property, or a parameter derived from a biological property produced by a dosage form, and a physicochemical property or characteristic of the same dosage form [2].
Food and drug administration (FDA) definition of IVIVC
An In-vitro in-vivo correlation (IVIVC) has been defined by the Food and Drug Administration (FDA) as “a predictive mathematical model describing the relationship between an in-vitro property of a dosage form and an in-vivo response”.
Generally, the In vitro property is the rate or extent of drug dissolution or release while the In vivo response is the plasma drug concentration or amount of drug absorbed. Practically, the purpose of IVIVC is to use drug dissolution results from two or more products to predict similarity or dissimilarity of expected plasma drug concentration (profiles). Before one considers relating in vitro results to in vivo, one has to establish as to how one will establish similarity or dissimilarity of in vivo response i.e. plasma drug concentration profiles. The methodology of establishing similarity or dissimilarity of plasma drug concentrations profile is commonly known as bioequivalence testing. There are very well established guidances and standards available for establishing bioequivalence between drug profiles and products [3].
Received October 06, 2011; Accepted December 31, 2011; Published January 02, 2012
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
In Vitro–In Vivo Correlation (IVIVC) plays a key role in pharmaceutical development of dosage forms. This tool hastens the drug development process and leads to improve the product quality. It is an integral part of the immediate release as well as modified release dosage forms development process. IVIVC is a tool used in quality control for scale up and post-approval changes e.g. to improve formulations or to change production processes & ultimately to reduce the number of human studies during development of new pharmaceuticals and also to support the biowaivers. This article provides the information on the various guidances, evaluation, validation, BCS application in IVIVC, levels of IVIVC, applications of IVIVC in mapping, novel drug delivery systems and prediction of IVIVC from the dissolution profile characteristics of product.
In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug DevelopmentSomnath Sakore* and Bhaswat Chakraborty
Cadila Pharmaceuticals Ltd, Research & Development, 1389, Trasad Road, Dholka, Ahmedabad 387810, Gujarat, India
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 2 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
Purpose of IVIVCReduction of regulatory burden
IVIVC can be used as substitute for additional in vivo experiments, under certain conditions.
Optimization of formulation
The optimization of formulations may require changes in the composition, manufacturing process, equipment, and batch sizes. In order to prove the validity of a new formulation, which is bioequivalent with a target formulation, a considerable amount of efforts is required to study bioequivalence (BE) /bioavailability (BA).
Justification for “therapeutic’ product quality
IVIVC is often adequate for justification of therapeutically meaningful release specifications of the formulation.
Scale up post approval changes (Time and cost saving during the product development)
Validated IVIVC is also serves as justification for a biowaivers in filings of a Level 3 (or Type II in Europe) variation, either during scale-up or post approval, as well as for line extensions (e.g., different dosage strengths).
IVIVC as surrogate for in vivo bioequivalence and to support biowaivers (Time and cost saving)
The main purpose of an IVIVC model to utilize in vitro dissolution profiles as a surrogate for in vivo bioequivalence and to support biowaivers.
Levels of IvivcThere are four levels of IVIVC that have been described in the FDA
guidance, which include levels A, B, C, and multiple C [4]. The concept of correlation level is based upon the ability of the correlation to reflect the complete plasma drug level-time profile which will result from administration of the given dosage form.
Level A correlation
An IVIVC that correlates the entire in vitro and in vivo profiles has regulatory relevance and is called a Level A Correlation .This level of correlation is the highest category of correlation and represents a point-to-point relationship between in vitro dissolution rate and in vivo input rate of the drug from the dosage form [3,5].
Level A correlation is the most preferred to achieve; since it allows bio waiver for changes in manufacturing site, raw material suppliers, and minor changes in formulation. The purpose of Level A correlation is to define a direct relationship between in vivo data such that measurement of in vitro dissolution rate alone is sufficient to determine the biopharmaceutical rate of the dosage form.
Level B correlation
A level B IVIVC is based on the principles of statistical moment analysis. In this level of correlation, the mean in vitro dissolution time (MDT vitro) of the product is compared to either mean in vivo residence time (MRT) or the mean in vivo dissolution time (MDTvivo). MRT, MDTvitro and MDTvivo will be defined throughout the manuscript where appropriate [6]. A level B correlation does not uniquely reflect the actual in vivo plasma level curves, also in vitro data from such a
correlation could not be used to justify the extremes of quality control standards hence it is least useful for regulatory purposes [5].
Level C correlation
Level C correlation relates one dissolution time point (t50%, t90%, etc.) to one mean pharmacokinetic parameter such as AUC, tmax or Cmax. This is the weakest level of correlation as partial relationship between absorption and dissolution is established since it does not reflect the complete shape of plasma drug concentration time curve, which is the critical factor that defines the performance of a drug product.
Due to its obvious limitations, the usefulness of a Level C correlation is limited in predicting in vivo drug performance. In the early stages of formulation development Level C correlations can be useful when pilot formulations are being selected while waiver of an in vivo bioequivalance study (biowaiver) is generally not possible [5,6].
Multiple level C correlations
This level refers to the relationship between one or more pharmacokinetic parameters of interest (Cmax, AUC, or any other suitable parameters) and amount of drug dissolved at several time point of dissolution profile. Multiple point level C correlation may be used to justify a biowaivers provided that the correlation has been established over the entire dissolution profile with one or more pharmacokinetic parameters of interest. A multiple Level C correlation should be based on at least three dissolution time points covering the early, middle, and late stages of the dissolution profile. The development of a level A correlation is also likely, when multiple level C correlation is achieved at each time point at the same parameter such that the effect on the in vivo performance of any change in dissolution can be assessed [5,6].
Level D correlation
It is not a formal correlation but it is a semi quantitative (qualitative analysis) and rank order correlation and is not considered useful for regulatory purpose but can be serves as an aid in the development of a formulation or processing procedure [5,7] (Table 1).
IVIVC Models The relationship of observed drug concentration-time profiles
following administration of a tablet/capsule with drug dissolution and pharmacokinetics may be described graphically as shown in Figure 1.
It is generally assumed that absorption and dissolution have a
Level In vitro In vivo
A Dissolution curve Input (absorption) curves
B Statistical moments: meandissolution time (MDT)
Statistical moments: meanresidence time (MRT), mean absorption time (MAT), etc
C
Disintegration time, time to have 10%, 50%, 90% dissolved, dissolution rate,dissolution efficiency (DE)
Maximum observed concentration (Cmax), observed at time (Tmax), absorption constant (Ka), Time to have 10, 50, 90% absorbed, AUC(total or cumulative)
A: one-to-one relationship between in vitro and in vivo data, e.g., in vitro dissolution vs. in vivo absorptionB: correlation based on statistical moments, e.g., in vitro MDT vs. in vivo MRT or MATC: point-to-point relationship between a dissolution and a pharmacokinetic parameter, e.g., in vitro T50% vs. in vivo T max, Multiple C: relationship between one or several PK parameters and amount dissolved at several time points.
Table 1: Various parameters used in IVIVC depending on the level.
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 3 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
linear relationship hence dissolution and absorption characteristics of a drug are commonly shown interchangeably. Thus from Figure 2, it is to be noted that one should be able to establish drug profiles with dissolution profiles combined with the pharmacokinetic characteristics of the drug as describe in the example above. This process of obtaining a drug profile from dissolution results is known as convolution. The opposite of this, i.e., obtaining or extracting a dissolution profile from a blood profile, is known as deconvolution Figure 2.
Convolution model
In the development of convolution model the drug concentration-time profiles obtained from dissolution results may be evaluated using criteria for in vivo bioavailability/ bioequivalence assessment, based on Cmax and AUC parameters.
In mathematical terminology, dissolution results become an input function and plasma concentrations (e.g. from IV) become a weighting factor or function resulting in an output function representing plasma concentrations for the solid oral product.
Implementation of convolution-based method involves the production of a user-written subroutine for the NONMEM
software
package, has shown that a convolution-based method based on that of O’Hara et al. [9] produces superior results. Using the NONMEM package, a nonlinear mixed effects model can be fitted to the data with a time-scale model linking the in vitro and in vivo components [10].
It has been demonstrates that the convolution based and differential equation based models can be mathematically equivalent [11]. Software has been developed which implements a differential equation based approach. This method utilises existing NONMEM libraries and is an accurate method of modeling which is far more straightforward for users to implement. This research shows that, when the system being modeled is linear, the use of differential equations will produce results that are practically identical to those obtained from the convolution method.
But is a task that can be time consuming and complex [12]. As a result, this methodology, despite its advantages over the deconvolution-based approach, is not in widespread use.
Mathematically we can write the convolution as:
0( ) ( ) ( ) ( ) ( )
tC t C t F t C F t dδ δ τ τ τ= = −∫ (1)
Where, C(t) = Plasma drug concentrations after oral dose
Cδ(t) = Plasma concentrations after an IV dose or a dose of oral solution
Upon taking the derivative of C(t) with respect to time:
0( ) ( ) ( ) (0) ( )
tC t C t F t C F dδ δ τ τ= + ∫
(2)
When Cδ(0) = 0
( ) * ( )C t F tδ (3)
Advantages of this approach relative to deconvolution-based IVIVC approaches include the following: The relationship between measured quantities (in vitro release and plasma drug concentrations) is modeled directly in a single stage rather than via an indirect two stage approach. The model directly predicts the plasma concentration time course. As a result the modeling focuses on the ability to predict measured quantities (not indirectly calculated quantities such as the cumulative amount absorbed). The results are more readily interpreted in terms of the effect of in vitro release on conventional bioequivalence metrics [5].
Deconvolution model
Deconvolution is a numerical method used to estimate the time course of drug input using a mathematical model based on the convolution integral.
The deconvolution technique requires the comparison of in vivo dissolution profile which can be obtained from the blood profiles with in vitro dissolution profiles. The observed fraction of the drug absorbed is estimated based on the Wagner-Nelson method. IV, IR or oral solution are attempted as the reference. Then, the pharmacokinetic parameters are estimated using a nonlinear regression tool or obtained from literatures reported previously. Based on the IVIVC model, the predicted fraction of the drug absorbed is calculated from the observed fraction of the drug dissolved. It is the most commonly cited and used method in the literature [10]. However this approach is conceptually difficult to use. For example: (1) Extracting in vivo dissolution data from a blood profile often requires elaborate mathematical and computing expertise. Fitting mathematical models are usually subjective in nature, and thus do not provide an unbiased approach in evaluating in vivo dissolution results/profiles. Even when in vivo dissolution curves are obtained there is no parameter available with associated statistical confidence and physiological relevance,
Figure 1: A typical drug concentration (in blood) – time profile reflecting the fate of a drug in the human body following an oral dose (tablet/capsule).
Cmax
Con
cent
ratio
n
Tmax Time
Figure 2: Schematic representation of deconvolution and convolution processes. Convolution is the process of combined effect of dissolution and elimination of drug in the body to reflect blood drug concentration-time profile (right to left). On the other hand, extracting dissolution profiles from blood drug concentration-time profile is known as the deconvolution process (left to right) [8].
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 4 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
which would be used to establish the similarity or dissimilarity of the curves [13]. A more serious limitation of this approach is that it often requires multiple products having potentially different in vivo release characteristics (slow, medium, fast). These products are then used to define experimental conditions (medium, apparatus etc.) for an appropriate dissolution test to reflect their in vivo behavior. This approach is more suited for method/apparatus development as release characteristics of test products are to be known (slow, medium, fast) rather product evaluation [14].
Differential equation based approach
Another approach, has been proposed is based on systems of differential equations [15]. The use of a differential equation based model could also allow for the possibility of accurately modelling non-linear systems and further investigation is being carried out into the case where the drug is eliminated by a nonlinear, saturable process. The convolution and deconvolution methods assume that the system being modelled is linear but, in practice, this is not always the case. Work to date has shown that the convolution-based method is superior, but when presented with nonlinear data even this approach will fail. It is expected that, in the nonlinear case, the use of a differential equation based method would lead to more accurate predictions of plasma concentration.
The incorporation of time-scaling in the PDx-IVIVC equation allows this parameter to be estimated directly from the in vivoand vitro release data. As a result, the predictability of an IVIVC model can be evaluated over the entire in vivo time course.Internal predictability of the IVIVC model was assessed using convolution.PDx-IVIVC Model Equation:
1 2 1 2
0, t 0.( )
( ), t 0.vivovitro
x ta a x b b t
≥= + − + ≥
(4)
For orally administered drugs, IVIVC is expected for highly permeable drugs, or drugs under dissolution rate-limiting conditions, which is supported by the Biopharmaceutical Classification System (BCS) [6,16]. For extended-release formulations following oral administration, modified BCS containing the three classes (high aqueous solubility, low aqueous solubility, and variable solubility) is proposed [17].
IVIVC Development Any well designed and scientifically sound approach would be
acceptable for establishment of an IVIVC. For the development and validation of a IVIVC model, two or three different formulations with different release rates, such as slow, medium, fast should be studied In vitro and In vivo [6].
A number of products with different release rates are usually manufactured by varying the primary rate controlling variable (e.g., the amount of excipient, or a property of the drug substance such as particle size) but within the same qualitative formulation. To develop a discriminative in vitro dissolution method, several method variables together with formulation variables are studied, e.g., different pH values, dissolution apparatuses and agitation speeds. Essentially at this stage a level A correlation is assumed and the formulation strategy is initiated with the objective of achieving the target in vitro profile.Development of a level A IVIVC model includes several steps.
In context of understanding the applications of IVIVR throughout
the product development cycle, it is useful to become familiar with the following terms as they relate to a typical product development cycle for oral extended-release product [5].
An assumed IVIVC is the one that provides the initial guidance and direction for the early formulation development activity. Thus, during step 1 and with a particular desired product, appropriate in vitro targets are established to meet the desired in vivo profile specification. This assumed model can be the subject of revision as prototype formulations are developed and characterized in vivo, with the results often leading to a further cycle of prototype formulation and In vivo characterization.
Out of this product development cycle and In vivo characterization and, of course, extensive in vitro testing is often developed what can be referred to as retrospective IVIVC.
The defined formulation that meets the in vivo specification is employed for Stage 2. At this stage based on a greater understanding and appreciation of defined formulation and its characteristics, a prospective IVIVC is established through a well defined prospective IVIVC study [18,5].
Step 1
In the first step, the In vivo input profile of the drug from different formulations is calculated from drug concentrations in plasma (Figure 3). The target In vivo profile needs to be first established, based on, if possible, pharmacokinetic/pharmacodynamic models. Certainly, step 1 activity should culminate in a pilot PK study. This is typically a four or five-arm cross-over study. The size of this pilot pharmacokinetic study will vary depending on the inherent variability of the drug itself but typically range from 6 to 10 subjects [5]. The results of this pilot PK study provide the basis for establishing what has been referred to as a retrospective IVIVC .To separate drug input from drug distribution and elimination, model-dependent approaches, such as Wagner-Nelson and Loo-Riegelman, or model independent procedures, based on numerical deconvolution, may be utilised [19,20,21]. In step 1, the parameters that describe drug input rate, drug distribution and/or elimination are determined. In the model dependent approaches, the distribution and elimination rate constants describe pharmacokinetics after absorption. In the numerical deconvolution approach, the drug unit impulse response function describes distribution and elimination phases, respectively. The physicochemical characteristics of the drug substance itself, in relevance to formulation approach and dissolution at distal sites in the gastro-intestinal tract, need to be taken into account. Based on this information a priori in vitro methods are usually then developed and a theoretical in vitro target is established, which should achieve the desired absorption profile [5,18].
Step 2
By this phase of the development process, a defined formulation that meets the In vivo targets has been achieved. Extensive In vitro characterization is again performed across pH, media and apparatus, along with the consideration of results of stage 1. This leads to execution of a prospective IVIVC study. The IVIVC is developed and defined after an analysis of the result of that prospective in vivo study. It can often involved further in vitro method development in the context of the observed results, but clearly with the objective of establishing a definitive IVIVC. In this step, the relationship between
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 5 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
Step1;
Step3;
Step 2: IVIVC
% absorbed
%Dissolved
Prospective
Time (hr)
Time (hr)
% Released
In vitro DissolutionRelease rate:
Release rate:
Release rate:
Release rate:
Fast
Fast
Fast
Fast
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Assumed IVIVC
Retrospectiv IVIVC Defined formulation
DECONVOLUTION
IVIVC
IVIVC
In vivo absorption
Absorbed
Time
Comcentration
(mg/ml)
VALIDATION
Predicted Plasma Levels
Concentration
(ng/ml)
Time
observed plasma LeveiS
CONVOLUTION
Figure 3: Development of IVIVC with validation.
in vitro dissolution and the in vivo drug input profile is determined (Figure 3). Either a linear or nonlinear relationship may be found. In some cases, time-scaling of in vitro data must be used, because In vitro dissolution and In vivo input may follow the same kinetics but still have different time-scales [6,22]. The time-scaling factor should be the same for all formulations if an IVIVC at level A is sought. During the early stages of correlation development, dissolution conditions may be altered to attempt to develop a 1-to-1 correlation between the in vitro dissolution profile and the In vivo dissolution profile. This work should also result in the definitive in vitro method that has been shown to be correlated with in vivo performance and sensitive to the specific formulation variables.
Step 3
In this phase plasma drug concentration profiles are predicted and compared to the observed time courses for different formulations (Figure 3). To generate predicted time courses, the drug input profile is predicted based on In vitro dissolution data and the In vitro-In
vivo relationship generated in step 2. In the convolution process, the predicted drug input and parameters describing drug distribution and/or elimination phases are combined in order to get predicted time courses. This procedure, which includes steps 1-3, is called two-stage deconvolution. Alternatively, a drug input profile based on in vitro dissolution data can be solved together with parameters describing systemic pharmacokinetics, i.e. distribution and elimination. This approach is called direct convolution.
Different IVIVC model are used as a tool for formulation development and evaluation of immediate and extended release dosage forms for setting a dissolution specification and as a surrogate for bioequivalence testing.
As a result, considerable effort goes into their development and the main outcome is “the ability to predict, accurately and precisely, expected bioavailability characteristics for an extended release (ER) drug product from dissolution profile characteristics [10].
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 6 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
Once the IVIVC is established and defined it can be then used to guide the final cycle of formulation and process optimization program statistically based experimental design studies looking at critical formulation and process variables. This information can also be used into the activities of scale-up, pivotal batch manufacture, and process validation culminating in registration, approval and subsequent post-approval scale-up and other changes. Thus rather than viewing the IVIVC as a single exercise at a given point in a development program, one should view it as a parallel development in itself starting at the initial assumed level and being built on and modified through experience and leading ultimately to a prospective IVIVC”.
Validation of IVIVC Model Evaluation of predictability of IVIVC
Prediction errors are estimated for Cmax and AUC to determine the validity of the correlation.
Various approaches of are used to estimate the magnitude of the error in predicting the in vivo bioavailability results from in vitro dissolution data.
Predictability of correlation
The objective of IVIVC evaluation is to estimate the magnitude of the error in predicting the in vivo bioavailability results from in vitro dissolution data. This objective should guide the choice and interpretation of evaluation methods. Any appropriate approach related to this objective may be used for evaluation of predictability [5,23]. It can be calculated by Prediction error that is the error in prediction of in vivo property from in vitro property of drug product (Figure 3).
Depending on the intended application of an IVIVC and the therapeutic index of the drug, evaluation of prediction error internally and/or externally may be appropriate [24].
Internal predictability
Evaluation of internal predictability is based on the initial data used to define the IVIVC model. Internal predictability is applied to IVIVC established using formulations with three or more release rates for non-narrow therapeutic index drugs exhibiting conclusive prediction error. If two formulations with different release rates are used to develop IVIVC, then the application of IVIVC would be limited to specified categories. The bioavailability (Cmax, tmax/AUC) of formulation that is used in development of IVIVC is predicted from its in vitro property using IVIVC. Comparison between predicted bioavailability and observed bioavailability is done and % P.E is calculated. According to FDA guidelines, the average absolute %P.E should be below 10% and %P.E for individual formulation should be below 15% for establishment of IVIVC.
Under these circumstances, for complete evaluation and subsequent full application of the IVIVC, prediction of error externally is recommended [23].
Acceptance criteria
According to FDA guidance
1) ≤15% for absolute prediction error (%P.E.) of each formulation.
2) ≤ 10% for mean absolute prediction error (%P.E.).
External predictability
Most important when using an IVIVC as a surrogate for bioequivalence is confidence that the IVIVC can predict in vivo performance of subsequent lots of the drug product. Therefore, it may be important to establish the external predictability of the IVIVC.
Evaluation of external predictability is based on additional test data sets [5]. External predictability evaluation is not necessary unless the drug is a narrow therapeutic index, or only two release rates were used to develop the IVIVC, or, if the internal predictability criteria are not met i.e. prediction error internally is inconclusive [4,23]. The predicted bioavailability is compared with known bioavailability and % P.E is calculated. The prediction error for external validation should be below 10% whereas prediction error between 10-20% indicates inconclusive predictability and need of further study using additional data set [24].
The % prediction error can be calculated by the following equation:
Prediction error
For Cmax
max max
max
( )%Prediction error (P.E.)= 100
C observed C predictedC observed
−× (5)
For AUC:(AUC AUC )%Prediction error (P.E.)= 100
AUC observed predicted
observed−
× (6)
Limitation of predictability metrics
Metrics used to evaluate the predictability is described simply the prediction error (%P.E.) for only two PK parameters i.e. Cmax and AUC. Emax predicted with IVIVC model represents the maximum of the mean plasma profiles but is compared with the mean Cmax observed calculated as the average of individual profile at different Tmax. But Tmax is not included in predictability metrics.
Factors to be Consider in Developing a CorrelationBiopharmaceutics classification system (BCS)
Biopharmaceutics Classification System (BCS) is a fundamental guideline for determining the conditions under which in-vitro, in-vivo correlations are expected [25]. It is also used as a tool for developing the in-vitro dissolution specification.
The classification is based on the drug dissolution and absorption model, which identifies the key parameters controlling drug absorption as a set of dimensionless numbers: the Absorption number, the Dissolution number and the Dose number [25-27].
The Absorption number is the ratio of the mean residence time to the absorption time.
2/ ( / ) / ( / )n res abs effA T T R L Q R Pπ= + (7)
The Dissolution number is a ratio of mean residence time to mean dissolution time given as equation 2
2 2 min0/ ( / ) / ( / 3 )n res diss sD T T R L Q pr DCπ= +
(8)
The Dose number is the mass divided by an uptake volume of 250 ml and the drug’s solubility as Equation 3
min/ ( / )o o sD Dose V C=
(9)
The mean residence time here is the average of the residence time
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 7 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
in the stomach, small intestine and the colon. The fraction of dose absorbed then can be predicted based on these three parameters. For example, Absorption number 10 means that the permeation across the intestinal membrane is 10 times faster than the transit through the small intestine indicating 100% drug absorbed.
In the BCS, a drug is classified in one of four classes based solely on its solubility and intestinal permeability [27].
A biopharmaceutic drug classification scheme for correlating in vitro drug product dissolution and in vivo bioavailability is proposed based on recognizing that drug dissolution and gastrointestinal permeability are the fundamental parameters controlling rate and extent of drug absorption. This classification system was devised by Amidon et al. [27].
The drugs are divided into high/low-solubility and permeability classes. Currently, BCS guidelines are provided by USFDA, WHO, and EMEA (European Medicines Academy)
Class I: HIGH solubility / High permeability,
Class II: LOW solubility / High permeability,
Class III: HIGH solubility / LOW permeability,
Class IV: LOW solubility / LOW permeability.
Class I: High solubility- high permeability drugs
In case of class I , drugs (such as metoprolol) is well absorbed (though its systemic availability may be low due to first pass extraction/ metabolism) and the rate limiting step to drug absorption is drug dissolution or gastric emptying if dissolution is very rapid. The dissolution specification immediate release (IR) dosage forms of perhaps 85% dissolved in less than 15 min. May insure bioequivalence. To insure bioavailability for this case, the dissolution profile must be well defined and reproducible. [5,27].
Class II: Low solubility- high permeability drugs
This is the class of drugs (such as phenytoin) for which the dissolution profile must be most clearly defined and reproducible. More precisely this is the case where absorption number, (An) is high and Dissolution number (Dn) is low. Drug dissolution in vivo is then the rate controlling step in drug absorption and absorption is usually slower than for class I [28-31].
Class III: High solubility-low permeability drugs
For this class of drugs (such as cimetidine) Permeability is the rate controlling step in drug absorption. While the dissolution profile must be well defined, the simplification in dissolution specification as in Class I is applicable for immediate release dosage forms where drug input to the intestine is gastric emptying rate controlled.. Both rate and extent of drug absorption may be highly variable for this class of drugs, but id dissolution is fast i.e. 85% dissolved in less than 15 min, this variation will be due to the variable gastrointestinal transit, luminal contents , and membrane permeability rather than dosage form factors [5].
Class IV: Low solubility-low permeability drugs
This class of drugs present significant problems for effective oral delivery. The number of drugs that fall in this class will depend on the precise limits used from the permeability and solubility classification.
Applications
This concept underlying the BCS published finally led to introducing the possibility of waiving in vivo bioequivalence (BE) studies in favor of specific comparative in vitro testing to conclude BE of oral immediate release (IR) products with systemic actions [32].
In terms of BE, it is assumed that highly permeable, highly soluble drugs housed in rapidly dissolving drug products will be bioequivalent and that, unless major changes are made to the formulation, dissolution data can be used as a surrogate for pharmacokinetic data to demonstrate BE of two drug products. The BCS thus enables manufacturers to reduce the cost of approving scale-up and post approval changes to certain oral drug products without compromising public safety interests [33].
It is a drug-development tool that allows estimation of the contributions of three major factors, dissolution, solubility and intestinal permeability that affect oral drug absorption from IR solid oral dosage forms. It was first introduced into regulatory decision-making process in the guidance document on immediate release solid oral dosage forms: Scale-up and post approval changes [2]. BCS system is an indicator of developing a predictive IVIVC and also examined the importance of drug dissolution and permeability on IVIVC validity (Table 2).
The establishment of correlation needs, as described in the FDA or USP definitions, to use various parameters summarized in following table: Waiver of in vivo BE studies
Class Solubility Permeability IVIVC correlation for IR Products
I High HighIVIVC correlation if dissolution rate is slower than gastric emptying rate, otherwise limited or no correlation
II Low HighIVIVC correlation expected if in in vitro dissolution rate is similar to in vivo dissolution rate , unless dose is very high
III High LowAbsorption [permeability] is rate determining and limited or no IVIV correlation with dissolution rate.
IV Low Low Limited or no IVIV correlation expected.
Table 2: IVIV correlation expectation for immediate release product based on biopharmaceutic class.
Biopharmaceutics Drug Classificationfor Extended Release Drug Products **
Class Solubility Permeability IVIVC
IA High & Site Independent High & Site Independent IVIVC Level A
expected
IB High & Site Independent
Dependent on site & Narrow Absorption Window
IVIVC Level C expected
IIaLow & Site Independent High & Site Independent IVIVC Level A
expected
IIbLow & Site Independent Dependent on site & Narrow
Absorption WindowLittle or no IVIVC
Va: Acidic Variable Variable
Little or no IVIVC
Vb: basic Variable Variable IVIVC Level A
expected.
Table 3: Biopharmaceutics Drug Classification for Extended Release Drug Products.
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 8 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
based on BCS Recommended for a solid oral Test product that exhibit rapid (85% in 30 min) and similar in vitro dissolution under specified conditions to an approved Reference product when the following conditions are satisfied (Table 3,4):
• Products are pharmaceutical equivalent
• Drug substance is highly soluble and highly permeable and is not considered have a narrow therapeutic range
• Excipients used are not likely to effect drug absorption
In vitro dissolution
Dissolution plays the important role in the formulation development as an obvious stage in IVIVC development when the dissolution is not influenced by factors such as pH, surfactants, osmotic pressure, mixing intensity, enzyme, ionic strength. Drug absorption from a solid dosage form following oral administration depends on the release of the drug substance from the drug product, the dissolution or solubilization of the drug under physiological conditions, and the permeability across the gastrointestinal tract. The purpose of the in-vitro dissolution studies in the early stage of drug development is to select the optimum formulation, evaluate the active ingredient and excipients, and assess any minor changes for drug products. During the early stages of correlation development, dissolution conditions may be altered to attempt to develop a one-to-one correlation between the in vitro dissolution profile and the in vivo dissolution profile [5]. For the IVIVC perspective, dissolution is proposed to be a surrogate of drug bioavailability. Thus, dissolution standard may be necessary for the in-vivo waiver [26]. The dissolution methodology, which is able to discriminate between the study formulations and which best, reflects the in vivo behavior would be selected. Once a discriminating system is developed, dissolution conditions should be the same for all formulations tested in the biostudy for development of the correlation and should be fixed before further steps towards correlation evaluation are undertaken [34]. The types of dissolution apparatus used as per USP recommended in the FDA guidance especially, for modified release dosage form are specified by the USP and are:
[1] Rotating basket,
[2] Paddle method,
[3] Reciprocating cylinder,
[4] Flow through cell,
Other dissolution methodologies may be used, however, the first four are preferred, especially the basket and paddle. But primarily it is
recommended to start with the basket or paddle method prior to using the others [26].
The in vitro dissolution release of a formulation can be modified to facilitate the correlation development. Changing dissolution testing conditions such as stirring speed, choice of apparatus, pH of the medium, and temperature may alter the dissolution profile.
As previously described, appropriate dissolution testing conditions should be selected so that the formulation behaves in the same manner as the in vivo dissolution.
For an appropriate dissolution test, in general and in particular for developing IVIVC, one requires to conduct the test selecting experimental conditions to simulate an in vivo environment as closely as possible. Commonly the following experimental conditions should be considered in this regard.
A common dissolution medium is dearated water, simulated gastric fluid (pH 1.2), or intestinal fluid (pH 6.8 or 7.4) without enzyme, and buffers with a pH range of 4.5 to 7.5 and be maintained at 37°C. For sparingly water-soluble drugs, use of surfactants in the dissolution medium is recommended [34,35]. A simple aqueous dissolution media is also recommended for BCS Class I drug as this type of drug exhibits lack of influence of dissolution medium properties [5,36]. Water and simulated gastric fluid then are the default mediums for most of the Class I drugs. A typical medium volume is 500 to 1000 ml.
1. Frequent samples (8-10) should be withdrawn to obtain a smooth dissolution profile leading to complete dissolution within the dosing interval of the test product in humans.
2. The normal test duration for immediate release is 15 to 60 minutes with a single time point. For example, BCS class I recommend 15 minutes. Additionally, two time points may be required for the BCS class II at 15 minutes and the other time at which 85% of the drug is dissolved [36].
3. In contrast, in vitro dissolution tests for a modified release dosage form require at least three time points to characterize the drug release. The first sampling time (1-2 hours or 20- 30% drug release) is chosen to check dose-dumping potential. The intermediate time point has to be around 50% drug release in order to define the in vitro release profile.
4. The dissolution medium should not be de-aerated. Preference should be given that the medium be equilibrated at 37°C with dissolved air/gasses, particularly for IVIVC studies.
5. An apparatus should be selected to have an appropriate
BCS Class Examples Drug delivery technology
Class I Metoprolol, Diltizem, Verapamil, Propranolol, Acyclovir, Atropine, verapamil.
Class IIPhenytoin, Danazole, Ketokonazole, Mefenamic acid, Tacrolimus, Piroxicam, griseofulvine, Warfarin,
Micronization, stabilization of high-energy states (including lyophilized fast-melt systems), use of surfactants, emulsion or microemulsion systems, solid dispersion and use of complexing agent such as cyclodextrins.e.g nanosuspension and nanocrystals are treated as hopeful means of increasing solubility and BA of poorly water-soluble active ingredients [28,30,31].
Class III Cimetidine, Neomycin, ranitidine, Amoxycillin, Oral vaccine system, Gastric retention system, High-Frequency Capsule and Telemetric Capsule [28,30,31].
Class IV Cyclosporin A, Furosemide, Ritonavir, Saquinavir andTaxol.
The class IV drugs present a major challange for the development of drug delivery systems due to their poor solubility and permeability characteristics. These are administered by parenteral route with the formulation containing solubility enhancers [ 28,30,31].
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 9 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
mechanism to provide thorough but gentle mixing and stirring for an efficient product/medium interaction. Use of sinkers may be avoided as these often alter the dissolution characteristics of the test products. Paddle and basket apparatuses are known for their inefficient stirring and mixing, thus their use should be critically evaluated before use for IVIVC studies.
6. The last time point is to define essentially complete drug release. The dissolution limit should be at least 80% drug release. Further justification as well as 24 hours test duration are required if the percent drug release is less than 80 [34,37].
7. If the dissolution results are not as expected, then the product/formulation should be modified to obtain the desired/expected release characteristics of the product. However, altering experimental conditions such as medium, apparatus, rpm etc. should be avoided as these are generally linked to GI physiology which remains the same for test to test or product to product. Obtaining dissolution results by altering testing (experimental) conditions may void the test for IVIVC purposes.
Once the discriminatory system is established, dissolution testing conditions should be fixed for all formulations tested for development of the correlation [6]. A dissolution profile of percentage or fraction of drug dissolved versus time then can be determined.
Comparison between dissolution profiles could be achieved using a difference factor (f1) and a similarity factor (f2) which originates from simple model independent approach. The difference factor calculates the percent difference between the two curves at each time point and is a measurement of the relative error between the two curves:
11 1
/ *100n n
t t tt r
f R T R= =
= − ∑ ∑ (10)
Where, n is the number of time points, Rt is the dissolution value of the reference batch at time t, and Tt is the dissolution value of the test batch at time t. The similarity factor is a logarithmic reciprocal square root transformation of the sum squared error and is a measurement of the similarity in the percent dissolution between the two curves
0.5
21
50* log 1 (1 / ) *100n
t tt
f n R T−
2
=
= + ( − ) ∑ (11)
Generally, f1 values up to 15 (0-15) and f2 values greater than 50 (50-100) ensure sameness or equivalence of the two curves. The mean in vitro dissolution time (MDTvitro) is the mean time for the drug to dissolve under in vitro dissolution conditions. This is calculated using the equation 6:
0( ( )) /vitroMDT M M t dt M
∞
∞ ∞= −∫ (12)
For the IVIVC development, the dissolution profiles of at least 12 individual dosage units from each lot should be determined. The coefficient of variation (CV) for mean dissolution profiles of a single batch should be less than 10%. Since dissolution apparatuses tend to become less discriminative when operated at faster speeds, lower stirring speeds should be evaluated and an appropriate speed chosen in accordance with the test data. Using the basket method the common agitation is 50-100 rpm; with the paddle method, it is 50-75 rpm and 25 rpm for suspension [5].
In vivo absorption (Bioavailability studies)
The FDA requires in vivo bioavailability studies to be conducted
for a New Drug Application (NDA). A bioavailability study should be performed to characterize the plasma concentration versus time profile for each of the formulation. These studies for the development of IVIVC should be performed in young healthy male adult volunteers under some restrictive conditions such as fasting, non-smoking, and no intake of other medications. In prior acceptable data sets, the number of subjects has ranged from 6 to 36. Although crossover studies are preferred, parallel studies or cross-study analyses may be acceptable. The latter may involve normalization with a common reference treatment. The drug is usually given in a crossover fashion with a washout period of at least five half-lives.
The bioavailability study can be assessed via plasma or urine data using the following parameters: (I) area under the plasma time curve (AUC), or the cumulative amount of drug excreted in urine (Du), (II) maximum concentration (Cmax), or rate of drug excretion in urine (dDu/dt), and (III) a time of maximum concentration (Tmax).
Several approaches can be used for determining the In vivo absorption. Wagner-Nelson, Loo-Riegelman, and numerical deconvolution are such methods [2,37]. Wagner Nelson and Loo-Riegelman are both model dependent methods in which the former is used for a one-compartment model and the latter is for multi-compartment system.
The Wagner Nelson method is less complicated than the Loo-Riegelman as there is no requirement for intravenous data. However, misinterpretation on the terminal phase of the plasma profile may be possible in the occurrence of a flip flop phenomenon in which the rate of absorption is slower than the rate of elimination.
Application of An IVIVCApplication in drug delivery system
Various rate controlling technologies are used as the basis for Modified release dosage forms e.g. Diffusion-dissolution, matrix retardation, osmosis, etc. to control, and prolong the release of drugs, for the administration by oral or parenteral route [24,38].
The novel drug delivery systems have been developed such as OROS, liposomes, niosomes, pharmacosomes, microspheres, nanoparticles, implants, in situ gelling system, organogels, transdermal drug delivery systems, parenteral depots, etc. as a substitute for conventional dosage forms. The obvious objective of these dosage forms is to achieve zero-order, long term, pulsatile, or “on demand” delivery. Major applications of IVIVC related to oral drug delivery and a few issues related to the development of IVIVC models for parenteral drug delivery are addressed herewith [39].
In early stages of drug delivery technology development
The most crucial stage in the drug development is drug candidate selection. Such selection is primarily based on the drug “developability” criteria, which include physicochemical properties of the drug and the results obtained from preformulation, preliminary studies involving several in vitro systems and in vivo animal models, which address efficacy and toxicity issues [24,40]. During this stage, IVIVC (exploring the relationship between in vitro and in vivo properties) of the drug in animal models provide an idea about the feasibility of the drug delivery system for a given drug candidates. In such correlations, study designs including study of more than one formulation of the modified-release
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 10 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
dosage forms and a rank order of release (fast/slow) of the formulations should be incorporated. Even though the formulations and methods used at this stage are not optimal, they promise better design and development efforts in the future.
Formulation assessment: In vitro dissolution
A suitable dissolution method that is capable of distinguishing the performance of formulations with different release rates in vitro and in vivo is an important tool in product development. Depending on the nature of the correlation, further changes to the dissolution method can be made. When the discriminatory in vitro method is validated, further formulation development can be relied on the in vitro dissolution only.
Dissolution specifications
Modified-release dosage forms typically require dissolution testing over multiple time points, and IVIVC plays an important role in setting these specifications [24,39]. Specification time points are usually chosen in the early, middle, and late stages of the dissolution profiles. In the absence of an IVIVC, the range of the dissolution specification rarely exceeds 10% of the dissolution of the pivotal clinical batch. However, in the presence of IVIVC, wider specifications may be applicable based on the predicted concentration-time profiles of test batches being bioequivalent to the reference batch.
The process of setting dissolution specifications in the presence of an IVIVC starts by obtaining the reference (pivotal clinical batch) dissolution profile. The dissolution of batches with different dissolution properties (slowest and fastest batches included) should be used along with the IVIVC model, and prediction of the concentration time profiles should be made using an appropriate convolution method. Specifications should optimally be established such that all batches with dissolution profiles between the fastest and slowest batches are bioequivalent and less optimally bioequivalent to the reference batch. The above exercise in achieving the widest possible dissolution specification allows majority of batches to pass and is possible only if a valid Level A model is available [24].
Future biowaivers
Frequently, drug development requires changes in formulations due to a variety of reasons, such as unexpected problems in stability, development, availability of better materials, better processing results, etc. Having an established IVIVC can help avoid bioequivalence studies by using the dissolution profile from the changed formulation, and subsequently predicting the in vivo concentration-time profile [24,41].
This predicted profile could act as a surrogate of the in vivo bioequivalence study. This has enormous cost-saving benefit in the form of reduced drug development spending and speedy implementation of post-approval changes. The nature of post-approval changes could range from minor (such as a change in non release-controlling excipient) to major (such as site change, equipment change, or change in method of manufacture, etc) [24,42].
IVIVC - Parenteral drug delivery
IVIVC can be developed and applied to parenteral dosage forms, such as controlled-release particulate systems, depot system, implants, etc, that are either injected or implanted. However, there are relatively fewer successes in the development of IVIVC for such dosage forms, which could be due to several reasons, a few of which are discussed
further. Sophisticated modeling techniques are needed to correlate the in vitro and in vivo data, in case of burst release which is unpredictable and unavoidable [24,43].
Potent Drugs & Chronic Therapy - In general, several parenteral drug delivery systems are developed for potent drugs (eg, hormones, growth factors, antibiotics, etc) and for long-term delivery (anywhere from a day to a few weeks to months). In such instances, to establish a good IVIVC model, the drug concentrations should be monitored in the tissue fluids at the site of administration by techniques such as microdialysis, and then the correlation should be established to the in vitro release.
Biowaivers
Validated IVIVC is applicable to serve as justification for a biowaiver in filings of a Level 3 (or Type II in Europe) variation, either during scale-up or post approval, as well as for line extensions (e.g., different dosage strengths). A biowaiver will only be granted if the prediction of the in vivo performance of the product with the modified in vitro release rate remains bioequivalent with the originally tested product (i.e., the new dissolution rate remains within the IVIVC based biorelevant corridor).
The FDA guidance outlines five categories of biowaivers: 1) biowaivers without an IVIVC, 2) biowaivers using an IVIVC: non-narrow therapeutic index drugs, 3) biowaivers using an
IVIVC: narrow therapeutic index drugs, 4) biowaivers when in vitro dissolution is independent of dissolution test conditions and 5) situations for which an IVIVC is not recommended for biowaivers Biowaivers may be granted for manufacturing site changes, equipment changes, manufacturing process changes, and formulation composition changes according to a predictive and reliable IVIVC. The changes may range from minor changes that are not significant to alter product performance to major ones where an IVIVC is not sufficient to justify the change for regulatory decision [4,24].
Establishment of dissolution specifications
It is relatively easy to establish a multipoint dissolution specification for modified-release dosage forms .The dissolution behavior of the biobatch maybe used to define the amount to be released at each time point. However, the difficulty arises in the variation to be allowed around each time point [37]. The FDA guidance describes the procedures of setting dissolution specifications in cases of level A, multiple levels C, and level C correlation and where there is no IVIV correlation. Once an IVIVC developed, IVIVC should be used to set specifications in such a way that the fastest and lowest release rates allowed by the upper and lower dissolution specifications result in a maximum difference of 20% in the predicted Cmax and AUC. Predicted plasma concentration and consequent AUC and Cmax could be calculated using convolution or any other appropriate modeling techniques [24]. In the case of multiple level C correlation, the last time point should be the time point where at least 80% of drug has dissolved. For level C correlation, reasonable deviations from ±10 % may be acceptable if the range at any time point does not exceed 25%. When there is no IVIVC, the tolerance limits may be derived from the spread of in vitro dissolution data of batches with demonstrated acceptable in vivo performance (biobatch) or by demonstrating bioequivalence between batches at the proposed upper and lower limit of the dissolution range (the so called side batch
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 11 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
concept). Variability in release at each time point is recommended not to exceed a total numerical difference of ±10% (a total of 20%) or less of the labeled claim. In certain cases, deviations from this criterion can be acceptable up to a maximum range of 25%. Beyond this range, the specification should be supported by bioequivalence studies [43].
Mapping
Mapping is a process which relates Critical Manufacturing Variables (CMV), including formulation, processes, and equipment variables that can significantly affect drug release from the product. The mapping process defines boundaries of in vitro dissolution profiles on the basis of acceptable bioequivalency criteria. The optimum goal is to develop product specifications that will ensure bioequivalence of future batches prepared within the limits of acceptable dissolution specifications. Dissolution specifications based on mapping would increase the credibility of dissolution as a bioequivalency surrogate marker and will provide continuous assurance and predictability of the product performance [5].
Some Limitations in the IVIVC Arising from the In Vivo Data
Could easily be understood:
1. More than one dosage form is needed and if possible intravenous or solution is essential to calculate deconvolution.
2. Pharmacokinetics and absorption of the drug should be ‘‘linear.’’ If the pharmacokinetic processes are dependent on the fraction of dose reaching the systemic blood flow (or of the dose administered) or on the rate of absorption, comparison between formulation and simulation cannot be made. This non-linearity may be owing to saturable absorption processes (active absorption), induction or inhibition of the metabolism, the first past effect, which is rate/absorption dependent, etc. Those points must be studied before any attempt to establish an IVIVC.
3. Absorption should not be the limiting factor, if the solubility is not the limiting factor in comparison to the drug release, an IVIVC may be attempted. The release must depend on the formulation, and must be the slowest phenomenon vs. dissolution and absorption.
ConclusionsThe pharmaceutical industry has been striving to find a ways to
saving precious resources in relevance to the budgets and increasing cost of drug development. IVIVC is a tool applied in various areas and stages of drug development to find a place in the regulatory bodies around the world. IVIVC can serve as surrogate for in vivo bioavailability and to support biowaivers also allows setting the dissolution specification and methods. The substitute of expensive clinical trials with the use of IVIVC is perhaps the most important feature of IVIVC. From the regulatory point of view IVIVC can assist certain scale-up and post-approval changes. IVIVC principles have been mostly applied to oral products, there exists a need to develop methodologies and standards for non-oral delivery systems, to develope more meaningful dissolution and permeation methods. Acknowledgement
The authors gratefully acknowledge Mrs. Sangita Sakore (Regulatory affairs, Formulation & Development, MKPPL, Pune, India) for her contribution.
References
1. Leeson LJ (1995) In vitro/ In vivo correlations. Drug Info J 29: 903-915.
2. US Department of Health and Human Services (1995) Guidance for industry: Immediate release solid oral dosage forms scale-up and postapproval changes: chemistry, manufacturing, and controls, in vitro dissolution testing, and in vivo bioequivalence documentation. Center for drug Evaluation and Research.
3. Center for Drug Evaluation, USFDA (1995) Guidance for Industry: Immediate Release Solid Oral Dosage Forms: Scale Up and Post Approval Changes.
4. Uppoor VRS (2001) Regulatory perspectives on in vitro (dissolution)/in vivo (bioavailability) correlations. J Control Rel 72: 127-132.
5. Jaber E (2006) In vitro - In vivo Correlation: From Theory to Applications. J Pharm Pharmaceut Sci 9: 169-189.
6. Food and Drug Administration (1997) Guidance for industry: extended release oral dosage forms: Development, evaluation, and application of in vitro/in vivo correlations.
7. Sirisuth N, Eddington ND (2002) In vitro in vivo correlations, systemic methods for the development and validation of an IVIVC metoprolol and naproxen drug examples. Int J Generic Drugs 3: 250-258.
8. Qureshi SA (2010) In Vitro-In Vivo Correlation (IVIVC) and Determining Drug Concentrations in Blood from Dissolution Testing - A Simple and Practical Approach. Open Drug Delivery J 4: 38-47.
9. O’Hara T, Hayes S, Davis J, Devane J, Smart T, et al. (2001) In vivo-In Vitro Correlation (IVIVC) Modeling Incorporating a Convolution Step. J Pharmacokinet Pharmacodyn 28: 277-298.
10. Gaynor C, Dunne A, Davis J (2008) A Differential Equations Approach to In Vitro – In Vivo Correlation Modelling. International Biometric Conference, Dublin.
11. Dunne A (2007) Approaches to developing IVIVC models, Ch 5. In Chilukuri, Sunkara and Young (Eds), Pharmaceutical Product Development: In Vitro – In vivo Correlation. Taylor and Francis, New York.
12. Beal SL, Sheiner LB (1992) NONMEM User’s Guides, NONMEM Project Group, University of California, San Francisco.
13. Meyer MC, Straughn AB, Mhatre RM, Shah VP ,Williams RL (1998) Lack of in vitro / in vivo correlations of 50 mg and 250 mg primidone tablets. Pharm Res 15: 1085-1089.
14. Food and Drug Administration. Rockville, MD Abdou, HM (1989) Dissolution Bioavailability and Bioequivalence. Easton Pennsylvania: Mack Printing.
16. Dressman JB, Amidon GL, Reppas C, Shah VP (1998) Dissolution testing as a prognostic tool for oral drug absorption: immediate release dosage forms. Pharm Res 15: 11-22.
17. Corrigan OI (1997) The biopharmaceutic drug classification and drugs administered in extended release (ER) formulations. Adv Exp Med Biol 423: 111-128.
18. Yu H, Joves R (2004) The STATs of cancer--new molecular targets come of age. Nat Rev Cancer 4: 97-105.
19. Wagner JG, Nelson E (1964) Kinetic analysis of blood levels and urinary excretion in the absorptive phase after single doses of drug. J Pharm Sci 53: 1392-1403.
20. Loo JC, Riegelman S (1968) New method for calculating the intrinsic absorption rate of drugs. J Pharm Sci 57: 918-928.
21. Cutler DJ (1978) Linear system analysis in pharmacokinetics. Pharmacokinet Biopharm 6: 265-282.
22. Brockmeier D, Voegele D, von Hattingberg HM (1983) In vitro-in vivo correlation, a time scaling problem? Basic techniques for testing equivalence. Arzneimittelforschung 33: 598-601.
23. Jayaprakasam B, Seeram NP, Nairs MG (2003) Anticancer and antiinflammatory activities of cucurbitacins from Cucurbita andreana. Cancer Lett 189: 11-16.
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.S3-001
Page 12 of 12
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
24. Chilukuri DM, Sunkara G (2003) IVIVC: An Important Tool in the Development of Drug Delivery Systems. Drug Deliv Technol 3: 4.
25. Young D, Devane JG, Butler J (1997) In Vitro-In Vivo Correlations. New York: Plenum press.
26. Amidon GL, Robinson JR, Williams RL (1997) Scientific Foundations for Regulating Drug Product Quality. American Association of Pharmaceutical Scientists. Alexandria, Virginia: AAPS Press.
27. Amidon GL, Lennernas H, Shah VP, Crison JR (1995) A theoretical basis for a biopharmaceutic drug classification: The correlation of in vitro drug product dissolution and in vivo bioavailabilty. Pharm Res 12: 413-419.
28. Gohel MC, Mehta NR (2005) An audit of recent inputs on biopharmaceutical classification system. Pharmaceut Rev.
29. Yu LX, Amidon GL, Polli JE, Zhao H, Mehta MU, et al. (2002) Biopharmaceutics classification system: The scientific basis for biowaiver extension. Pharm Res 19: 921-925.
30. Wilding I (1999) Evolution of the Biopharmaceutics Classification System (BCS) to Modified Release (MR) formulations: What do we need to consider? Eur J Pharm Sci 8: 157-159.
31. Devane J (1998) Oral drug delivery technology: Addressing the solubility/permeability paradigm. Pharmaceut Technol 22: 68-80.
32. Helga M (2002) The Biopharmaceutical Classification System (BCS) and its usage. Drugs Made in Germany 45: 63-65.
33. Dressman J, Butler J, Hempenstall J, Reppas C (2001) The BCS: Where do we go from here? Pharmaceut Technol 25: 68-76.
34. Sievert B, Siewert M (1998) Dissolution tests for ER products. Dissolut Technol 5.
35. Shargel L, Yu ABC (1993) Applied Biopharmaceutics and Pharmacokinetics. East Norwark, Connecticut: Appleton & Lange.
36. Galia E, Nicolaides E, Horter D, Lobenberg R, Reppas C, et al. (1998) Evaluation of various dissolution media for predicting in vivo performance of class I and class II drugs. Pharm Res 15: 698-705.
38. Strickley RG (1999) Parenteral formulations of small molecules therapeutics marketed in the United States Part I, PDA. J Pharm Sci Tech 53: 324-349.
39. Modi NB, Lam A, Lindemulder E, Wang B, Gupta SK (2000) Application of in vitro-in vivo correlation (IVIVC) in setting formulation release specifications. Biopharm Drug Dispos 21: 321-326.
40. Venkatesh S, Lipper RA (2000) Role of the development scientist in compound lead selection and optimisation. J Pharm Sci 89: 145-154.
41. Hwang SS, Gorsline JJ, Louie J, Dye D, Guinta D, et al. (1995) in vitro and in vivo evaluation of a once-daily controlled release pseudoephedrine product. J Clin Pharmacol 35: 259-267.
42. FDA (1997) Guidance for Industry: SUPAC-MR: Modified release solid oral dosage forms: scale-up and post-approval changes: chemistry, manufacturing and controls, in vitro dissolution testing, and in vivo bioequivalence documentation.
43. Young D, Chilukuri D, Becker R, Bigora S, Farrell C, et al. (2002) Approaches to developing a Level-A IVIVC for injectable dosage forms. AAPS Pharm Sci 4: M1357.
Submit your next manuscript and get advantages of OMICS Group submissionsUnique features:
Received: 23 July 2010, Revised and Accepted: 23 August 2010
ABSTRACT
Literature and experimental data relevant to the decision to allow a waiver of in vivo bioequivalence testing for the approval of immediate release (IR) solid oral dosage forms containing ofloxacin have been reviewed. According to the current Biopharmaceutics Classification System (BCS), ofloxacin should be assigned to Class I. Therapeutic use, therapeutic index, pharmacokinetic properties, reported BE/bioavailability (BA) and data related to the possibility of excipient interactions studies of Ofloxacin were also taken into consideration in order to ascertain whether a biowaiver can be recommended. Ofloxacin seems not to be critical with respect to a risk for bioinequivalence, as no examples of bioinequivalence have been identified. However; if (a) the test product contains only excipients in their usual amounts present in ofloxacin solid oral IR drug products approved in ICH or associated countries, for instance as presented in this article; and (b) the comparator and the test product both are very rapidly dissolving a biowaiver for IR ofloxacin solid oral drug products is considered justified for all tablet strengths.
Keywords: Absorption, Biopharmaceutics Classification System (BCS), Ofloxacin, Permeability, Solubility.
INTRODUCTION
A biowaiver monograph of ofloxacin based on literature data together with some additional experimental data has been presented here. A biowaiver implies that bioequivalence (BE) assessment studies would be waived for marketing authorizations (MA) by Health Authorities for a new tablet or capsules, or a new formulation of an existing immediate release (IR) dosage form, and hence the product is considered bioequivalent to its reference product, without carrying out a bioequivalence (BE) study. The risks of waiving in vivo BE testing for the approval of new and/or reformulated immediate release (IR) solid oral dosage forms containing ofloxacin, including both reformulated products and new multi source products, are evaluated in consideration of their biopharmaceutical and clinical properties. The scientific basis for a waiver request for ofloxacin tablets has been developed according to Biopharmaceutical Classification System (BCS)1 .
The BCS states that three major factors govern the rate and extent of drug absorption of IR solid oral dosage forms: dissolution rate, solubility and intestinal permeability. For IR dosage forms containing active pharmaceutical ingredients (APIs) showing high solubility, high intestinal permeability, and rapid dissolution, a waiver from performing BE studies (biowaiver) can be scientifically justified. In the regulatory domain this is adopted by both the US FDA and the European CPMP in their guidances for industry, Waiver of In Vivo Bioavailability (BA) and BE Studies for Immediate‐Release Solid Oral Dosage Forms Based on a BCS 2 and the Note for Guidance on the Investigation of BA and BE 3 respectively, have been together referred to as the Guidances in this article. In particular, the US FDA document describes in detail the data that are necessary for a successful application for a biowaiver. To explore the scope and the possibilities of gathering BCS related data from scientific literature, and in order to set up such BCS‐monographs, a literature search was carried out on ofloxacin.
The aim of this monograph is to evaluate all pertinent data available from literature sources for ofloxacin to assess the risks associated with a biowaiver. For these purposes risk is defined as the probability of an incorrect biowaiver decision as well as the consequences of an incorrect biowaiver decision in terms of public health and individual patient risk. On the basis of these considerations, a recommendation can be made as to whether a biowaiver is advisable or not for ofloxacin solid oral dosage forms. This systematic approach to recommend or advice against a
biowaiver decisions is referred to in recently published World Health Organization (WHO) Guideline.
General characteristics of Ofloxacin
Chemical, Pharmaceutical and Pharmacokinetic BCS‐related information on ofloxacin was obtained by means of a literature search. The following data‐fields were defined in order to standardize the dataset: indication, solubility, dissolution, poly‐morphism, partition coefficient, pKa, available dose, permeability, stereospecificity, pharmacokinetic properties. Literature data was accessed from PubMed, PubChem, Medicines Complete, WHO search engine, WHOLIS, the BIAM, 16 ROTE LISTE, and VIDAL databases. Key words used for searching were: Ofloxacin, bioequivalence, bioavailability, biowaiver, solubility, permeability, dissolution, excipient, toxicity, polymorphism, and pharmacokinetics.
Nomenclature
Ofloxacin (INN) It’s chemical name is (±)‐9‐fluoro‐2,3‐dihydro‐3‐methyl‐10‐(4‐methyl‐1‐piperazinyl)‐7‐oxo‐7H‐pyrido[1,2,3‐de]‐1,4‐benzoxazine‐6‐carboxylic acid. 4
Its structure is shown in below Fig 1.
N
O
N
O
COOH
CH3
NH3C
F
Fig. 1: Structure of ofloxacin
Therapeutic indications
Ofloxacin is a new fluoroquinolone with a spectrum of activity similar to other fluoroquinolones with activity which includes Chlamydia trachomatis, Mycobacterium spp., Mycoplasma spp. and Legionella pneumophila. Ofloxacin may be less susceptible to the development of resistance from Staphylococcus aureus commonly seen with currently available fluoroquinolones5.
It is also used in chlamydial infections including nongonococcal urethritis in treating mycobacterial infections such as leprosy. Ofloxacin tablets are indicated for the treatment of adults with mild to moderate infections (unless otherwise indicated) caused by susceptible strains of the designated microorganisms in the infections listed below 6.
International Journal of Pharmacy and Pharmaceutical Sciences
ISSN- 0975-1491 Vol 2, Suppl 4, 2010
Sakore et al.
Int J Pharm Pharm Sci, Vol 2, Suppl 4, 156161
2
• Acute bacterial exacerbations of chronic bronchitis due to Haemophilus influenzae or Streptococcus pneumoniae.
• Community‐acquired Pneumonia due to Haemophilus influenzae or Streptococcus pneumoniae.
• Uncomplicated skin and skin structure infections due to methicillin‐susceptible Staphylococcus aureus, Streptococcus pyogenes, or Proteus mirabilis.Acute, uncomplicated urethral and cervical gonorrhea due to Neisseria gonorrhoeae.
• Nongonococcal urethritis and cervicitis due to Chlamydia trachomatis.
• Mixed Infections of the urethra and cervix due to Chlamydia trachomatis and Neisseria gonorrhoeae.
• Acute pelvic inflammatory disease (including severe infection) due to Chlamydia trachomatis and/or Neisseria gonorrhoeae.
• Uncomplicated cystitis due to Citrobacter diversus, Enterobacter aerogenes, Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, or Pseudomonas aeruginosa.
• Complicated urinary tract infections due to Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Citrobacter diversus, or Pseudomonas aeruginosa.
• Prostatitis due to Escherichia coli (http://www.rxlist.com/floxin‐drug.htm)
Therapeutic index and toxicity
An adult oral or intravenous dose ranges from 200 mg daily to 400 mg twice daily depending on the severity and the nature of the infection. Oral doses up to 400 mg may be given as a single dose, preferably in the morning. For intravenous use a 0.2% solution is infused over 30 minutes or a 0.4% solution over 60 minutes. A dose of 400 mg daily or intermittently by mouth has been recommended by WHO as part of alternative multidrug therapy regime for leprosy 7.
The following is a compilation of the data for ofloxacin based on clinical experience with both the oral and intravenous formulations. The incidence of drug‐related adverse reactions in patients during Phase 2 and 3 clinical trials was 11%. Among patients receiving multiple‐dose therapy, 4% discontinued ofloxacin due to adverse experiences. In clinical trials, the following events were considered likely to be drug‐related in patients receiving multiple doses of ofloxacin: nausea 3%, insomnia 3%, headache 1%, dizziness 1%, diarrhea 1%, vomiting 1%, rash 1%, pruritus 1%, external genital pruritus in women 1%, vaginitis 1%, dysgeusia 1%. Information on overdosage with ofloxacin is limited. One incident of accidental overdosage has been reported. In this case, an adult female received 3 grams of ofloxacin intravenously over 45 minutes. A blood sample obtained 15 minutes after the completion of the infusion revealed an ofloxacin level of 39.3 μg/mL. In 7 h, the level had fallen to 16.2 μg/mL, and by 24 h to 2.7 μg/mL. During the infusion, the patient developed drowsiness, nausea, dizziness, hot and cold flushes, subjective facial swelling and numbness, slurring of speech, and mild to moderate disorientation. All complaints except the dizziness subsided within 1 h after discontinuation of the infusion. The dizziness, most bothersome while standing, resolved in approximately 9 h. Laboratory testing reportedly revealed no clinically significant changes in routine parameters in these patient. Thus, ofloxacin does not have a narrow therapeutic index 6.
Chemical properties
Stereoisomers and polymorphs
Ofloxacin chemically a fluorinated corboxyquinolone, and it’s the racemate 6 Polymorphic forms have not been reported in the literature.
Partition coefficient (logP)
The n‐octanol/water partition coefficient (log P) of ofloxacin was reported as ‐0.48 8.
pKa
Ofloxacin is an amphoteric drug with two protonation sites9,10. Its pKa are 6.05 for the carboxylic group and 8.22 for the piperazine nitrogen given in figure 2.
N
O
N
O
COOH
CH3
NH3C
F
pKa = 6.0
pKa = 8.0
Fig. 2: The molecular structure of ofloxacin with the approximate pKa values.
Solubility
Ofloxacin is freely soluble in acetic acid, slightly soluble in water, methanol, ethanol or acetone8.
Dosage form strengths
The WHO Essential Medicines List (EML) lists Ofloxacin Tablet strengths from 200 to 400 mg (WHO drug information, 2007) Ofloxacin tablet dosage form existing in different countries through out world on different brand names by different marketing authorization7 . In the United States, NDA exists for strengths in the range of 200 to 400 mg3 .
Pharmacokinetic properties
Permeability and absorption
One of the permeability studies for ofloxacin drug substance was carried out with Caco‐2 assay method. This cell culture model was previously evaluated and determined to be a suitable method according to the BCS Guidance as it demonstrated a rank‐order correlation between in vitro permeability and human extent of absorption for the model drugs, with a clear segregation between high and low permeability drug substances11. Based on the previous reports of human absolute bioavailability, it was expected that ofloxacin would be classified as a highly permeable (HP) drug12,13 . Also, in the Caco‐2 permeability assays, ofloxacin was classified as HP drugs. Thus, the in vitro results matched human in vivo data based on absolute bioavailability. In addition, there was evidence that ofloxacin underwent some active transport as its permeability apparent values decreased with concentration 14 .
Following oral administration, there is rapid and extensive oral absorption from the gastrointestinal tract achieving peak serum concentration within 1 – 3 h and levels in excess of 100 g/ml in the urine and bladder 8.
The pharmacokinetics of ofloxacin are characterised by almost complete bioavailability (95 to 100%), peak serum concentrations in the range of 2 to 3 mg/L after a 400mg oral dose and an average half‐life of 5 to 8h. Ofloxacin is rapidly and well absorbed from the gastrointestinal tract5.Oral bioavailability is almost 100% and a peak plasma concentration of 3 to 4 μg/mLis achieved within 1 to 2 hours after a dose of 400 mg by mouth. Absorption may be delayed by the presence of food, but the extent of absorption is not substantially affected 7 .
Distribution
About 25% of ofloxacin is bound to plasma proteins. Ofloxacin is widely distributed in body fluids, including the CSF, and tissue penetration is good. It crosses the placenta and is distributed into breast milk. Relatively high concentration is achieved in bile 7 .
Metabolism and excretion
There is limited metabolism to desmethyl and N‐oxide metabolites; desmethylofloxacin has moderate antibacterial activity. Ofloxacin is eliminated mainly by the kidneys. Excretion is by tubular secretion and glomerular filtration and 75 to 80% of a dose is excreted unchanged in the urine over 24 to 48 hours, resulting in high urinary concentrations. Less than 5% is excreted in the urine as metabolites. From 4 to 8% of a dose may be excreted in the faeces. Only small
157
Sakore et al.
Int J Pharm Pharm Sci, Vol 2, Suppl 4, 156161
3
amount of ofloxacin are removed by Dialysis 7 . In comparison with other available quinolones, elimination is more highly dependent on renal clearance, which may lead to more frequent dosage adjustments in patients with impaired renal function6.
Food and excipients interaction
Ofloxacin interacts with multivalent cation‐containing products, such as aluminum‐ or magnesium‐containing antacids and products containing calcium, iron, or zinc. Concomitant use invariably results in marked reduction of oral absorption of this antimicrobial. The mechanism of this interaction is formation of insoluble chelation complexes in the gastrointestinal tract that inhibit drug absorption 15,16 .
Multivitamin preparations that contain minerals should be avoided. Similar adverse effects on fluoroquinolone absorption were observed with concomitant administration of ferrous sulfate (iron), with decreases in bioavailability of the antibiotic of 19‐66 %.17,18 .
Although it is usually recommended that concomitant intake of calcium‐rich foods (e.g., milk) be avoided because of the potential for chelation effects, the actual influence of dairy products on fluoroquinolone absorption varies19,20 . Milk did not alter the rate or extent of absorption of ofloxacin or its elimination 21 .
Sucralfate significantly interferes with oral absorption of fluoroquinolones. It decreased the bioavailability of these drugs by up to 98% when given within 2 hours of antibiotic administration. The mechanism of this interaction has been attributed to both the aluminum content of the sucralfate salt and direct binding of the fluoroquinolone by the sucralfate itself 22,23. The degree to which fluoroquinolones are absorbed is not significantly affected by food. Studies involving ciprofloxacin, levofloxacin, gatifloxacin, and moxifloxacin consistently reported alterations in drug absorption rates without change in the extent of absorption 24.
When fluoroquinolones are administered with food, peak concentration times are usually slightly delayed, and maximum
plasma concentrations (C max) are decreased 8‐16%. The area under the plasma concentration versus time curve (AUC) is invariably unchanged and alterations in absorption rates are considered to be clinically insignificant21.
Dosage form performance
Bioavailability and bioequivalence
Bioavailability of oral and intravenous ofloxacin was investigated after the administration of multiple doses of 400 mg every 12 h to 20 healthy male volunteers in a randomized, crossover, open‐label study. Ofloxacin concentrations in plasma were evaluated after 4 days of oral or intravenous (1‐h infusion) dosing with a 3‐day wash‐out period between regimens. As expected, delivery to the systemic circulation took slightly longer after the oral dosing (time to maximum concentration of drug in serum of 1.7 h) relative to the 1‐h intravenous infusion, but the systemic availabilities of ofloxacin by the two routes of administration were equivalent (area under the concentration‐time curve from 0 to 12 h ratio of 95%)25.
Excipients
Ofloxacin interact with multivalent cations present in fillers, binders and lubricants. Table 2 shows the excipients present in ofloxacin IR solid drug products in US market. It can be inferred that these drug products successfully passed an in vivo BE study. In Table 2 the amounts of various excipients found in single API ofloxacin products, along with the ranges specified by the FDA for oral drug products in general, are given 3 .
Excipients present in IR ofloxacin tablets with US MA are summarized in Table 3. In vivo comparisons of different formulations were not reported. Therapeutic inequivalence between brand‐name drug products and FDA‐approved generic drug products has not been reported and there have been no reports of bioinequivalence of IR tablets with an approval in India.
Table1: Excipients present in Ofloxacin IR solid oral drug with a Marketing Authorization United States (IIG Limits)
Excipients Max. amount present in solid oral dosage forms with a MA in the USA (mg) Lactose Anhydrous 735.20 Modified corn starch 433.32 Hydroxy propyl cellulose 46.00 Hypromellose 54.00Magnesium stearate 400.74Polyethylene Glycol 0.12 POLYSORBATE 80 21.25Sodium starch Glycolate 876.00Purified Talc 91.20 Titanium dioxide 27.00 Different countries having ofloxacin with following brand names:
Details of excipients used in the Ofloxacin tablet formulation from different countries were not available for studying.
Dissolution
The present biowaiver criteria state that, in addition to similarity of dissolution profiles, the test and the comparator drug product
should both be rapidly dissolving , which is defined as: not less than 85% of API releases within 30 min employing the dissolution conditions decribed therein 2,3 The Office of Generic Drugs (OGD), USFDA recommended dissolution medium is 0. 1 N HCl of 900ml, using USP‐II apparatus at 100 rpm with time points 10,20,30 & 45 minutes and specification for ofloxacin tablets is: not less than 80% (Q) should be dissolved in 45 mins.
MATERIALS AND METHODS
Solubility
The solubility of Ofloxacin as a function of pH is shown in Table 2. The solubility of ofloxacin was determined and all the solibility tests were conducted in triplicate. The media used were water media of various pH as 1.2, 4.5, 5.0, 6.0, 6.8, 7.2, 7.5, 8.2, and pH 9.2 and the temperatures were maintained at 37±0.5 ◦C.
158
Sakore et al.
Int J Pharm Pharm Sci, Vol 2, Suppl 4, 156161
2
Table 2: Experimental solubility data (mg/ml) for ofloxacin and the corresponding dose/solubility (d/s) ratios for highest tablet strengths
S No pH pH after adittion of ofloxacin
Calculated solubility in mg/ml
Dose/solubility (D/S) ratios for highest tablet strengths (mg)
The release rate of Ofloxacin was determined using United States Pharmacopoeia (USP) Dissolution Testing Apparatus II (Paddle method). The dissolution test was performed in 900 ml of 0.1N HCl, in acetate buffer of pH 4.5 and simulated intestinal fluid pH 6.8, at 37 ± 0.5°C and 50 rpm. A sample (5 ml) of the solution was withdrawn
from the dissolution apparatus at intervals of 10, 20, 30 and 45 minutes and the samples were replaced with fresh dissolution medium. The samples were diluted to a suitable concentration with dissolution media. Absorbance of these solutions was measured at 294nm using a UV/Visible spectrophotometer. Cumulative percentage drug release was calculated using an equation obtained from a standard curve shown in table 3.
Table 3: Dissolution profiles of formulations of 200 mg, 300 mg and 400 mg of Ofloxacin
The present biowaiver criteria state that, in addition to similarity of dissolution profiles, the test and the comparator drug product should both be ‘‘rapidly dissolving,’’ which is defined as not less than 85% of API releases within 30 minutes, employing the dissolution conditions described therein. The same dissolution method was employed for evaluating randomly selected IR Ofloxacin drug products having a marketing authorization in USA and in India and we found that both formulations showing above 85% drug release within 30 minutes. Thus, it was found that the Ofloxacin drug products exhibited rapidly dissolving characteristics within the BCS limits.
DISCUSSION
Solubility
The USFDA defines ‘‘highly soluble drugs’’ exhibiting a dose/solubility (D/S) of <250 ml over the pH range 1–7.5, (3)(CDER, Guidance for Industry, 2000) while the EU and the recently revised WHO Guidelines limit the requirements to the pH range of 1–6.8. It was recently suggested that the USFDA should also redefine the solubility boundaries for BCS Class I (i.e high solubility and high permeability) to pH 1.2–6.8 (http://www.fda.gov/cder/foi/label/2007). At 250C, all tablet strengths conform to the criterion of 250 mL for the dose/solubility ratio at pH 6.8 and below (Table 1). At pH 7.5, the WHO recommended dose comply with this dose/solubility ratio criterion but higher tablet strengths do not. However, these data refer to 250C, not at 370C, as required by the Guidances3.
The solubility values found in the literature were not assessed under conditions specified for the Biopharmaceutics Classification System
(BCS) classification .Therefore new solubility determinations were carried out by us. The minimum solubility of Ofloxacin was about 2.66 mg/ mL. The corresponding dose/solubility (D/S) ratio, calculated for the highest commercially available tablet strength on the US market and on the WHO EML, was 150.38 mL or lower in the relevant pH range (Table 1). An API is ‘‘highly soluble’’ if its D/S ratio is below 250 mL 3. ( WHO, Proposal to waive in vivo bioequivalence requirements, 2006). Thus, ofloxacin can be regarded as ‘‘highly soluble”.
Permeability
According to BCS, a drug showing high solubility and high permeability is considered as Class‐1 drug. Ofloxacin is rapidly and well absorbed from the gastrointestinal tract. Oral bioavailability is almost 100% and a peak plasma concentration of 3 to 5 μg/mL is achieved 1 to 2 hours after a dose of 400 mg by mouth. Absorption may be delayed by the presence of food, but the extent of absorption is not substantially affected. The plasma half life ranges from 4 to 7 h in renal impairment values of 15 to 60 h have been reported. About 25% is bound to plasma proteins. Ofloxacin is widely distributed in body fluids, including the CSF and tissue penetration is good. It crosses the placenta and is distributed into breast milk. It also appears in bile.
There is limited metabolism to desmethyl and N‐oxide metabolites: demethylofloxacin has moderate antibacterial activity. Ofloxacin is eliminated mainly by the kidneys. Excretion is by tubular secretion and glomerular filtration and 65% to 80% of a dose is excreted unchanged in the urine over 24 to 48 h resulting in high urinary concentrations. Less than 5% is excreted in the urine as metabolites.
159
Sakore et al.
Int J Pharm Pharm Sci, Vol 2, Suppl 4, 156161
2
From 4 to 8% of a dose may be excreted in the faces (USFDA Drug approved information26, 27.
Ofloxacin is an amphoteric drug with two protonation sites. Its pKas are 6.05 for the carboxylic group and 8.22 for the piperazine nitrogen 28. The log P value (octanol/water partition coefficient) is 0.33 29. At blood pH, 87% of the drug is in the zwitterionic neutral form HQ +/‐ 28 .This form of the molecule is the most hydrophobic and can readily diffuse through membrane lipids 30 . Fluoroquinolones could have a common transporter in the intestine and, according to their affinities, compete with each other for binding when coadministered 31. investigated the effect of P‐glycoprotein blockers on intestinal ofloxacin elimination in rats. P‐glycoprotein is an energy‐dependent drug‐efflux system located at several sites, particularly at the plasma apical membrane of intestinal cells 31, 32. This transport molecule seems to protect intestinal cells from plant alkaloids and other cytotoxic hydrophobic compounds 33. The stereoselectivity and saturability of intestinal ofloxacin secretion in vivo 34.
Ofloxacin is a moderately lipophilic quinolone with an octanol‐water partition coefficient of 0.41 at pH 7.0, 0.33 at pH 7.2, and 0.28 at pH 7.3 35 ,36.After administration of ofloxacin 200mg I.V. Infusion the ratios OF AUCCSF/AUCs (csf: cerebro spinal fluid & s: serum) and AUCCSF 0‐∞/AUCs0‐∞ there was a high level of penetration of ofloxacin into CSF (0.59 to 0.81 and 0.53 to 0.79, respectively 37.
Ofloxacin is excellently absorbed and has a biological half‐life of 3 to 3.5hr, high volume of distribution, predominant renal elimination, and only limited biotransformation38 . In vitro Caco‐2 assay results concluded that ofloxacin was classified as high permeable drug 39. In TC7 cells, ofloxacin displayed concentration‐dependent permeability and was actively absorbed 40.
BCS classification
Ofloxacin is ‘‘highly soluble.’’Data on its oral absorption and permeability are not fully conclusive but suggest this API to be a BCS Class III drug, with permeability properties approaching the border to BCS Class I. It should be noted that the cut‐off for ‘‘highly permeable’’ varies with regulatory authority. The FDA sets a limit for the fraction of dose absorbed of not less than 90%, the EMEA requires ‘‘high permeability’’ but does not define a limit for the fraction of dose absorbed and the WHO requires not less than 85% fraction of dose absorbed. Up to now, the FDA does not accept biowaivers for BCS Class III APIs, which would exclude ofloxacin from biowaiving. On the other hand, the recently revised WHO guidance extended the possibility of a biowaiver approval to BCS Class III APIs under certain conditions. Therefore ofloxacin is a candidate for biowaiver according to the WHO guidance.
Surrogate techniques for in vivo bioequivalence testing
Ofloxacin is ‘‘highly soluble’’ and the pure drug shows ‘‘very rapid dissolution’’. Furthermore bioinequivalence of ofloxacin formulations was reported neither in vivo nor in vitro and is unlikely to occur for this very soluble API. Hence, the stricter dissolution methodology for biowaiving of BCS Class III drugs according the WHO Guidance, that is, ‘‘very rapid dissolution’’ over the pH range of 1.2–6.8, should be capable of detecting poor quality of formulations. A caveat to the use of dissolution tests as surrogates for in vivo BE testing is that in vitro dissolution tests are not able to detect excipient influences on permeability and/or GI transit time which may cause bioinequivalence 3 .
Risks of bioinequivalence caused by excipients and/or manufacturing
Since no report of a bioinequivalent drug product has appeared in the accessible literature, the risk of bioinequivalence of ofloxacin IR dosage forms seems to be low. The risk of bioinequivalence caused by an excipient interaction is further reduced if the test product contains only excipients present in drug products having a MA in an ICH or associated country. The excipients present in a number of European countries are listed in Table 1. Patient risks associated with bioinequivalence of ofloxacin IR dosage forms can lead to decreased antibiotic efficacy. However, the risk of bioinequivalence
of ofloxacin IR dosage forms appears to be relatively low, especially if the test product is formulated only with excipients shown in Table 2 and complies with the criteria for ‘‘very rapidly dissolving.’’
ACKNOWLEDGEMENT
The authors gratefully acknowledge Mrs. Nilam Patel (Formulation & Development, Cadila Pharmaceuticals Ltd, Ahmedabad, India) for her contribution.
REFERENCES
1. Amidon GL, Lennerna SH. Shah VP, Crison JR. A theoretical basis for a Biopharmaceutics Drug Classification: The correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res 1995; 12: 413–420.
2. Committee for Proprietary Medicinal Products (CPMP) London. The European Agency for the evaluation of Medicinal products, Evaluation of medicines for human use.. Note for guidance on the investigation of bioavailability and bioequivalence. Available from URL: 2001. http://www.emea.eu.int/pdfs/human/ewp/140198en.pdf.
3. U.S. Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER). Guidance for industry: Waiver of in vivo bioavailability and bioequivalence studies for immediate‐release solid oral dosage forms based on a Biopharmaceutics Classification System. 2000.
4. United States Pharmacopoeias, United States Phamacopoeial Convention. INC. Twin Brook Parkway. Rockville. 2004; p1355.
6. U.S. Department of Health and Human services Food and Drug Administration, Center for Drug Evaluation and Research, 1998. Freedom of Information. Available from: http://www.fda.gov/cder/foi/label/2007/019735s058lbl.pdf
7. Parfitt K. Martindale, The Complete Drug Reference. Edited by The Pharmaceutical Press, London, 1999; 32nded.
8. Henry AO, Ikhuoria MA. Analytical profile of the fluoroquinolone antibacterials I Ofloxacin. African J Biotech 2008; 7: 670‐680.
9. Barbosa J, Berges R, Sanz‐Nebot V. Retention behaviour of quinolone derivatives in high‐performance liquid chromatography. Effect of pH and evaluation of ionization constants. J.Chromatogr A 1998 ;823: 411‐422.
10. Fabre D, Bressolle F, Kinowski JM, Bouvet O, Paganin F, Galtier M. A reproducible, simple and sensitive HPLC assay for determination of ofloxacin in plasma and lung tissue. Application in pharmacokinetic studies. J Pharm Biomed Ana 1994;12: 1463‐1469.
11. Volpe DA, Ciavarella AB, Asafu‐Adjaye EB, Ellison CD, Faustino PJ, Yu LX. Method suitability of a Caco‐2 cell model for drug permeability classification. AAPS Pharm Sci 2001;3: (S1).
12. Pickerill KE, Paladino JA, Schentag JJ. Comparison of the fluoro‐quinolones based on pharmacokinetic and pharmacodynamic parame‐ters. Pharmacother 2000; 20: 417‐428.
13. Bergan, T.; Pharmacokinetics of fluorinated quinolones. In: Andri‐ole VT, ed. The Quinolones. London, UK: Academic Press. 1988. 119‐152.
14. Castillo‐garit J A, Marrero‐ponce Y, Torrens F, Garcia‐domenech R. Predicting Caco‐2 Cell Permeability Using Atom‐Based Stochastic and Non‐Stochastic Linear Indices. J Pharm Sci 2008; 97: 1946‐1976.
15. Akerle JO, Okhamafe AO. Influence of oral co‐administered metallic drugs on ofloxacin pharmacokinetics. J Antimicrob Chemother 1991; 28: 87‐94.
16. Shimada J, Shiba K, Oguma T, Miwa H, Yoshimura Y, Nishikawa T, et al. Effect of antacid on absorption of the quinolone lomefloxacin. Antimicrob Agents Chemother 1992;36: 1219‐1224.
17. Cabarga MM, Navarro AS, Gandarillas CL, Dominguez‐Gil A. Effects of two cations on gastrointestinal absorption of ofloxacin. Antimicrob Agents Chemother. 1991; 35: 2102‐2105.
18. Polk RE, Healy DP, Sahai J, Drwal L, Racht E. Effect of ferrous sulfate and multivitamins with zinc on absorption of
160
Sakore et al.
Int J Pharm Pharm Sci, Vol 2, Suppl 4, 156161
3
ciprofloxacin in normal volunteers. Antimicrob Agents Chemother 1989;33: 1841‐1844.
19. Flor SD, Guay RP, Opsahl JA, Tack K, Matzke GR. Effects of magnesium‐aluminum hydroxide and calcium carbonate antacids on bioavailability of ofloxacin. Antimicrob Agents Chemother 1990; 34: 2436‐2438.
20. Verho, M., Malerczyk, V., Dagrosa, E., Korn, A. The effect' of food on the pharmacokinetics of ofloxacin. Curr Med Res Opin 1986; 10: 166‐171.
21. Dudley MN, Marchbanks C R, Flor SC , Beals B. The effect of food or milk on the absorption kinetics of ofloxacin. Eur J Clinical Pharmacol 1991; 41: 569‐571
23. Van S, Nix DE, Wiltop JH, Love JH, Spivey JM, Goldstein HR. Combined use of ciprofloxacin and sucralfate. The Annals Of Pharmacotherapy 1991;25: 578‐582.
24. Bruce AM,. Effect of Enteral Feeding with Ensure on Oral Bioavailabilities of Ofloxacin and Ciprofloxacin. Antimicrob Agents Chemother 1994; 38: 2101‐2105.
25. Flor SC. Bioequivalence of oral and intravenous ofloxacin after multiple –dose administration to healthy male volunteers. Antimicrob Agents Chemother 1993;37: 1468‐1472.
27. McMullin CM. The pharmacokinetics of once‐daily oral 400 mg ofloxacin in patients with peritonitis complicating continuous ambulatory peritoneal dialysis. J Antimicrob Chemother 1997;39:29‐31.
28. Furet YX, Deshusses J, Peche`re JC. Transport of pefloxacin across the bacterial cytoplasmic membrane in quinolone‐susceptible Staphylococcus aureus. Antimicrob Agents Chemother 1992;36: 2506–2511.
29. Hirai K, Aoyama H, Suzue S, Irikura T, Lyobe S, Mitsuhashi S. Isolation and characterization of norfloxacinresistant mutants of Escherichia coli K‐12. Antimicrob Agents Chemother 1986;30: 248‐253.
30. Gruber GU. Jaehde SF, Relationships between the chemical structure and the HPLC capacity factor of gyrase inhibitors and their metabolites in different methanol‐water eluents. Fresenius Z Anal. Chem 1988;330: 388–389.
31. Croop JM, Raymond M, Haber D, Devault RJ, Arceci PG, Houseman DE. The three multidrug resistance genes are expressed in a tissue‐specific manner in normal human tissues. Mol Cell Biol 1989;9: 1346–1350.
32. Thiebaut F, Tsuruo T, Hamada H, Gottesman MM, Pastan I, Willingham M C. Cellular localization of the multidrug‐resistance gene product P‐glycoprotein in normal human tissues. Proc Natl Acad Sci U. S. A. 1987; 84: 7735–7738.
33. Ince P, Elliott K, Appleton DR., Moorghen M, Finney KJ, Sunter JP, et al Modulation by verapamil of vincristine pharmacokinetics and sensitivity to metaphase arrest of the normal rat colon in organ culture. Biochem Pharmacol 1991;41: 1217–1225.
34. Lyndia R. intestinal elimination of ofloxacin enantiomers in the rat:evidence of a carrier‐mediated process. Antimicrob Agent Chemother 1996; 40: 2126–2130.
35. Ashby J, Piddock LJV, Wise R. An investigation of the hydrophobicity of the quinolones. J Antimicrob Chemother 1985;16: 805‐808.
36. Takacs NK, Jozan M, Hermecz I, Szasz G. Lipophilicity of antibacterial fluoroquinolones. Int J Pharm 1992;79: 89‐96.
37. Nau R. Pharmacokinetics of ofloxacin and its metabolites in cerebrospinal fluid after a single intravenous infusion of 400 mgs of ofloxacin. Antimicrob Agents Chemother 1994;38: 1849‐1853.
38. Hartmut I, Pharmacokinetics of ofloxacin after parenteral and oral administration. Antimicrob Agents Chemother 1987;31:1338‐1342.
39. Donna A, Volpe E. Permeability Classification of Representative Fluoroquinolones by a Cell Culture Method. AAPS Pharm Sci 2004; 6(2): Article 13.
40. Awadallah B, Wahl MA. Transport of ofloxacin enantiomers in the Caco‐2‐TC7 cell line. AAPS Pharm Sci 2002; 4 (S1).
161
About SIPS Saraswati Institute of Pharmaceutical Sciences was established in 2006 under the auspices of Shree Saraswati Education Sansthan. The institute is situated in a green and clean environment at Dhanap, 10 kms away from Gandhinagar. The college is affiliated to Gujarat Technological University, approved by AICTE & PCI. The college possesses a very good infrastructure with highly equipped laboratories and state of the art equipments. SIPS conducts following courses :
About Seminar A drug molecule has to pass through various phases before reaching market and all the disciplines of pharmaceutical sciences play a vital role in this process. Looking at the increasing number of biological targets identified for various diseases it is the need of the hour to not only have efficient and fast methods of chemical syntheses but also to have man power with good analytical skills along with a good working knowledge of specific screening techniques. Researchers have to keep themselves abreast of recent developments in the area of drug discovery and development. We have planned to have eminent speakers with ability to appeal to a multidisciplinary audience. Such symposiums are an essential part of an academic curriculum for motivating the young minds towards scientific research.
Objectives To bring together academicians and industrialists of multi-disciplinary areas for deliberations on recent research methodologies.
Symposium Schedule
24 - 9 - 2011 Registration and Inauguration 9:30-10:15 am Plenary Session Dr. M.R. Yadav 10:30-11:30 am Professor & Head, Department of Pharmacy , The Maharja Sayajirao Univ. of Baroda, Vadodara Title: Application of Spectrophotometric
Techniques in Pharmacy Field Dr. I.S. Anand 11:30-12:30 pm Professor and Head, Dept. of Pharmacology, Shree Sarvajanik Pharm. College, Mehsana. Title : Overview of Drug Discovery & Development Dr. ShitalKumar Zambad 12:30-1:30 pm AGM Department of Pharmacology , Torrent Research Centre. Gandhinagar. Title: GLP 1 Secretagogues: Advancing therapy for Type 2 Diabetes Lunch Break Dr. M.T. Chabbaria 2:30-3:30 pm Associate Professor, L.M. College of Pharmacy, Ahmedabad Title : Drug Design‐Serendipity to Success Mr. Somnath Sakore 3:30-4:30 pm Assistant Manager –CRO Cadila Pharmaceuticals Ltd. Ahmedabad Title: In Vitro In Vivo Co‐relations ‐ A tool in Drug Development
Valedictory
Symposium on
“Novel Technologies to Expedite Drug Discovery and Development”
In-Vitro-In-Vivo Correlation (IVIVC): A Tool In drug Development
Mr. Somnath SakoreCadila Pharmaceuticals Ltd
Symposium on Novel Technologies to Expedite Drug Discovery and
Development
Outline• Definition of IVIVC • Purpose of IVIVC• Levels of IVIVC• In vitro data • In vivo data• IVIVC models• IVIVC development• Predictability • IVIVC in drug development of extended release products• Issues• Factors to be consider for correlation development • Conclusion
ISSN 2229-5054 International Journal of Drug Formulation & Research Nov-Dec. 2010, Vol. 1 (iii) 324-348
Available online on www.ordonearresearchlibrary.org
324
International Journal of Drug Formulation & Research
LONG ACTING IN SITU GELLING VEHICLE FOR PHTHALMIC DELIVERY
Vandamme developed poly (amidoamine) (PAMAM) dendrimers for controlled ocular drug
delivery of pilocarpine and tropicamide [76]. Devarakonda designed Polyamidoamine (PAMAM)
Dendrimers for Water-Insoluble Nifedipine [77]. Marano et al have have performed a long-term
study into the use of a lipophilic amino-acid dendrimer to deliver an anti-vascular endothelial
growth factor (VEGF) oligonucleotide (ODN-1) into the eyes of rats and inhibit laser-induced
choroidal neovascularization (CNV) [78]. The polymer micelle is a particle fundamentally formed
with a hydrophilic polymer chain as a shell and a hydrophobic polymer chain as core. The drug
delivery system of the invention can be effectively applied to photodyanamic therapies, when a
photosensitive drug used as a drug and can be subjected to therapy for age related macular
degeneration through occluding choroidal new vessels [79].
7. Solid dosage forms Ocular inserts
Films, erodible and nonerodible inserts, rods shields are the most logical delivery systems
aimed at remaining for a long period of time in the front of the eye, listed in table 2 [86-94].
Table2 various ocular inserts: Name Description SODI (soluble ocular drug insert) [86] of a soluble acrylamide, N-
Small oval wafer, composed Co-polymer consisting of vinyl pyrrolidone and ethyl softens on insertion
NODS(New or novel ophthalmic delivery system)[87]
Medicated solid polyvilnyl alcohol flag that is attached to a paper covered handle, an application flag detaches and gradually dissolves, releasing the drug.
Collagen shields [88] Erodible discs composed of crosslinked porcine scleral collagen. Ocusert [89] Flat, flexible elliptical insoluble device consisting of two layers enclosing a
reservoir, used commercially to deliver pilocarpine for 7 days. (OTS) Minidiscs or ocular therapeutic system [90]
4-5 mm diameter contoured either hydrophilic or hydrophobic disc.
Lacrisert [90] Rod shaped device made from hydroxy propyl used in the treatment of dry eye syndrome as an alternative to artificial tears.
Ophthalmic inserts [91] A cylindrical device containing mixtures of silicone elastomer and sodium chloride as a release modifier with a stable polyacrylic acid (PAA) interpenetrating polymer network grafted on to surface
Bioadhesive ophthalmic drug insert ( BODI) [92]
Adhesive rods based on mixtures of hydroxypropyl hydroxypropyl cellulose ethyl cellulose, polyacrylic acid, cellulose acetate phthalate.
Dry drop [93] A preservative free drop of hydrophilic polymer solution (hydroxyl propyl methyl cellulose) that is freeze dried on the tip of a soft hydrophobic carrier strip, immediately hydrates in the tear film.
Gelfoam [94] Slabs of Gelfoam Impregnating with mixtures of drug and cetyl ester wax in chloroform.
Sangita D.kute* et al. /International Journal Of Pharmacy&Technology