Analytical Issues in Process Development – QdB Prof. Attilio Citterio Dipartimento CMIC “Giulio Natta” http://iscamap.chem.polimi.it/citterio/dottorato // PhD IN INDUSTRIAL CHEMISTRY AND CHEMICAL ENGINEERING (CII)
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Analytical Issues in Process Development – QdBProf. Attilio CitterioDipartimento CMIC “Giulio Natta”http://iscamap.chem.polimi.it/citterio/dottorato//
PhD IN INDUSTRIAL CHEMISTRY AND CHEMICAL ENGINEERING (CII)
Attilio Citterio
Sampling
• Sampling methodology (analytical sample must be representative of the whole batch)
• Can be a problem with large batches• Variations can occurs due to
- Position in filter, centrifuge or drier, leading to different amount of solvent
- inadequate agitation in vessels causing non-uniform reactions- Differences in heating (e.g. baking on sides of reactor) may cause
variations in level of impurities- Physical contamination- Non-uniform particle size
• Before sampling final products should be sieved to ensure uniformity
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In-Process Checks
Sampling is the greatest source of error Require semi-quantitative (or better quantitative)
methods for following reactions- Analyse starting materials and products quantitatively- Do they total 100%?- Are there transient intermediates?
Analyse during work-up Analyse upper and lower layers in separations Avoid derivatising methods where possible
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n-BuLi
AlCl3
Cl
Cl
O
O
O
O
O
O Cl
Cl
O
CO2H
BF3 MeOH
ClO
CO2H
ClCl
Cl
O
CO2MeCl
O
CO2Me
Cl
+
(95%) (5%)
Derivatizing Problem
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Analytical Methodology
• Develops alongside synthetic work• Assay and impurity profile• Reference samples• Isolation and characterization of impurities• Quality control as chemistry changes• Need to review methods in the light of new information
Reference Standards• Required early in the development process to determine response
factors• For each step standards are needed for main product and impurities• Primary reference standard - highly purified• Working reference standard - a typical batch whose purity has been
measured against the primary reference
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Specifications
• Bulk drug product must meet high specifications- No opportunity for later upgrading
• Other chemical products should also have high specifications where this is practicable
• Raw materials and intermediates may have looser specifications- Chemical processing tends to remove impurities
BUT- This should be investigated and demonstrated on a case-by-case
basis
• The ultimate purpose of all specifications is a high quality final product
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Problems Arising from Impurities
May be carried through the synthesis- e.g. positional isomers, homologues
May catalyse side-reactions- e.g. acids in aldehydes
May poison metal catalysts in later steps- e.g. sulphur compounds
Will demand considerable effort- Isolation, analysis, investigation of fate
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formaldehyde +HN N HN N
OH
HN N
OH
HN N
OH
+
OH
HN N
SHN NHMe
NCN
+ isomers & bis adducts
Isomers are Critical
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HN N
SHN NHMe
NCN
Impurities in cysteamineImpurities in methylamine, e.g. dimethylamineimpurities in cyanamide, e.g. dicyanamide
For a final drug, it would be important to check for the absence of these compounds
Isomers are Critical
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CHOHO
MeO
CHOHO
MeO
+CHOHO
MeO
Cl Br
Chlorine
Analysts need assistance from organic chemists to decide what to look for and in synthesis of potential impurities.
GC-MS or HPLC-MS are useful in identifying small peaks in chromatograms.
Isomers are Critical
Bromine in chlorine - bromine is only a small amount but reacts fast:
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Key raw material
Possible impurities
Likely to be carried through synthesistight spec required
Unlikely to react furtherlarge amounts (e.g. 5%)may be tolerated
HO
MeO
MeO
OH
MeO
OH
MeO
S S
OMe
Evaluation of Impurities
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Na2Cr2O7
Main product
N N
O +N CO2H
O
N
O
impurity
Unexpected Impurities
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Evolution of RM Specifications
Early laboratory syntheses
Accept supplier’s spec
Note supplier and lot number with all experiments
Perform simple identity tests (IR, melting point) and record results
Retain a small sample of each lot for possible testing later
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Evolution of Specifications
First clinical batches or bio-batches
Formal system of sampling and analysis Must set tentative specifications Test against supplier’s specifications Consider if tighter specifications are required Develop test methods which are specific for the
compound Use tests
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Certificates of Analysis
Obtain supplier’s C. of A. for all raw materials
Most suppliers need constant reminding to send C. of A.
Do not rely on C. of A. alone- Supplier’s specs may be inappropriate for the intended use- Manufacturer may change process without notification- Assay figures may come from non-specific methods, e.g. titrations - Material may have deteriorated in storage or in transit
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Water
Specifications for water-quality required, especially for later processing steps- chemical and biological quality to be assured
Distillation and deionizing units should be avoided- Provide ideal conditions for microbial growth- Require complicated sterilisation & validation
Potable mains water suitable for most chemical processing
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Hazardous Raw Materials
Some materials are too dangerous to be sampled or analysed under normal laboratory conditions e.g. Bromine, sodium hydride, fuming nitric acid
For these, a certificate of analysis from the supplier will be sufficient
There should still be evidence that the identity of the substance has been assured as far as possible, if only from its appearance
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Final Product and Key Intermediates
Appearance - Colour check, visible spectrum?
Identity - usually by IR spectrum
Assay - By HPLC, HPTLC, GC etc
Impurity profile - By HPLC, HPTLC, GC
Solvents, incI. H2O - Loss on drying
Specific tests (GC, NMR, KF)
Other purity checks - Microanalysis, NMR, MS
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Final Product and Key Intermediates
Inorganics - Sulphated ash or ROI- IR for ammonium salts- Specific tests for metals (AA)- Anion analysis
Crystal form - Melting point- DSC- Particle size analysis
Optical purity - By methods other than rotation- NMR, GC, HPLC- Avoid derivatization if possible
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Final Drug Specifications
Assay 98 -102%(possibly 99-101%)
Impurities- Specific, named <0.5%- Unknown <0.1 %- Total <2.0%
Ash < 0.2%
Heavy metals <20 ppm
Solvents <0.2%but lower for specific solvents
Crystal form as required
Particle size as required
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Impurities in Drug Substance
Alt impurities > 0.1% w/w to be identified and characterised
All impurities > 0.01% w/w to be identified if possible- If not possible - designate by e.g. TR
Toxicity data required for impurities- from studies on isolated impurity OR- from studies on drug substance lots containing typical levels of the
impurity Impurity content may be estimated from area
normalisation- Response factors must be known and taken into account
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Impurities in Drug Substance
Levels of toxic or carcinogenic impurities may have to be set lower than 0.5%- < 0.1% of minimum toxic dose in daily dose of drug product.
ExampleDaily dose of drug substance - 100 mgMinimum toxic dose of impurity - 20 mgMaximum permitted impurity level -20 mg / 100 mg x 0.1% = 0.02%
For carcinogenic impurities, level to be reduced by at least one further power of ten
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Impurity Identification Programme
Identify impurities >0.1 %- Isolation by prep. HPLC or prep. TLC- Chromatographic comparison with samples of known compounds
Prepare reference samples (ca. 59) and obtain response factors- Chromatographic isolation- Independent synthesis
Repeat for remaining impurities >0.01% - GC/MS may help in identification
Synthesise potential impurities and check - against chromatographic system
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Class 1 Solvents in Pharmaceutical Products
(solvents that should be avoided)
Solvent Concentration Limit Concern(ppm)
Benzene 2 CarcinogenCarbon tetrachloride 4 Toxic and
environmental hazard1,2-Dichloroethane 5 Toxic1,1-Dichloroethene 8 Toxic1,1,1-Trichloroethane 1500 Environmental hazard
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(solvents to be strongly limited)
Solvent PDE Concentration Limit(mg/day) (ppm)
Acetonitrile 4.1 410Chlorobenzene 3.6 360Chloroform 0.6 60Cyclohexane 38.8 38801.2-Dichloroethene 18.7 1870Dichloromethane 6.0 6001,2-Dimethoxvethane 1.0 100N,N-Dimethylacetamide 10.9 1090N,N-Dimethylformamide 8.8 8801.4-Dioxan 3.8 3802-Ethoxyethanol 1.6 160
Class 2 Solvents in Pharmaceutical Products
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Solvent PDE Concentration Limit(mg/day) (ppm)
Ethylene glycol 3.1 310Formamide 2.2 220Hexane 2.9 290Methanol 30.0 30002-Methoxyethanol 0.5 50Methylbutylketone 0.5 50Methylcyclohexane 11.8 1180N-Methylpyrrolidone 8.4 4840Nitromethane 0.5 50Pyridine 0.2 200Sulfolane 1.6 160Tetraiin 1.0 100Toluene 8.9 8901.1.2-Trichloroethene 0.8 80Xylene* 21.7 2170
*usually 60% m-xylene. 14% p-xylene, 9%o-xylene with 17% ethyl benzene.
Class 2 Solvents (2)
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(solvents with low toxic potential)
Acetic acid Ethyl acetate Methylethyl ketoneAcetone Ethyl ether Methylisobutyl ketoneAnisole Ethyl formate 2-Methyl-1-propanol1-Butanol Formic acid Pentane2-Butanol Heptane 1-PentanolButyl acetate Isobutyl acetate 1-Propanoltert-Butylmethyl ether Isopropyl acetate 2-PropanolCumene Methyl acetate Propyl acetateDimethylsulfoxide 3-Methyl-1-butanol TetrahydrofuranEthanol
Class 3 Solvents Limited by GMP or other Quality based requirements
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1,1-Diethoxypropane Methylisopropyl ketone1,1-dimethoxymethane Methyltetrahydrofuran2,2-dimethoxypropane Petroleum etherIsooctane Trichloroacetic acidIsopropyl ether Trifluoroacetic acidEthyl lactate
Manufacturers should supply justification for residual levels of these solvents in pharmaceutical products.
Solvents without Adequate Toxicological Data
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Good Manufacturing Practice
“That part of Quality Assurance aimed at ensuring products are consistently manufactured to the quality appropriate to their intended use.”
Code of Practice to BS 5750 Pt 2 (1987), P3.8
• Should get right result every time• No “Acceptable Quality Limits”• No undue reliance on Final Testing• Quality cannot be tested into the product
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Gimme More Paper!
SOPs Training Records Equipment Logs Inventory Control Qualifications Validations Batch Records
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Process Validation
“Establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its predetermined specifications and quality attributes.”
MATERIALS+
EQUIPMENT+
PROCEDURES+
BUILDINGS+
PERSONEL
= PROCESSES
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Process Validation
Comes late in the development process All reagents, solvents, stoichiometries have been fixed
- i.e. process has been optimised
Understanding of each process step is vital- What can go wrong?- How robust is the process?- What happens if reaction conditions changed slightly?
Statistical designs may help convince authorities that quantitative evaluation of parameters has been carried out
Concentrate on later stages initially and work back
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Process Validation
For each process stage Define raw materials and conditions Determine CRITICAL parameters and set limits Determine worst case within limits Determine edge-of-failure limits View each step deeply Define monitoring strategy Set standard yields and a variance
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Process Validation
Scale-Up - need to prove that quality and yield do not change
Documentation, recording info in lab and plant In-process analysis QC on intermediates Specifications on intermediates Development reports Justification for changes to parameters during
development Combining steps more difficult
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DEFINEPRODUCT
ATTRIBUTES
DEFINEPROCESS
STEPSDEVELOPPROCESS
VERIFYPROCESS
DESIGNEQUIPMENT
FACILITYINSTALL
EQUPMENTQUALIFY
EQUPMENT
ONGOINGSYSTEM
ANALYSIS
TESTINTEGRATED
SYSTEMINTEGRATE
SYSTEM
TESTPROCESS
STEPS
DATADATA ANALYSIS
Process Validation Cycle
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Validation Procedure
• Prepare validation protocol in advance- Detailed instructions for steps to be validated- Acceptance criteria at appropriate points
• Perform process at least 3 times consecutively
• All predetermined specifications and criteria must be met each time
• Inexplicable failures render the process invalid- Applies also to subsequent batches
• Material produced in the course of a successful validation may be used further
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Retrospective Validation
May be applied to processes which have been operated successfully over a long period
Prepare detailed description of process as described before for prospective validation
Justify process by reference to existing historical data from previous batches
Consider at least thirty consecutive batches Demonstrate that the process has not changed
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Change Control
Process changes should be anticipated- New equipment- New suppliers for raw materials- More efficient chemistry
Formal system for handling changes- SOP- All changes documented- Review to assess potential impact on quality
Minor changes require little further action- Evaluation of batches produced by new method
Major changes require revalidation
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Validation and Development
• R&D processes cannot themselves be validated
• Development chemist must be aware that process must eventually be validated for manufacturing
• Development chemists provide much of the data for validation reports- Choice of synthetic route- Detailed processing steps- Critical parameters- Identification and control of impurities
• Validation begins with earliest clinical batches
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Edge of failure limits
Proven acceptable range
Normaloperating
range
Optimumcritical parameter
Operating Zone Diagram
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Setting Ranges for Process Parameters
Vital part of validation procedure
generated by experiment, not during the validation runs
Development work must define for each “critical parameter”
- Normal operating range- Validated range- Edge of failure limits
Validation runs confirm these results
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Setting Ranges for Process Parameters
• What can the process tolerate?- Quality considerations- Economic considerations- Environmental considerations- Safety considerations
• What can the plant equipment achieve?- Anything is technically possible, but at at price
• Set normal operating range narrowly around optimum conditions
• Set validated range as wide as possible without compromising quality
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Justification of Operating Ranges
The wider the range the more difficult it is to justify experimentally
The more parameters involved the more complicated it becomes
Cannot test every possible combination of values Cannot assume that worst case occurs at the limit of the
domain Can use Response Surface Analysis to find worst case
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Process Analytical Technology (PAT)
Process control trough new technologies (innovations), focus on manufacturing scienceA system for designing (process development), analyzing and controlling manufacturing processes, based on timely measurements of critical Q & performance attributes of raw-materials, in-process materials and processes with the goal of ensuring final product Q.Processes to assure acceptable end-product Q at the completion of the process (quality by design)Focus of PAT is understanding
PAT tools: process analyzers multivariate tools for design, data acquisition, anal. process control tools continuous improvement/knowledge management tools
Continuous Quality Verification
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PAT & closing the loop
Process outputProcess feed
hold
rele
ase
LIMS
LabProcess
Close loop control (physical / chemical
parameters only)
Temp., pH, pO2, pressure, …
Temperature, pH, pO2pressure
Product
M
Bio-reactor
Advanced Process Control
PAT
Process Analyzer
QualitativeFingerprint
Monitoring
Quality build in by design
Right first time
Real-timerelease
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The Regulatory changes impacting R&D and Manufacturing
Today Vision
New initiatives to:improve manufacturing qualityaccelerate developmentLower the regulatory burden
FDA new principles:Quality by design & design space Quality systems approachReflecting product & process understanding and knowledge
FDA’s focus:Keynote address at IFPAC February 2007, by FDA's Chief Medical Officer, Dr. Janet Woodcock, on
Development & manufacturing should be integratedDevelopment of quality surrogates for clinical performance(link critical product attributes to clinical outcomes)rigorous, mechanistically based and statistically controlled processes
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The PAT Implementation Roadmap
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Select Appropriate Process Analyser
Laser diffraction
Spectroscopy
RamanSpectroscopyNMR
Spectroscopy
IRSpectroscopy
WeighingTechnology
Level
Flow
Liquid Analytics
Laser Diode Spectrom.
Temperature
Positioners
PressureGas
Analytics
Gas Chroma-tography
NIR Spectrosco
py
Mass Spectroscopy
ProcessAnalytics
Chemometrics/ MVDA DoE
Information management
tools
Data Modelling/
Mining
Product & processdesign regulatory
(advanced)Controls
PAT Toolbox
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In situ NIR Analysis
Concentration monitoring with NIR
time
Amou
nt in
%
TBP additionAzide
Intermediate
Amine
AmineTBP or intermediate
50 100 150 200 250-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
Reduction of an azide to amine by Tri-n-butylphosphine
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Chemical Imaging
A picture says more than 1’000 words
Dissolution Problem: too much Mg stearate at the surface
Pixels
Pixe
ls
10 20 30 40 50 60
10
20
30
40
50
60
Pixels
Pixe
ls
10 20 30 40 50 60
10
20
30
40
50
60
GOOD SAMPLES BAD SAMPLESPC3 : Active
GOOD SAMPLES BAD SAMPLESPC2 : Magnesium stearate
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Measurements Across the Process
• Reaction monitoring• Blending and mixing• Fermentation• Drying
Process Monitoring
UV and NIR optical fibers
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NeSSI as Enabling technology for...
• Miniature physicalsensors
• Miniature chemicalcomposition sensors
Panametrics & Swagelok
Courtesy of Applied Analytics
Porter Instruments and the Swagelok Co.
Rosemount Analytical
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The Qualitative Fingerprint
Process data
NIR spectral data
End-product Quality data
Temp., pH, pO2, pressure, …
LIMS
QualitativeFingerprint
MVDA(PCA)
MVDA(PCA)
MVDA(PLS)
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Quality by Design (QbD)
• Systematic approach to development• Begins with predefined objectives • Emphasizes product and process understanding and
process control• Based on sound science and quality risk management
from ICH Q8(R1)
FDA Initiatives: “Pharmaceutical Quality for the 21st Century” - Final report 2004 – Objective:“A maximally efficient, agile, flexible pharmaceutical manufacturing sector that reliably produces high-quality drug products without extensive regulatory oversight”.
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Elements of QbD
Define desired product performance
upfront;identify product CQAs
Design formulation and process to meet
product CQAs
Understand impact of material attributes
and process parameters on product CQAs
Identify and control sources of variability
in material and process
Continually monitor and update
process to assure consistent quality
Risk assessment and risk control
Product & process design and development
Qualityby
Design
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Recent Quality Guidance and Initiatives (FDA)
INITIATIVES
2004 2005 2006 2007 2008 2009
GUIDANCE
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Example QbD Approach (Q8R1)
• Target the product profile
• Determine critical quality attributes (CQAs)
• Link raw material attributes and process parameters to CQAs and perform risk assessment
• Develop a design space
• Design and implement a control strategy
• Manage product lifecycle, including continual improvement
Product profile
CQAs
Risk assessment
Design space
Control strategy
ContinualImprovement
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Design Space
Definition The multidimensional combination and interaction
of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality
Regulatory flexibility Working within the design space is not considered a change
Important to note Design space is proposed by the applicant and is subject to
regulatory assessment and approval
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Design Space Determination
First-principles approach combination of experimental data and mechanistic knowledge of
chemistry, physics, and engineering to model and predict performance
Non-mechanistic/empirical approach statistically designed experiments (DOEs) linear and multiple-linear regression
Scale-up correlations translate operating conditions between different scales or pieces
of equipment Risk Analysis
determine significance of effects Any combination of the above
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Design Space Example
• Design space proposed by the applicant• Design space can be described as a mathematical function or
simple parameter range• Operation within design space will result in a product meeting the
defined quality attributes
40
50
600
1
250.055.060.065.070.075.080.085.090.095.0
100.0
Diss
olut
ion
(%)
Parameter 1Parameter 2
40 42 44 46 48 50 52 54 56 58 600
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Dissolution (%)
Parameter 1
Parameter 2
90.0-95.085.0-90.080.0-85.075.0-80.070.0-75.065.0-70.060.0-65.0
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Design Space and Quality Control Strategy
Process (or Process Step)
Design Space
Monitoring ofParametersor Attributes
Process Controls/PAT
InputProcess
Parameters
Input Materials
Product (or Intermediate)
ProductVariability
ReducedProductVariability
ProcessVariability
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Quality Risk Management Process (Q9)
ProcessDevelopment
Control StrategyDevelopment
Continual Improvement
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Role of Quality Risk Management inDevelopment & Manufacturing
ManufacturingProcess Scale-up & Tech Transfer
Quality Risk Management
Process Development
Product Development
Product qualitycontrol strategy
RiskControl
RiskAssessment
Process design space
ProcessUnderstanding
Excipient & drug
substance design space
Product/prior Knowledge
RiskAssessment
Continualimprovement
ProcessHistory
RiskReview
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Example Control Strategy forReal Time Release Testing
Tablet Compression
Pan CoatingSifting Roller
compactionBlending
Raw materials & API dispensing• Specifications
based on product
NIR MonitoringBlend Uniformity
Laser DiffractionParticle Size
Dispensing
NIR Spectroscopy(At-Line) • Identity• Assay • API to Excipient
ratio
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Business Drivers
Company Image Reduced risk via
technology platform, anti-counterfeiting Improved product tracking Reverse poor image Improved quality system thought audits Reduced risk for recall, warning letter,
consent decree
Validation Optimization Validation needs understanding Integral part of project Built validation into process
Improve Existing Process
Gain new process understanding Process optimization Reduced cost of quality Raw material specifications Know product availability + yield Real Time Release
New Product Development Real Time Release (RTR) Fast time to market Fast scale-up Clinical batches Process optimization Reduced cost of quality
End of life-cycle Transferability of process Scale down
Site to Site transfer Accelerate transfer Reduce validation effort Reduce project time Mitigate transfer risk Move manufacturing to most
effective site
PAT/QbD
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Miniaturized Analytical Equipments
Fast GC is a chip-based instrument with an integrated Thermal Conductivity Detector. A tiny and easy exchangeable GC cartridge (60*100*12.5 mm) contains injector, detector, column and heating capability up to 180°C.C2V focuses on natural gas, oil and process applications, e.g., a BTU analysis is done in less than 20 seconds.
Thermo Fisher Scientific
Micro NMRspectrum of a 3 micro liter water sample using a RF micro coil
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Conclusion
• Development chemists must make a large contribution to the validation and design effort
• To ensure smooth validation at end of line, project must be well organised from the beginning by QbD techniques based on risk analysis
• Development reports are vital- Summarise efforts over a time period- Summarise work on a particular area- Collate raw data and put it in context- Provide justification for the process to be validated
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