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Birgit Schmauser | April 2008 1 |1 | Pharmaceutical Development with Focus on Paediatric formulations WHO/FIP Training Workshop Hyatt Regency Hotel Sahar.

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Presentation on theme: "Birgit Schmauser | April 2008 1 |1 | Pharmaceutical Development with Focus on Paediatric formulations WHO/FIP Training Workshop Hyatt Regency Hotel Sahar."— Presentation transcript:

1 Birgit Schmauser | April |1 | Pharmaceutical Development with Focus on Paediatric formulations WHO/FIP Training Workshop Hyatt Regency Hotel Sahar Airport Road Andheri East, Mumbai, India 28 April 2008 – 2 May 2008

2 Birgit Schmauser | April |2 | Analytical Method Development Presented by: Birgit Schmauser, PhD Federal Institute for Drugs and Medical Devices (BfArM)

3 Birgit Schmauser | April |3 | Analytical Method Development In this presentation: Standards in developing analytical methods for Standards in developing analytical methods for –Originator and multisource generic FPPs Specifications Specifications Stability Stability Parallel development of analytical methods for cleaning validation Parallel development of analytical methods for cleaning validation

4 Birgit Schmauser | April |4 | Analytical Method Development Originator, First-time Generic and Multisource Generic Originator, First-time Generic and Multisource Generic Multisource Generic First-time Generic Originator Pharmacopoeias Information from regulatory agencies (publicly available) & literature data Originator´s specifications API quality standards Pharmacopoeias Information from regulatory agencies (publicly available) & literature data Originator´s specifications FPP quality standards Verify identity, potency, purity of API and FPP by pharmacopoeial methods and in-house methods Derive identity, potency, purity of API and FPP by in house methods Establish identity, potency, purity of API and FPP by in-house methods Analytical methods

5 Birgit Schmauser | April |5 | Analytical Method Development HPLC-method to assay potency and purity – risk assessment HPLC-method to assay potency and purity – risk assessment Multisource Generic First-time Generic Originator Selectively screen/detect any impurity or degradant Establish potency Identify impurities/degradants Verify impurities from Pharmacopoeia Characterise „in-house“ impurities/degradants (Response factors) Derive impurities/degradants from Originator Characterize „in-house“ impurities/degradants Calculate response factors Characterise all impurities/degradants Calculate Response factors (qualification by clinical use) Use pharmacopoeial reference materials Extract (& reproduce) reference materials Establish reference materials „Implement“ for routine use Adapt/modify to/for routine use Adapt to routine use

6 Birgit Schmauser | April |6 | Analytical Method Development Interchangeability (IC) of multisource generic FPPs (Essential similarity with Innovator FPP) (Essential similarity with Innovator FPP) Pharmaceutical + Bioequivalence Equivalence Pharmaceutical + Bioequivalence Equivalence IC = PE + BE IC = PE + BE

7 Birgit Schmauser | April |7 | Analytical Method Development Pharmaceutical equivalence Pharmaceutical equivalence –FPPs meet the same or comparable standards by use of equivalent analytical methods Same API ( chemical and physical equivalence)Same API ( chemical and physical equivalence) Same dosage form and route of administrationSame dosage form and route of administration Same strengthSame strength Comparable labelingComparable labeling –Equivalence in pharmaceutical development –Equivalence in stability –Equivalence in manufacture (WHO-GMP)

8 Birgit Schmauser | April |8 | Analytical Method Development Prequalification requirements Prequalification requirements –Validation of analytical methods is a prerequisite for prequalification of product dossiers Non-compendial APIs and FPPs are tested with methods developed by the manufacturer Non-compendial APIs and FPPs are tested with methods developed by the manufacturer For compendial APIs and FPPs the „applicability“ of pharmacopoeial methods to particular products must be demonstrated (verification) For compendial APIs and FPPs the „applicability“ of pharmacopoeial methods to particular products must be demonstrated (verification) –Analytical methods must be developed and validated according to TRS 823, Annex 5, Validation of analytical procedures used in the examination of pharmaceutical materials; ICH Q2 (R1) –Analytical methods must be developed and validated according to TRS 823, Annex 5, Validation of analytical procedures used in the examination of pharmaceutical materials ; ICH Q2 (R1) To be used within GLP and GMP environments To be used within GLP and GMP environments

9 Birgit Schmauser | April |9 | Analytical Method Development METHODSPHARMACEUTICALCLINICAL At initial phase of pharmaceutical development To understand the profile of related substances and to study stability To start measuring the impact of key product and manufacturing process parameters on consistent FPP quality To develop a stable and reproducible formulation for the manufacture of bioequivalence, dissolution, stability and pilot-scale validation batches To determine bioavailability in healthy volunteers At advanced phase of pharmaceutical development To be robust, transferable, accurate and precise for specification setting, stability assessment and QC release of prequalified product batches To optimise, scale-up and transfer a stable and controlled manufacturing process for the prequalification product To prove bioequivalence after critical variations to the prequalified dossier Use of analytical methods - generics

10 Birgit Schmauser | April | Analytical Method Development Prerequisites for analytical method validation Prerequisites for analytical method validation –Six “M”s Quality of the analytical method M an M achine qualified calibrated robust qualified M ethods suitable characterised documented M ilieu M aterial M anagement Quality Reference standards Tempe- rature Analysts´ support skilled Humidity Vibrations Time Supplies Irradi- ations

11 Birgit Schmauser | April | Analytical Method Development Method development life cycle Method development life cycle Planning Development and Validation Policy Objectives/Requirements of Method Information Gathering Resource Gathering Method development Initital Method Development Pre-Validation Evaluation Method Optimization Robustness System Suitability Development Plan – Project Customer Evaluation Testing Validation Experiments Method Transfer Experiments Filed Method in Use Periodically Monitoring/Review of Methods in Control Labs From: Analytical Chemistry in a GMP Environment. Edited by J.M. Miller and J.B. Crowther, ISBN , Wiley & Sons Inc.

12 Birgit Schmauser | April | Analytical Method Development Validation should verify the suitability of an analytical method for its intended purpose Validation should verify the suitability of an analytical method for its intended purpose Validation should be founded on method development performed beforehand that suggest the suitability and robustness of the method Validation should be founded on method development performed beforehand that suggest the suitability and robustness of the method Validation may be performed in different ways (individual purpose) according to common standards Validation may be performed in different ways (individual purpose) according to common standards

13 Birgit Schmauser | April | Validation protocol Validation protocol –Method principle / objective –Listing of responsibilities Laboratories involved and their role in the validation Laboratories involved and their role in the validation –Method categorization –List of reagents (including test lots) and standards –Test procedures to evaluate each validation parameter and proposed acceptance criteria –Plan or procedure when acceptance criteria are not met –Requirements for the final report The validation process cannot proceed until the protocol and all parties involved approve the acceptance criteria The validation process cannot proceed until the protocol and all parties involved approve the acceptance criteria

14 Birgit Schmauser | April | Analytical Method Development Innovator versus Generics Innovator versus Generics GenericsInnovator -+ R & D on API -+ Preclinical trials - Method validation summary Clinical trials phase I and II - Method validation completed Clinical trials phase III - Validated methods Post marketing phase IV Validated methods: GMP and GLP Validated methods Entering of Generics; Pharmaceutical development, Comparability with Innovator

15 Birgit Schmauser | April | Analytical Method Development Validation Characteristics Validation Characteristics AssayImpuritiesIdentification limitquantitative Accuracy Precision Specificity Detection Limit Quantitation Limit Linearity Range Robustness

16 Birgit Schmauser | April | Analytical Method Development Accuracy and precision Accuracy and precision Accurate & precise Accurate & imprecise Inaccurate & precise Inaccurate & imprecise

17 Birgit Schmauser | April | Analytical Method Development Precision Precision –Expresses the closeness of agreement between a series of measurements obtained from multiple sampling of the same homogenous sample –Is usually expressed as the standard deviation (S), variance (S 2 ) or coefficient of variation (RSD) of a series of measurements –Precision may be considered at three levels Repeatability (intra-assay precision) Repeatability (intra-assay precision) Intermediate Precision (variability within a laboratory) Intermediate Precision (variability within a laboratory) Reproducibility (precision between laboratories) Reproducibility (precision between laboratories)

18 Birgit Schmauser | April | Analytical Method Development Normal distribution, probability function [P(x)] and confidence interval [CI] Normal distribution, probability function [P(x)] and confidence interval [CI] –Probability (P), that measurements from a normal distribution fall within [µ-x n, µ+x n ] for x n = n  is described by the “erf-function”  µ  mean)  An interval of ± 3  covers 99.73% of values An interval of ± 3  covers 99.73% of values Number of times each value occursP xnxnxnxn      Values      

19 Birgit Schmauser | April | Analytical Method Development Normal distribution, probability function [P(x)] and confidence interval [CI] Normal distribution, probability function [P(x)] and confidence interval [CI] –Probability-P Confidence interval [CI] centered around the mean [µ] in units of sigma [  ] described by “inverse erf-function”: –A CI of 95% includes values ± 1.95  around the mean xpxpxpxpP          

20 Birgit Schmauser | April | Analytical Method Development Relationship of variability, probability and reliability of data Relationship of variability, probability and reliability of data –High variability of data (large  ) generate large confidence intervals and thus lower the reliability of the mean –Low variability of data (small  generate small confidence intervals and thus increase the reliability of the mean

21 Birgit Schmauser | April | Analytical Method Development Repeatability Repeatability –Six replicate sample preparation steps from a homogenously prepared tablet mixture (nominal value of API 150 mg) Assay Peak area Injection mg/98.06% mg/98.66% mg/97.54% mg/98.72% mg/101.30% mg/99.52% mg/98.96% Mean 1.98 mg/1.32% 2329 SD (  ) 1.32%1.32%RSD Mean ± 3 SD = Confidence interval of 99.73% ± 3x1.32% = 95% %

22 Birgit Schmauser | April | Analytical Method Development Intermediate precision Intermediate precision –Expresses within-laboratories variations (different days, different analysts, different equipment etc.) Peak area analyst 3 Peak area analyst 2 Peak area analyst 1 Injection Mean SD (  ) 0.51%0.28%1.32%RSD Analyst 1: 98.96% ± 3 x 1.32% Analyst 2: 99.12% ± 3 x 0.28 Analyst 3: % ± 3 x 0.51 Average of 3 analysts ± 3SD: 95% % Mean ± 3 SD: (  100%)

23 Birgit Schmauser | April | Analytical Method Development Reproducibility Reproducibility –Expresses the precision between laboratories Collaborative studies, usually applied to standardisation of methodology Collaborative studies, usually applied to standardisation of methodology – Transfer of technology – Compendial methods

24 Birgit Schmauser | April | Analytical Method Development Accuracy Accuracy –Expresses the closeness of agreement between the value which is accepted either as a conventional true value or an accepted reference value and the value found Sometimes referred to as „TRUENESS“Sometimes referred to as „TRUENESS“ true mean

25 Birgit Schmauser | April | Analytical Method Development To find out whether a method is accurate: Drug substance (assay) Drug substance (assay) –Application of the method to an analyte of known purity (e.g. reference substance) –Comparison of the results of one method with those of a second well- characterised method (accuracy known) Drug product (assay) Drug product (assay) –Application of the method to synthetic mixtures of the drug product component to which known quantities of the analyte have been added Drug product may exceptionally be used as matrixDrug product may exceptionally be used as matrix Drug substance/Drug product (Impurities) Drug substance/Drug product (Impurities) –Application of the method to samples spiked with known amounts of impurities

26 Birgit Schmauser | April | Analytical Method Development Accuracy: Application of the method to synthetic mixtures of the drug product components to which known quantities of the analyte have been added Accuracy: Application of the method to synthetic mixtures of the drug product components to which known quantities of the analyte have been added Recovery reduced by ~10 – 15% Recovery reduced by ~10 – 15% From : Analytical Method Validation and Instrument Performance Verification, Edited by Chung Chow Chan,Herman Lam, Y.C. Lee and Xue-Ming Zhang, ISBN , Wiley & Sons

27 Birgit Schmauser | April | Analytical Method Development When to expect Accuracy problems When to expect Accuracy problems –Insufficient selectivity of the method Impurity peaks are not resolved and account for assay valueImpurity peaks are not resolved and account for assay value –Recovery is < 100% Irreversible adsorption of analyte to surfaces of the systemIrreversible adsorption of analyte to surfaces of the system –Incorrect assay value of a reference standard Due to decomposition of reference standardDue to decomposition of reference standard –Incorrect assay value due to change in matrix Analytical laboratory still uses the preceding matrix as standardAnalytical laboratory still uses the preceding matrix as standard

28 Birgit Schmauser | April | Analytical Method Development Specificity Specificity –Is the ability to assess unequivocally the analyte in the presence of components which may be expected to be present (impurities, degradants, matrix…) Identity testing –To ensure the identity of an analyte Purity testing –To ensure accurate statement on the content of impurities of an analyte Assay –To allow an accurate statement on the content of an analyte in a sample

29 Birgit Schmauser | April | Analytical Method Development Specificity: Overlay chromatogram of an impurity solution with a sample solution Specificity: Overlay chromatogram of an impurity solution with a sample solution From : Analytical Method Validation and Instrument Performance Verification, Edited by Chung Chow Chan,Herman Lam, Y.C. Lee and Xue-Ming Zhang, ISBN , Wiley & Sons

30 Birgit Schmauser | April | Analytical Method Development Specificity and stability Stress stability testing to ensure the stability indicating potential of an analytical method Stress stability testing to ensure the stability indicating potential of an analytical method –Apply diverse stress factors to the API –Apply diverse stress factors to the FPP Stress conditions: e.g. Supplement 2 of Generic Guideline; TRS 929, Annex 5 Assure that the API can be assessed specifically in the presence of known and unknown (generated by stress) impurities Assure that known impurities/degradants can be specifically assessed in the presence of further degradants By peak purity assessment and (overlay of) chromatograms

31 Birgit Schmauser | April | Analytical Method Development Stress stability studies versus forced degradation studies Stress stability studies versus forced degradation studies Stress stability (5 – 15% decomposition) Forced degradation Stress parameter pH ± 2 (2 weeks) 0.2 ml 1N HCl / 5 ml API-solution / 3h, 6h, 12h, 24h…7d (RT & 60°C) Acid pH ± 10 (2 weeks) 0.2 ml 1N NaOH / 5 ml API-solution / 3h, 6h, 12h, 24h…7d (RT & 60°C) Base 1 g/ml oxygen bubbled through (8 hours) 0.1 – 2% H 2 O 2 (24 hours) 0.2 ml 5% or 35% H 2 O 2 / 5 ml API- solution (RT, to 7d & 60°C, 3h) H 2 O 2 / Oxygen - 60°C / 5 ml solution (3h, 6h…7d) Heat 60°C (4 weeks) 105° C / solid API (1d and 7d) Heat 365 nm or white fluorescent light / solid API (1d and 7d) UV or Light 50°C / 80% RH (4 weeks) -Humidity

32 Birgit Schmauser | April | Analytical Method Development Limit of Detection (LOD, DL) Limit of Detection (LOD, DL) –The LOD of an analytical procedure is the lowest amount of analyte in sample which can be detected but not necessarily quantitated as an exact value Determination is usually based on Determination is usually based on –Signal to noise ratio (~3:1) (baseline noise) or –Standard deviation of response (  ) and Slope (S) 3.3  /S3.3  /S

33 Birgit Schmauser | April | Analytical Method Development Limit of Quantitation (LOQ, QL) Limit of Quantitation (LOQ, QL) –The LOQ is the lowest amount of analyte in a sample which can be quantitatively determined with suitable precision and accuracy The quantitation limit is used particularly for the determination of impurities and/or degradation productsThe quantitation limit is used particularly for the determination of impurities and/or degradation products Determination is usually based on Determination is usually based on –Signal to noise ratio (~10:1) (baseline noise) or –Standard deviation of response (  ) and Slope (S) 10  S10  S

34 Birgit Schmauser | April | Analytical Method Development Noise LOD Signal to Noise = 3:1 LOQ Signal to Noise = 10:1 LOD, LOQ and Signal to Noise Ratio (SNR)

35 Birgit Schmauser | April | Analytical Method Development LOQ LOQ –Quantitation by SNR is accepted –Quantitation by Standard deviation of response (  ) and Slope (S) (10  S) is more adequate as it involves the response of the actual analyte –Best to calculate in the region close to y-intercept

36 Birgit Schmauser | April | Analytical Method Development LOQ and impurities LOQ and impurities –In determination of impurities in APIs and FPPs the LOQ should be determined in the presence of API LOQ should be NMT reporting levelLOQ should be NMT reporting level LOQ should be given relative to the test concentration of APILOQ should be given relative to the test concentration of API –Specificity of impurity determination should always be demonstrated in the presence of API at API specification levels Spiking of test concentration (API/FPP) with impurities at levels of their specification rangeSpiking of test concentration (API/FPP) with impurities at levels of their specification range

37 Birgit Schmauser | April | Analytical Method Development Spiking Spiking –API test concentration (normalised) 0.1 mg/ml (100%) 0.1 mg/ml (100%) –Impurity spiking concentrations mg/ml (1%) – specification limit mg/ml (1%) – specification limit mg/ml (0.1%) – limit of quantitation (minimum requirement) mg/ml (0.1%) – limit of quantitation (minimum requirement) API at test concentrations API below test concentrations

38 Birgit Schmauser | April | Analytical Method Development Linearity of an analytical procedure is its ability (within a given range) to obtain test results which are directly proportional to the concentration (amount) of analyte in the sample Linearity of an analytical procedure is its ability (within a given range) to obtain test results which are directly proportional to the concentration (amount) of analyte in the sample –If there is a linear relationship test results should be evaluated by appropriate statistical methods Correlation coefficient (r) Correlation coefficient (r) Y-intercept Y-intercept Slope of regression line Slope of regression line Residual sum of squares Residual sum of squares PLOT OF THE DATA PLOT OF THE DATA

39 Birgit Schmauser | April | Analytical Method Development Usual acceptance criteria for a linear calibration curve Usual acceptance criteria for a linear calibration curve –r > 0.999; y-intercept a 0.999; y-intercept a < 0 to 5% of target concentration RSD (wrt calibration curve) < 1.5-2% r > r < From : Analytical Method Validation and Instrument Performance Verification, Edited by Chung Chow Chan,Herman Lam, Y.C. Lee and Xue-Ming Zhang, ISBN , Wiley & Sons

40 Birgit Schmauser | April | Analytical Method Development Range Range –The range of an analytical procedure is the interval between the upper and lower concentration (amounts) of analyte in the sample for which it has been demonstrated that the analytical procedure has a suitable level of precision, accuracy and linearity

41 Birgit Schmauser | April | Analytical Method Development Range Range –Assay 80 to 120% of test concentration80 to 120% of test concentration –Content uniformity 70 to 130% of test concentration70 to 130% of test concentration –Dissolution Q-20% to 120%Q-20% to 120% –Impurities Reporting level – 120% of specification limit (with respect to test concentration of API)Reporting level – 120% of specification limit (with respect to test concentration of API) –Assay & Impurities Reporting level to 120% of assay specificationReporting level to 120% of assay specification

42 Birgit Schmauser | April | Analytical Method Development Linearity is limited to 150%of shelf life specification of impurities Linearity is limited to 150%of shelf life specification of impurities –Test concentration can be used to determine impurities To determine drug substance (assay) the test concentration must be diluted The range is 0 – ~ 150% of impurity specification From : Analytical Method Validation and Instrument Performance Verification, Edited by Chung Chow Chan,Herman Lam, Y.C. Lee and Xue-Ming Zhang, ISBN , Wiley & Sons

43 Birgit Schmauser | April | Analytical Method Development Robustness Robustness –Robustness of an analytical procedure should show the reliability of an analysis with respect to deliberate variations in method parameters –The evaluation of robustness should be considered during the development phase –If measurements are susceptible to variations in analytical conditions the analytical conditions should be suitably controlled or a precautionary statement should be included in the procedure

44 Birgit Schmauser | April | Analytical Method Development Influence of buffer pH and buffer concentration in mobile phase on retention times of API and impurities Influence of buffer pH and buffer concentration in mobile phase on retention times of API and impurities Conclusion: The buffer composition should be maintained in a range of 85 ± 0.5% Conclusion: The buffer composition should be maintained in a range of 85 ± 0.5% –Missing: Acceptance criterion for maximal deviation of retention time should be defined unless justified Impurity C Impurity B Impurity A API As is buffer pH buffer pH Buffer conc. 83% Buffer conc. 87%

45 Birgit Schmauser | April | Analytical Method Development System suitability testing System suitability testing –Based on the concept that equipment, electronics, analytical operations and samples to be analysed constitute an integral system that can be evaluated as such –Suitability parameters are established for each analytical procedure individually Depend on the type of analytical procedureDepend on the type of analytical procedure

46 Birgit Schmauser | April | Analytical Method Development Method stability Method stability –System suitability over time Sample solution stability Sample solution stability –A solution of stavudine is stable for ~ 2 h, then it starts to degrade to thymine Impurity-spiked sample solution stability Impurity-spiked sample solution stability  A solution containing stavudine spiked with its impurity thymine does not allow to clearly distinguish between degradation and spike  A solution containing stavudine of a FPP-stability sample solution does not allow to clearly distinguish between FPP-stability degradation and sample solution degradation Should be analysed immediately

47 Birgit Schmauser | April | Analytical Method Development When to be „surprised“ about validation data: When to be „surprised“ about validation data: –Precision of impurity determination –Precision of API determination –Method precision of released API (dissolution) % RSD 0.33 – 2.25 System precision % RSD 0.0 Method precision % RSD 0.08 Average peak area % RSD ≤ 2.0 Acceptance criterion % RSD 0.4 Average peak area % RSD ≤ 10.0 Acceptance criterion

48 Birgit Schmauser | April | Analytical Method Development Specification range (USL-LSL) Specification range (USL-LSL) –Process variability (usually ± 2 SD) –Analytical variability (± 3  ) ~ NMT 30% of total specification range ~ NMT 30% of total specification range Analytical variability Process variability Analytical variability Process variability –Reliability of evaluation of major process variables by analytical procedures depends on analytical variability –Impurities LOQ and specification limit (e.g. qualification limits NMT 0.15%)LOQ and specification limit (e.g. qualification limits NMT 0.15%) –Response factors (LOQ modified by response factor)

49 Birgit Schmauser | April | Analytical Method Development Methods for cleaning validation Methods for cleaning validation –Method for assay and related substances used in stability studies of API and FPP Specificity (in samples taken from a cleaning assessment)Specificity (in samples taken from a cleaning assessment) Linearity of response (from 50% of the cleaning limit to 10x this concentration; R 2 ≥ )Linearity of response (from 50% of the cleaning limit to 10x this concentration; R 2 ≥ ) PrecisionPrecision –Repeatability (RSD ≤ 5%) –intermediate precision [ruggedness (USP)] –Reproducibility Limits of detection and quantitationLimits of detection and quantitation Accuracy or recovery from rinsate (≥ 80%), swabs (≥ 90%), and process surface (≥ 70%)Accuracy or recovery from rinsate (≥ 80%), swabs (≥ 90%), and process surface (≥ 70%) Range (lowest level is at least 2x higher than LOQ)Range (lowest level is at least 2x higher than LOQ)

50 Birgit Schmauser | April | Analytical Method Development Summary Analytical procedures play a critical role in pharmaceutical equivalence and risk assessment/management Analytical procedures play a critical role in pharmaceutical equivalence and risk assessment/management –Establishment of product-specific acceptance criteria –Assessment of stability of APIs and FPPs Validation of analytical procedures should demonstrate that they are suitable for their intended use Validation of analytical procedures should demonstrate that they are suitable for their intended use Validation of analytical procedures deserves special attention during assessment of dossiers for prequalification Validation of analytical procedures deserves special attention during assessment of dossiers for prequalification

51 Birgit Schmauser | April | Analytical Method Development THANK YOU THANK YOU


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