Generics Perspective: Success Strategies for Genotoxic Impurity Identification, Assessment and Control

Transcription

1 Generics Perspective: Success Strategies for Genotoxic Impurity Identification, Assessment and Control Raphael Nudelman, Ph.D. Head of Chemical & Computational Toxicology Genotoxic Impurities London, June 2015

2 Scope Understand the basis of the strategy used for GTI identification, assessment and control Outline key pitfalls and how they are overcome Examine how we use in silico tools and (Q)SAR as part of the assessment strategy Identify how ICH M7 impacts GTI assessment strategies

3 Who we are Global R&D Discovery and Product Development Non Clinical Development Non Clinical Safety Raphael Nudelman Chemical & Computational Toxicology Generics R&D Specialty R&D API units EHS 3

4 Who we are

5 For DS Examine entire RoS (manual + computational) to identify PGIs sm, reagents, solvents, intermediates, byproducts, products A + B Strategy C D E + F G Assess actual + reasonably expected PGIs Calculate purge factors Control recommendations

6 Strategy For DP Identify potentially reactive degradation products (real + potential) Control recommendations

7 Compound specific limit (Class 1) TTC (Class 2 + 3) ICH Q3 (Class 4 + 5) Strategy Control recommendations LTL adjusted TTC Purgeability (no control)

8 Strategy Control recommendations Justifiable higher exposure Metabolites Food-related Pharmacopoeial levels Reference listed drug (RLD) Chemical class mitigation / read-across Monofunctional alkyl chlorides (halides?) α,β-unsaturated aldehydes (ketones, esters, amides?) Alkyl sulfonates? Advanced cancer treatment Tox data (in vivo mutagenicity/carcinogenicity)

9 Strategy Other recommendations When levels can t be justified we recommend: Ames test Alternative in vivo mutagenicity studies

10 Pitfalls Identifying potentially reactive structures Initial analysis based on structurally alerting functional groups from Müller (2006)

11 Müller et al., Reg Tox Pharm 2006, 44,

12 Pitfalls Identifying potentially reactive structures Initial analysis based on structurally alerting functional groups from Müller (2006) Subsequent in silico predictions are much more regioselective, thus precluding PGIs identified manually, and conversely often identify many more PGIs

13 Pitfalls Identifying potentially reactive structures Initial analysis based on structurally alerting functional groups from Müller (2006) Subsequent in silico predictions are much more regioselective, thus precluding PGIs identified manually, and conversely often identify many more PGIs Solution: involve ChemTox as early as possible

14 Using in silico tools Prior to M7 Use one in silico tool Result: potential for false negatives Post M7 Use 2 complementary in silico tools Statistical based tool has too many false positives Conflicting predictions

15 Using in silico tools 6. HAZARD ASSESSMENT ELEMENTS.. If warranted, the outcome of any computer system-based analysis can be reviewed with the use of expert knowledge in order to provide additional supportive evidence on relevance of any positive, negative, conflicting or inconclusive prediction and provide a rationale to support the final conclusion.

16 Using in silico tools Case studies requiring expert analysis

17 Using in silico tools Compound Derek alert Sarah alert Consensus Remarks Control recommendation Adipic acid Inactive Negative (100% confidence) Negative Negative Ames test (Toxnet) ICH Q3A qualification threshold Plausible (potential alkylating agent) Positive (alkyl halide) Positive Monofunctional alkyl halide (note 5 in M7) TTCx10 15 µg/day or run Ames test

18 Using in silico tools Compound Derek alert for mutagenicity Sarah alert Consensus Prediction Remarks Control recommendation Benzyl chloride Plausible (potential alkylating agent) Positive (100% confidence) Positive Positive Ames test (Toxnet). Mutagenic carcinogen (Class 1) with harmonic mean TD 50 of 61.5 mg/kg/day in the Carcinogenic Potency Database (CPDB) Compound specific threshold of 61.5 µg/person/day is calculated by linear extrapolation from the TD 50 Benzyl bromide Plausible (potential alkylating agent) Positive (100% confidence) Positive Negative in 2-year carcinogenicity study ICH Q3A qualification threshold

19 Using in silico tools Compound Derek alert for mutagenicity Sarah alert Consensus Prediction Remarks Control recommendation Inactive Positive Equivocal - TTC or run Ames test Phosphorus oxychloride Inactive Outside domain Equivocal Purge knowledge may be used to avoid analytical testing TTC if not purged out

20 Using in silico tools Compound Derek alert for mutagenicity Sarah alert Consensus Prediction Remarks Control recommendation Diisopropyl azodicarboxylate (DIAD) Inactive Outside domain Negative Sarah Nexus could not associate an appropriate training set to this compound and thus considered it out of domain. Further expert evaluation of this compound showed no structural alerts. ICH Q3A qualification threshold F F 1,3- Difluorobenzene Inactive Positive Equivocal This compound is a class 3 impurity TTC or run Ames test

21 Using in silico tools Compound Derek alert for mutagenicity Sarah alert Consensus Prediction Remarks Control recommendation 4,6-Dichloro-2- methylpyrimidine 1-indanone Inactive Positive Negative Inactive Positive Negative The positive Sarah alert can be dismissed because the training set compounds contain alkyl halides moieties which are known mutagens, and are not present in this compound. The positive Sarah alert can be dismissed because the training set compounds contain PAHs which are known mutagens, and are not present in this compound. ICH Q3A qualification threshold ICH Q3A qualification threshold

22 Using in silico tools Compound Derek alert for mutagenicity Sarah alert Consensus Prediction Remarks Control recommendation THP-protected intermediate Inactive in bacterium; Plausible in mammal (alkyl aldehyde precursor) Negative Negative The plausible alert for mutagenicity in mammalian cells is out of the scope of the ICH M7 guideline ICH Q3A qualification threshold

23 Using in silico tools Compound Derek alert for mutagenicity Sarah alert Consensus Prediction Remarks Control recommendation Inactive Positive Negative 1. The examples in the training set contain alerting moieties that are not present here. 2. α,β -Unsaturated ketones are rarely mutagenic* ICH Q3A qualification threshold Plausible (α,β - unsaturated aldehyde) Positive Positive - TTC or run Ames test *Snodin & McCrossen, Regul. Toxicol. Pharmacol., 2013, 67,

24 Summary Strategy used for GTI identification, assessment and control Key pitfalls and how they are overcome How we use in silico tools as part of the assessment strategy How ICH M7 impacts GTI assessment strategies