Presenter: Susanne Glowienke, PCS, Novartis

44th ICGM, Basel, 2016

ICH M7 Classification and the involvement of (Q)SAR methods

Outline

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Introduction

ICH M7 hazard assessment

In silico systems and use of expert knowledge

• Case studies for ICH M7 classes 3,4 and 5

Compound specific risk assessment

• Case studies for ICH M7 class 1

Summary

Assessment strategy

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ICH M7 adapted process

Ames positiveImpurityIn silico

assessment

ICH Q3A

No mutagenicity alert

ICH M7

Mutagenicity alert

Purge factor

assessment

Insufficient purge

Ames test

ICH Q3A

Ames negative

ICH M7

Analytical testing

ICH M7

Scientific based

argumentation

Sufficient

purge

Ames test performed only for not purged compounds

ppm limit tests required for Ames positive/unpurged assumed mutagen

ICH-M7 implementation

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Purge factor tool (Lhasa consortium proposal)

Purge Safety Factor = predicted purge factor / required purge factor

Reference: A. Teasdale et.al, OPRD 2013-17(2), 22

> 10 x> 100 x≥ 1000 x

Potentially mutagenic (PMI)

or mutagenic impurity (MI)

Comparison of predicted purge factor*) vs. required

purge factor calculated from TTC or PDE requirements

Scientific justification• Apply purge approach

• Not necessarily

supported by analytical

data

Collect experimental data

on purge properties• E.g. solubility, reactivity etc.

to support scientific rationale

• Analytical data collection not

necessarily required

Measure purge factor• Spiking experiments

• Trace analysis as

required to support

scientific rationale

PSFPurge Safety Factor

Mutagenic impuritiesHazard assessment in ICH M7 guideline

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Hazard assessment involves:

• Initial analysis of actual and potential impurities by conducting database and literature searches for carcinogenicity and bacterial mutagenicity data

- Classification into Class 1, 2, or 5

• Assessment of Structure-Activity Relationships (SAR) that focuses on bacterial mutagenicity predictions

- Classification into Class 3, 4, or 5

Class Definition Proposed action for control

1 Known mutagenic carcinogen Compound specific limit

2 Known mutagen, unknown carcinogenic potential Control at or below acceptable limit (LTL / TTC)

3 Alerting structure unrelated to non-mutagen

No mutagenicity data

LTL/TTC or conduct bacterial mutagenicity assay

If mutagenic: class 2, if not mutagenic: class 5

4 Alerting structure related to non-mutagen

No mutagenicity data

Non-mutagenic impurity (ICH Q3A/B)

5 No structural alert; experimental lack of mutagenicity Non-mutagenic impurity (ICH Q3A/B)

Cohort of concern Individual control strategy

Cohort of concern

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Case by case approach

Compounds from structural classes of mutagens with extremely high carcinogenic potency

Aflatoxin like, N-nitroso-, and alkyl-azoxy structures

Acceptable intakes are (most probably) significantly lower compared to the standard TTC concept

For these compounds a case-by case approach needs to be developed to define acceptable intakes

Mutagenic impuritiesHazard assessment in ICH M7 guideline

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Hazard assessment involves:

• Computational toxicology assessment using (Q)SAR (Quantitative Structure Activity Relationship) methodologies

- Predict the outcome of bacterial mutagenicity assay

- Two (Q)SAR prediction methodologies that complement each other:

• Expert rule-based and statistical-based

• Absence of structural alerts is sufficient to conclude that impurity is of no mutagenic concern (no further testing recommended)

• Outcome of any computer system-based analysis can be reviewed with the use of expert knowledge

- provide additional supportive evidence on relevance of any positive, negative, conflicting or inconclusive prediction (rationale to support final conclusion

• Negative bacterial mutagenicity assay overrules structure-based concern

In silico systems

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Example for knowledge based system

Derek Nexus (Lhasa Ltd) – knowledge based

• Positive (structural alerts) and negative predictions possible

• Negative predicted compound is compared to Lhasa reference set of Ames test data, producing 3 possible outcomes

- (i) All features in molecule are found in accurately classified compounds from reference set: a negative prediction is displayed

- (ii) Features in molecule are found in non-alerting mutagens in reference set

• Prediction remains negative but misclassified features are displayed

• Relationship between misclassified features and mutagenic activity may be coincidental or contributory

- (iii) Features in molecule are not found in reference set

• Prediction remains negative and unclassified features are displayed

• Information on coverage

• (ii) and (iii) are subject to expert judgement

In silico systems used

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Derek Nexus – example for misclassified feature

No structural concern for mutagenicity detected

Oxazolidine moiety flagged as misclassified feature

• ICH M7 class 3, i.e. reference mutagen considered sufficiently similar to warrant Ames test? or

• Query other prediction tools/consider expert knowledge Class 4/5?

In silico systems used

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Example for a statistical system

Sarah Nexus (Lhasa Ltd) – statistics-based

• Structures submitted for processing are fragmented

• Fragments are reviewed for activity versus inactivity by arranging 'interesting' fragments into a network of hypotheses (or nodes)

• Relevant hypotheses are used to inform an overall prediction of toxicity

• Predicts activity or inactivity in the Ames test and provides information on coverage of query compound

Overall prediction hypothesis for fragments is positive

in Ames test

In silico systems used

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Derek and Sarah Nexus

Combined ICH M7 prediction

Conflicting prediction: Assign to ICH M7 class 3 or 5?

• Negative Derek prediction:

because molecule is not an

arylboronic acid

• Positive Sarah prediction:

because borolane moiety is part of

aryl boronic acids present in

reference set

Result is ICH M7 class 5 because Ames test was negative

Use of expert knowledge

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Considerations for an overall assessment and expert review

Expert review

• Assess negative predictions

• Refute positive predictions

• Address inconclusive prediction results

• Deal with out of domain results

Use of expert knowledge

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Concluding a combined Derek and Sarah Nexus prediction

Equivocal Sarah prediction:

• Similar molecules in training set are not mutagenic

• Derek prediction does not show structural alert

• Conclusion: ICH M7 class 5 Confirmed by negative Ames test

Amino-tetrazole

Refuted negative prediction from two methodologies

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O-(2-Hydroxyethyl)hydroxylamine

Negative prediction for bacterial mutagenicity using both expert rule-based and statistical-based models

However, conflicting evidence for mutagenicity of different hydroxylamine salts in public domain

Conclusion: Potential mutagenic response on the basis of the hydroxylamine moiety should be further evaluated

• Assigned to ICH M7 class 3

Submitted for Ames assay testing where mutations in strain TA1535 in the absence of S9 were induced

Use of literature data

Refuting a positive prediction based on an ICH M7 class 4 analysis (Amberg et al., 2016)

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Series of similar impurities predicted to be positive in statistical-based model

Common feature responsible forpositive prediction highlighted in red

Ames data generated for one structure (= known negative) and applied to other impurities where R, R1, R2 or R3 varied but without additional alerting functionality

Impurities are considered analogs of the known negative compound sharing same highlighted positive structural features

• Assigned to ICH M7 class 4

No further Ames tests conducted

Assessing an out-of-domain prediction using public analogs (Amberg et al., 2016)

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Aminoacetonitrile

Out-of-domain for statistical-based models and predicted to be negative by the expert rule-based model

Structurally similar compounds shown to be not mutagenic except 3-chloropropionitrile which contains additional alerting structure (alkyl chloride)not shared with aminoacetonitrile

Out of domain result over-ruledand conclusion not mutagenic

• ICH M7 class 5

Compound-specific risk assessmentMutagenic carcinogens (ICH M7 class 1)

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• Compound-specific risk assessments to derive acceptable

intakes (AI) should be applied instead of TTC-based

acceptable intakes where sufficient carcinogenicity data

exists

• For known mutagenic carcinogen, a compound-specific

acceptable intake can be calculated based on carcinogenic

potency and linear extrapolation as default approach

• Limits for frequently used chemicals are given in the ICH

M7 addendum (step 2b)

Compound-specific risk assessment (ICH M7 class1)Methods proposed in ICH M7 addendum

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Linear mode of action

• Calculation of acceptable intake (AI) (standard method)

- Selection of studies (consider quality), usually from CPDB

- Selection of tumor and site, route of administration, human relevance of

tumor

- AI = TD50 / 50’000 x 50 kg

Published regulatory limits

Non-linear thresholded mode of action

• Calculation of permissible daily exposure (PDE) if clear evidence for

thresholded mechanism of action

Acceptable limit based on exposure in environment or food

Compound-specific risk assessmentExample benzyl chloride (ICH M7 addendum)

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Benzyl chloride

Mutagenic and genotoxic in vitro but not in mammalian systems in vivo

IARC classified as Group 2A, probably carcinogenic to humans Clear

2-year rodent carcinogenicity studies available

• Site-of-contact tumors probably caused by irritation/inflammation not

considered relevant for humans at low amounts as impurity

• Thyroid C-cell tumors were used to derive AI (acceptable intake)

- TD50 = 40.6 mg/kg/day

• Lifetime AI =40.6 (mg/kg/day)/50,000 x 50 kg = 41 µg/day

Case study ICH M7 class 1p-Aminophenol (NVS)

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Studies to assess mutagenic/carcinogenic potential in literature:Assay Species Result

Ames test Salmonella strains TA98, TA100, TA97, TA1535, TA1537; +/- rat and hamster S9

Negative

Ames test Salmonella strains TA98, TA100, TA1535, TA1537 and E. coli; +/- rat S9

Positive (E. coli + S9)

HGPRT test Chinese hamster ovary (CHO) cells; +/- rat S9 Negative

Mouse lymphoma L5178Y (TK+/TK-) cell Positive (- S9)

Chrom ab Human lymphocytes Clastogenic (+/- S9)

Mammalian Erythrocyte Micronucleus Test

Mouse (in vivo) Statistically significant increase in the frequency of micronucleated polychromatic erythrocytes

Mouse splenocyte micronucleus test

Mouse (in vivo) Positive results have been found with a maximum after 14 days of treatment

Micronucleus test by oral route (gavage) in rats for 13 weeks

Rat (in vivo; daily administration at doses of 12 and 30 mg/kg for 13 weeks

Negative (no increase in number of micronucleated PCEs)

Mammalian Bone Marrow Chromosomal Aberration Test

Rat (in vivo, single doses, MTD reached) Equivocal

Carcinogenicity studyoral

Rat, 50 males/females, 2, 5, 12 and 30 mg/kg Negative

Carcinogenicity study dermal

Mouse, 50 males/females, 0.04, 0.2 and 1.0% in hair dye formulation

Negative

Case study ICH M7 class 1p-Aminophenol – other considerations

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• EFSA (European food agency)

- Potential for induction of point mutations in mammalian cells in vitro could not be

excluded, albeit results were observed at cytotoxic concentrations

• SCCP (Committee for cosmetics)

- Genotoxic in vitro and in vivo; induces clastogenic effects that occur at high doses

in the presence of toxic effects

• Biological significance of these effects and their relevance for exposed humans has to be

further discussed

- Threshold-related mechanism of action likely suggesting that no genotoxic risk for

humans under normal use conditions as ingredient in cosmetic products exist

• Metabolite of acetaminophen (Paracetamol)

• Paracetamol-induced genotoxicity seem to involve dose thresholds; from epidemiological

studies of acetaminophen no conclusive evidence for carcinogenicity in man

• p-Aminophenol «qualified» in acetaminophen studies

Case study ICH M7 class 1p-Aminophenol – taken together

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Derivation of PDE (permitted daily exposure) justified:

• Genotoxic potential in vitro and in vivo but evidence for thresholded

effect

• Available data from oral and dermal carcinogenicity studies suggests p-

aminophenol is not carcinogenic

PDE using carcinogenicity study

• PDE carcinogenicity, oral = 30 mg/kg x 50 kg / 5 x 10 x 1 x 10 x 1 = 3 mg/day(Adjustment factors: 5: extrapolation rats to humans, 10: variability between individuals, 1:

life-time study, 10: genotoxic effects, 1: 30 mg/kg is NOAEL for carcinogenicity)

PDE using repeat dose tox study: nephrotoxicity ≥ mid dose

• PDE repeat dose, oral = 10 mg/kg x 50 kg / 5 x 10 x 5 x 3 x 1 = 670 µg/day(Adjustment factors: 5: extrapolation rats to humans, 10: variability between individuals, 5:

3 month study, 3: dose-dependent tubular nephrosis, 1: NOAEL used)

Summary

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Hazard assessment of ICH M7 suggests assignment of

impurities into 5 classes together with appropriate

consequences:

Ames test, limitation, ICH Q3A/B impurity, PDE

For (Q)SAR assessment use of expert knowledge plays

key role

Compound specific risk assessments require careful

review of available data (including non-carcinogenicity

endpoints)

Useful publications

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In silico prediction under ICH M7 guideline

Establishing best practice in the application of expert review of mutagenicity under ICH M7Chris Barber, Alexander Amberg, Laura Custer, Krista L. Dobo, Susanne Glowienke, Jacky Van Gompel, Steve Gutsell, Jim Harvey, Masamitsu Honma, Michelle O. Kenyon, Naomi Kruhlak, Wolfgang Muster, Lidiya Stavitskaya, Andrew Teasdale, Jonathan Vessey, Joerg Wichard

Regulatory Toxicology and Pharmacology 73 (2015) 367-377

It's difficult, but important, to make negative predictionsRichard V. Williams, Alexander Amberg, Alessandro Brigo, Laurence Coquin, Amanda Giddings, Susanne Glowienke, Nigel Greene, Robert Jolly, Ray Kemper, Catherine O'Leary-Steele, Alexis Parenty, Hans-Peter Spirkl, Susanne A. Stalford, Sandy K. Weiner, Joerg Wichard

Regulatory Toxicology and Pharmacology 76 (2016) 79-86

Evaluation of a statistics-based Ames mutagenicity QSAR model and interpretation of the results obtainedChris Barber, Alex Cayley, Thierry Hanser, Alex Harding, Crina Heghes, Jonathan D. Vessey, Stephane Werner, Sandy K. Weiner, Joerg Wichard, Amanda Giddings, Susanne Glowienke, Alexis Parenty, Alessandro Brigo, Hans-Peter Spirkl, Alexander Amberg, Ray Kemper, Nigel Greene

Regulatory Toxicology and Pharmacology 76 (2016) 7-20

Principles and procedures for implementation of ICH M7 recommended (Q)SAR analysesAlexander Amberg, Lisa Beilke, Joel Bercu, Dave Bower, Alessandro Brigo, Kevin P. Cross, Laura Custer, Krista Dobo, Eric Dowdy, Kevin A. Ford, Susanne Glowienke, Jacky van Gompel, James Harvey, Catrin Hasselgren, Masamitsu Honma, Robert Jolly, Raymond Kemper, Michelle Kenyon, Naomi Kruhlak, Penny Leavitt, Scott Miller, Wolfgang Muster, John Nicolette, Andreja Plaper, Mark Powley, Donald P. Quigley, M. Vijayaraj Reddy, Hans-Peter Spirkl, Lidiya Stavitskaya, Andrew Teasdale, Sandy Weiner, Dennie S. Welch, Angela White, Joerg Wichard, Glenn J. Myatt

Regulatory Toxicology and Pharmacology. Regulatory Toxicology and Pharmacology 77 (2016) 13-24

Thank you

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Acknowledgement

Colleagues from TRD (in particular Guido Jordine)

for purge factor flow chart