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Undertaking expert review
under the ICH M7 guidelines
ACEMS/JEMS, Tokyo, November 2019
CEO
Dr Chris Barber
Agenda
• Introducing Lhasa
• The purpose of ICH M7
• Publications and supporting guidance
• Examples of expert review
• How accurate is expert review?
Lhasa is an educational charity that develops in sili
Head office in Leeds, UKNot-for-profit
Educational charity
A membership organisation
Data & knowledge sharing
Honest broker
Sponsor
PhDs
Teaching
lecturesWork
experienceAcademic
Agrochem
Biotech
Chemical
CROCosmetic
Generics
Personal Products
Pharma
Government
Tobacco
MIP-DILI
Regulators &
Governmental Agencies(38 are members of Lhasa)
Proprietary data mining
Predictive software
(expert & machine learnt)
Purge
Toxicity Metabolism
Degradation
Undergrad
projects
Publications &
presentations
FDA NIHS eTRANSAFE
eTOXPMDA
MHRAUSP
ICH M7
• Assessment and control of DNA reactive
(mutagenic) impurities in pharmaceuticals
to limit potential carcinogenic risk.
Is the impurity mutagenic?
Is the impurity present in the final API?
What are the potential impurities?
Implement a control strategy
reagents, intermediates,
impurities, degradants…
Ames test or in silico methods
Analytical or in silico methods
Lhasa provides a suite of tools
• We work with industry and regulators to provide data and
tools that support safe decision-making
Is the impurity mutagenic?
Is the impurity present in the final API?
What are the potential impurities?
Implement a control strategy
reagents, intermediates,
impurities, degradants…
Ames test or in silico methods
Analytical or in silico methods
Using in silico tools to predict mutagenicity
• ICH M7 supports using 2 complementary in silico predictions in place of an Ames study
• Expert system + statistical system - see Barber, C. Reg. Toxicol. Pharmacol. 2017, 84, 124
• ICH M7 Recommends the use of expert review
• Publications showing the importance, impact and application of expert review
• Establishing best practise in the application of expert review of mutagenicity under ICH M7.
Barber, C.., Reg. Toxicol. Pharmacol. 2015, 73, 367
• Use of in silico systems and expert knowledge for structure-based assessment of potentially
mutagenic impurities. Sutter, A.., Reg. Toxicol. Pharmacol. 2013, 67, 39
• Principles and procedures for implementation of ICH M7 recommended (Q)SAR analyses.
Amberg, A.., Reg. Toxicol. Pharmacol. 2016, 77, 13
• See https://www.lhasalimited.org/library/ for papers, posters, and videos…
Undertaking Expert Review
Expert assessment of 2 in silico predictions
A dihalonaphthalene Compound 13
Expert Review
M7 classification
?
A dihalonaphthalene Compound 13
Indicates
confidence in
the prediction
Expert Review
M7 classification
?
https://www.lhasalimited.org/products/sarah-nexus.htm#Confidence
Distinguishing between expert and statistical systems for application under ICH M7 Barber, C. Reg. Toxicol. Pharmacol. 2017, 84, 124
Review the expert predictionINACTIVE
• No alerts
• No misclassified
• Identifies features found in
false negative predictions
• No unclassified• Identifies features not
present in public datasets
• Expert agrees with Derek
Expert Review
M7 classification
?
It's difficult, but important, to make negative predictions.
Williams. Reg. Toxicol. Pharmacol. 2016, 76, 79
Review the statistical prediction
Expert Review
M7 classification
?
Low confidence prediction
• Worth reviewing carefully
Tricyclic aromatics
fire a different Derek
alert (phenanthrenes)
Fires Derek nitro alert
• Positive analogues not relevant• prediction over-ruled by expert
Expert review
• Inactive prediction
• No misclassified features
• Weak positive prediction (6%)
• Activity of compounds in Sarah are associated with other
functional groups that fire alternative Derek alerts.
• Most similar compound gives negative results
Non-mutagen
Class 5
Expert Review
M7 classification
?
An aryl acid chloride Compound 9
Expert Review
M7 classification
?
An aryl acid chloride Compound 9
Expert Review
M7 classification
?
Both positive predictions
are weak – needs
investigation
Review the expert prediction
• Equivocal
• There is evidence both for
and against mutagenicity
• Derek alert warns user that positive Ames is NOT driven by the compound
Expert Review
M7 classification
?
Specific comment that activity is dependent
upon the solvent used. Mechanism that
creates the active species is described
Review the statistical prediction
Expert Review
M7 classification
?
• Low confidence prediction
• Worth reviewing carefully
• Tricyclic aromatics fire
a different Derek alert
(phenanthrenes)
• Fires Derek nitro alert
• Closest analogues are active for other reasons - they do not support a positive prediction
• No hypothesis
for acid chloride
Expert review
Non-mutagen
Class 5
Expert Review
M7 classification
? • Positive prediction with equivocal reasoning for acid halide
• DMSO-dependent activity observed for this class
• Observed activity will depend upon solvent NOT compound
• Weak positive prediction
• Positive compounds can be explained by presence of other
groups
• Recommend retesting in a non-reactive solvent
• Predict this will be inactive
Bis aniline ether Compound 10
Expert Review
M7 classification
?
Compound 10
Expert Review
M7 classification
? Conflicting predictions
Review the expert prediction
Negative prediction made
• Derek predicts inactive (and explains why)
Expert Review
M7 classification
?
Near-miss to alert 351 which defines the electronics
of a para substituent needed for activity
Review the statistical prediction
Expert Review
M7 classification
?
Low confidence prediction
• Worth reviewing carefully
Similar compounds show
different activities (activity cliff)
A close negative
analogue…
• Weak prediction – likely to be close to activity cliff• Conservatively - insufficient evidence to class as negative
Positive hypothesis
for aromatic amines
…and has been
tested in 5 strains
Expert review
Mutagen
Class 3
Expert Review
M7 classification
?
• Conservatively classified as positive
• Expert review noted that a negative result is likely
• Inactive prediction
• No misclassified features
• Near-miss of alert 351 for aromatic amine
• Positive but low confidence
• The compounds most similar have mixed Ames results
• Positive compounds do not have any additional toxicophores
• Insufficient data to dismiss a positive prediction
Accuracy of expert review + in silico predictions
• The reproducibility of the Ames study has been reported as ~85%
• Mutagenesis 2009, 24, 359; J. Chem. Inf. Model. 2009, 49, 2077
• Expert review + 2 in silico systems are reported to give an accuracy > 90%
• Sutter.. Regul. Toxicol. Pharmacol. 2013, 67, 39
• In silico predictions have identified false positive Ames results
• Gunther. Reg Pharm Tox 2017, 91, 68
• Expert review of any Ames result is important
• Purity : “..highly potent mutagens such as aromatic nitro impurities could cause a
positive Ames result if present ..at levels as low as 0.00002%”
• GLP testing in 5 strains to OECD standards
Summary
• In silico systems should support the user
• ‘Hard’ predictions require more expert review
• Use all supporting evidence
• Confidence in each prediction?
• Do ‘similar’ analogues alert for different reasons?
• Strain data of key negative analogues?
• Take a conservative approach
• If not sure, test or rely on a purge argument
Hard Examples
Low confidence
Mis- or unclassified
Poor coverage of
important fragments
Own knowledge /
proprietary data disagrees
Conflicting predictions
Equivocal or no prediction
Activity cliff
Thank you ありがとうご
Head office in Leeds, UKNot-for-profit
Educational charity
A membership organisation
Data & knowledge sharing
Honest broker
Sponsor
PhDs
Teaching
lecturesWork
experienceAcademic
Agrochem
Biotech
Chemical
CROCosmetic
Generics
Personal Products
Pharma
Government
Tobacco
MIP-DILI
Regulators &
Governmental Agencies(38 are members of Lhasa)
Proprietary data mining
Predictive software
(expert & machine learnt)
Purge
Toxicity Metabolism
Degradation
Undergrad
projects
Publications &
presentations
eTRANSAFE
eTOX
FDA NIHSPMDA
MHRAUSP
Skills of an expert or an expert team 専門家や専門家チームのスキル
DrugMetabolist
Chemist化学者
Toxicologist毒物学者
Chemicalreactivity
Similarity
Chemicalstructure
Impurityprofile
Reactivemetabolites Metabolic
activationMetabolicprofile
(Q)SAR
Protocol and limitations of Ames assay
Mechanismsof activity
Analyticalchemistry
Functionalgroups
Processchemistry
Interpretation of strain data
How in silicosystems workstrengths/limitations
Supporting data
Where to focus