In silico strategies to assess potentially mutagenic impurities under ICH M7

The ability to assess an impurity as either non-mutagenic or not present in the final API can offer significant efficiencies without compromising safety.

An integrated solution to ICH M7 developed through collaboration.

In silico tools can provide a robust and cost-efficient solution, provided they are fit-for-purpose.

Impurity identification

Treat as non-mutagenic impurity Control to limits in API No further action

Mutagen?

ICHM7

No Yes No Yes

Purged?

Impurity identification

ICHM7

Mutagen? Purged?

Database search

Expert system

Statistical system

Expert Assessment

Classification

Report

Control

Expert Assessment

In silico Test Measure In silico

Lhasa Carcinogenicity Database

Expert assessment is a fundamental part of the assessment of the mutagenic potential of impurities under the ICH M7 guideline1, which makes a specific provision for the application of expert knowledge to support or overturn a (Q)SAR prediction.

Whilst expert assessment has been successfully applied in this context2,3, the definition of what constitutes expert analysis has been largely left open. Chris Barber et al.4 have outlined their views on establishing best practice in the application of expert review under ICH M7 and these views can be summarised by the Lhasa ICH M7 decision matrix.

This workbook builds on the practices outlined in that paper and provides a number of worked examples of performing expert assessment under ICH M7. In reviewing the examples it is important to note the following:

1. ICH M7 requires the use of 2 complementary methodologies (one expert rule-based and the other statistical-based)5. This exercise uses Derek Nexus which fulfils the requirements of the expert rule-based methodology and Sarah Nexus which fulfils the requirements of the statistical-based methodology.

2. For the purpose of this exercise, assessments have been made using a combination of the predictions from Derek Nexus, Sarah Nexus and Mirabilis, along with the supporting information they provide and data from similar compounds where applicable (read across).

3. All expert calls made on the examples are solely the opinion of experts at Lhasa Limited and are made here for guidance purposes only.

1. http://www.ich.org/products/guidelines/multidisciplinary/article/multidisciplinary-guidelines.html

2. Dobo, K. L., Greene, N., Fred, C., Glowienke, S., Harvey, J. S., Hasselgren, C., … Vijayaraj Reddy, M. (2012). ‘In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: an industry survey’. Regulatory Toxicology and Pharmacology : RTP, 62(3), 449–55. doi:10.1016/j.yrtph.2012.01.007.

3. Sutter, A., Amberg, A., Boyer, S., Brigo, A., Contrera, J. F., Custer, L. L., … van Gompel, J. (2013). ‘Use of in silico systems and expert knowledge for structure-based assessment of potentially mutagenic impurities’. Regulatory Toxicology and Pharmacology : RTP, 67(1), 39–52. doi:10.1016/j.yrtph.2013.05.001.

4. Barber, C., Amberg, A., Custer, L., Dobo, K. L., Glowienke, S., van Gompel, J., Gutsell, S., Harvey, J., Honma, M., Kenyon, M. O., Kruhlak, N., Muster, W., Stavitskaya, L., Teasdale, A., Vessey, J., Wichard, J. (2015). ‘Establishing bext practice in the application of expert review of mutagenicity under ICH M7’. Regulatory Toxicology and Pharmacology: RTP 73 (2015) 367-377.

5. Barber et. al. (2017) ’Distinguishing between expert and statistical systems for application under ICH M7’ Regulatory Toxicology and Pharmacology 84 (2017) 124-130

References

In silico Prediction 1

In silico Prediction 2

Out of domain or equivocal

Out of domain or equivocal

The Lhasa ICH M7 decision matrix4 provides an overview on the likely outcome based on your 2 predictions. Expert review and additional information can however lead to a different expert call.

Likely to conclude positive Very strong evidence would be needed to overturn both predictions.

Likely to conclude positive Lack of a second prediction suggests insufficient evidence to draw any

other conclusion.

Uncertain Likely to conclude positive without strong evidence to overturn a

positive prediction.

Uncertain Conservatively could assign as positive. May conclude negative with strong

evidence showing feature driving a ‘no prediction’ is present in the same context in known negative examples (without deactivating features).

Likely to conclude negative Expert review should support this conclusion - e.g. by assessing any concerning features (misclassified, unclassified, potentially reactive...).

ICH M7 decision matrix

Case study based on the synthesis of Pimavanserin

O

HONH2

K2CO

3, KI, DMF

free basehemi-tartratePimavanserin L-tartaric acid

i. H2, Raney-Ni

ii. Acetic acidiii. NaOH

O

O

O

O

N

CI CI

O

O

C N

N

N

N

N N

O

O

F

F

OBr

Example

4-hydroxybenzaldehyde

01

Both Derek Nexus and Sarah Nexus report a negative prediction.

ICH M7 Summary Results

5 strains reported in Vitic Nexus.

Expert review: The compound is non-mutagenic.

Example

1-Bromo-2-methylpropane (iso-Butyl Bromide)

02

Sarah Nexus brings up a negative with 100% confidence. Subsequent searching in Vitic Nexus brings up an exact match.

ICH M7 Summary Results

• The reference is quite old (1977) and pre-dates OECD guidelines

» No pre-incubation

» Concentration was not reported

• The compound was tested in 5-strains +/- S9

» It was not tested using e. coli or TA102

• The compound was tested in a desiccator (volatile compound)

• What does read-across tell us?

» Close analogues tested in the same paper were active

* Neopentyl analogue from Mutation Res Letters 1984, 140, 71

Expert review: This is not a safe result – would retest or consider as mutagenic.

Br

n-Bu-BrBr

s-Bu-BrBr

t-Bu-Br neopentyl-Br

Br

Br

*

Example

Phosgene

03

ICH M7 Summary Results

CI CI

O

Derek Nexus predicts a negative, however Sarah Nexus returns an out of domain prediction.

The data in Vitic Nexus shows that it tested negative in TA98/100 however it is also unlikely to survive the conditions.

Expert review: Expect it to be Ames negative but treat as Class 3 due to the lack of a strong QSAR prediction

Searching Vitic Nexus brings up an exact match:

Example

Benzyl isocyanate

04

ICH M7 Summary Results

O

O

C N

Derek Nexus has a strong alert – detailed expert analysis and lots of supporting publications.

Derek and Sarah Nexus give conflicting results.

Sarah Nexus does not have a specific hypothesis for isocyanates.

A range of analogues are known and the majority are predicted inactive, however a review of this class in Derek Nexus tells us that conditions in the assay can lead to incorrect negative results:

• These conflicting results may be a consequence of the aqueous instability and high bacterial toxicity associated with these classes of compound.6

• The effects of solvent and test media on the rate of decomposition of aromatic isocyanates and the implications of this for the interpretation of the relevance of Ames test results have been discussed7,8. In particular, the use of DMSO as solvent has been discouraged on the basis of the instability of aromatic isocyanates in this solvent.

Expert review: Given the question marks over the negative predictions, a conservative review is that it is a class 3.

A review of our predictions so far gives the following:

If we were to continue this for all compounds we would see:

O

HONH2

K2CO

3, KI, DMF

free basehemi-tartratePimavanserin L-tartaric acid

i. H2, Raney-Ni

ii. Acetic acidiii. NaOH

O

O

O

O

N

CI CI

O

O

C N

N

N

N

N N

O

O

F

F

OBr

O

HONH2

K2CO

3, KI, DMF

free basehemi-tartratePimavanserin L-tartaric acid

i. H2, Raney-Ni

ii. Acetic acidiii. NaOH

O

O

O

O

N

CI CI

O

O

C N

N

N

N

N N

O

O

F

F

OBr

References

6. Yamaguchi T. (1980) ‘Mutagenicity of isothiocyanates, isocyanates and thioureas on Salmonella typhimurium.’ Agricultural and Biological Chemistry 44, 3017-3018

7. Herbold et. al. (1998) ‘Studies on the effect of the solvents dimethylsulfoxide and ethyleneglycoldimethylether on the mutagenicity of four types of diisocyanates in the Salmonella/microsome test.’ Mutation Research 412, 167-175

8. Seel et. al. (1999) ‘Chemical behaviour of seven

aromatic diisocyanates (toluenediisocyanates and diphenylmethanediisocyanates) under in vitro conditions in relationship to their results in the Salmonella/microsome test.’ Mutation Research 438, 109-123

Can Mirabilis help assess the risk of the impurity surviving synthesis?Built on a method accepted by regulators9,10,11, Mirabilis is an industry-standardised, expert and scientifically robust software tool for the calculation of the purge factors of potentially mutagenic impurities in a synthetic route.

9. Teasdale et. al. (2013) ‘Risk assessment of genotoxic impurities in new chemical entities: Strategies to demonstrate control’ Organic Process Research and Development 17, 221

10. Teasdale et. al. (2010) ‘A Tool for the Semi-quantitative Assessment of Potentially Genotoxic Impurity (PGI) Carryover into API Using Physicochemical Parameters and Process Conditions’ Organic Process Research and Development 14, 943

11. Mclaughlin et. al. (2015) ‘Evaluation and Control of Mutagenic Impurities in a Development Compound: Purge Factor Estimates vs Measured Amounts’ Organic Process Research and Development 19, 153

Entry of the synthetic route into Mirabilis provides the following purge prediction:

The ICH M7 guideline specifies an acceptable limit of mutagenic impurities in the final drug product. Using the prediction from Mirabilis, the expected level in the final API can be calculated and the appropriate option assigned.

In summary, expert review incorporating Derek, Sarah and Vitic Nexus highlights 3 impurities of concern with regards to their mutagenic potential, with the other 6 predicted to be non-mutagenic. However through the use of Mirabilis it can be confidently concluded that 2 of the 3 impurities will be purged and therefore no further testing would be required.

Review of the 4 example compounds using this approach, gives the following conclusion:

• Non-mutagen (Vitic) acceptedClass 5 (non-mutagenic)

• Non-standard (negative) Ames data discounted by expertClass 3 (mutagenic)

• High purge predicted by MirabilisM7 Option 4 (not specified in submission)

• Derek contains unclassified: Sarah out of domainTreated as Class 3 (mutagenic)

• High purge predicted by MirabilisM7 Option 4 (not specified in submission)

• Derek positive: Sarah negative Treated as Class 3 (mutagenic)

• Moderate purge predicted by MirabilisEvaluate Options 1 or 2 (test in API or precursor)O

O

C N

CI CI

O

Br

Prediction of purge with sufficient confidence to be below acceptable limit in API such that no analytical testing is recommended. [Impurity not in specification]

Analysis shows above limit in precursor / intermediate - but with knowledge of purge can be assured that level in the API is below the acceptable limit without the need for any additional testing

Analysis shows below limit in precursor / intermediate…

Analysis shows below limit in APIOption 1

Option 2

Option 3

Option 4

=Purge Value from Mirabilis

Expected levelin final API

Measured or assumed levels during synthesis

shared knowledge shared progress

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