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ICH M7 Prediction

Lhasa Limited provides an integrated solution to assist in the meeting of the ICH M7 guideline.

  • Regulatory agencies will accept results from (Q)SAR methodologies in lieu of in vitro testing under certain circumstances.
  • The ICH M7 functionality within the Nexus Suite provides a calculation of an ICH M7 classification for impurities in a synthetic route.
  • Expert assessment is a fundamental part of the evaluation of the mutagenic potential of impurities under the ICH M7 guideline.

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The ICH M7 Guideline1 provides a practical framework that can be applied to the identification, categorization, qualification and control of mutagenic impurities to limit potential carcinogenic risk.


Expert Review


ICH M7 Brochure

What does the ICH M7 Guideline mean for you?

The guideline states that a computational toxicology assessment can be performed using two complementary (Q)SAR prediction methodologies which predict the outcome of a bacterial mutagenicity assay1.

One methodology should be expert rule-based and the second methodology should be statistical-based. (Q)SAR models utilizing these prediction methodologies should follow the general validation principles set forth by the Organisation for Economic Co-operation and Development (OECD)2.”

The important messages to take away from the guideline are:

  • Regulatory agencies will accept results from (Q)SAR methodologies in lieu of in vitro testing.
  • Expert review is a crucial step, allowing you to justify your case.
  • Structure-Activity Relationship (SAR) methodologies can be used to support the decision making for determining mutagenic potential of impurities and thereby minimising the expense of testing.
  • Experts can make use of existing data to support decisions and submissions.

The validation principles set forth by the OECD are as follows:

  1. A defined endpoint
  2. An unambiguous algorithm
  3. A defined domain of applicability
  4. Appropriate measures of goodness-of-fit, robustness and predictivity
  5. A mechanistic interpretation, if possible

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Why choose Lhasa?

Lhasa's solutions are currently used across a range of sectors but most notably pharmaceutical, cosmetic, chemical, regulators, government agencies and academia. A list of members can be viewed here.

When asked why people choose to work with Lhasa Limited, the common responses are:

Software is easy to use and well supported

Transparency of Lhasa systems allows trust and confidence in the science presented

All science is developed in-house, providing the opportunity to discuss directly with Lhasa expert scientists

Over 30 years of experience in developing state-of-the-art in silico prediction and database systems

Lhasa Limited provides an integrated solution to assist in the meeting of the ICH M7 guidelines:


Derek Nexus - an expert software for the prediction of toxicity 

The preferred expert rule-based system for the prediction of toxicity3,4

  • Gives a prediction and transparent supporting evidence to aid in decision making.
  • Expert rule-based systems are accepted under the ICH M7 guideline.
  • Conforms to the validation principles set forth by the Organisation for Economic Co-operation and Development (OECD).

Sarah Nexus - a statistical software for the prediction of mutagenicity 

  • Created with input from the Food and Drug Administration (FDA) under a Research Collaboration Agreement.
  • Conforms to the OECD validation principles.
  • Designed specifically to address the ICH M7 guideline.
  • Unique hierarchical model ensures results are based on data perceived to be of the greatest relevance.

Vitic - chemical database and information management system 

Zeneth - an expert software for the prediction of forced chemical degradation 

  • Can account for intermolecular reactions, allowing consideration of product interactions, interactions between APIs and excipients, and dimerization reactions.
  • Provides insight into relevant degradation pathways to aid decisions for mutagenicity studies.
  • Ability to export predicted degradants for analysis of mutagenicity in Derek and Sarah Nexus (separate licenses required).

Mirabilis - an expert software for the calculation of purge factors of potentially mutagenic impurities in a synthetic route 

  • Can be used to satisfy ICH M7 Control Option 4 by producing an estimated purge factor for removal of an impurity by a synthetic process.
  • Uses an industry-standardised approach to ensure consistency in submissions to regulators.
  • Provides expert commentary and detailed support, enabling justifiable decision-making.

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The FDA's Center for Drug Evaluation and Research accepts submissions from Derek Nexus and Sarah Nexus.

When submitting to regulators, you can make use of Lhasa Limited's reports which are available in a range of formats and are customisable, allowing you to present the pertinent information to support your submission. Reports can include a wealth of supporting information and as a minimum it is recommended that you include details of the version of the software and knowledge base/database used.

Lhasa Limited releases its software updates to members at the same time as its regulatory members, allowing you to make use of up-to-date knowledge when making submissions. As regulators also use current software versions for regulatory assessments, we recommend that you install new releases as soon as possible.

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General Approach

Lhasa Limited can help you to organise the relevant information for an ICH M7 submission. Using the ICH M7 functionality within the Nexus Suite, Derek and Sarah Nexus are brought together to provide the expert rule-based and statistical-based in silico predictions required under ICH M7.

By additionally providing the Nexus Suite with information about the API, a calculation of an ICH M7 classification can be made for a query structure which can take into account in-house or Vitic data.


ICH M7 Classification

The ICH M7 Guideline states that a “Hazard Assessment involves an initial analysis of actual and potential impurities by conducting database and literature searches for carcinogenicity and bacterial mutagenicity data in order to classify them as Class 1, 2, or 5 according to Table 1. If data for such a classification are not available, an assessment of Structure-Activity Relationships (SAR) that focuses on bacterial mutagenicity predictions should be performed1.



Proposed action for control


Known mutagenic carcinogens.

Control at or below compound-specific acceptable limit.


Known mutagen with unknown carcinogenic potential (bacterial mutagenicity positive, no rodent carcinogenicity data)

Control at or below acceptable limits (generic or appropriate TTC)


Alerting structure, unrelated to the structure of the drug substance, no mutagenic data.

Control at or below acceptable limits (generic or appropriate TTC) or run bacterial mutagenicity assay:

If non-mutagenic, treat as Class 5

If mutagenic, treat as Class 2


Alerting structure, same alert in drug substance which has been tested and is non-mutagenic.

Treat as non-mutagenic impurity.


No structural alerts, or alerting structure with sufficient data to demonstrate lack of mutagenicity or carcinogenicity.

Treat as non-mutagenic impurity.


Table 1: Impurities classification with respect to mutagenic and carcinogenic potential and the resulting control actions.

An ICH M7 classification is produced in the Nexus suite based on a calculation derived from the predictions provided by Derek and Sarah and any relevant experimental information (including user-added data or data provided by Vitic).

  • Once a user has uploaded the impurities from a given synthetic scheme and defined the Active Pharmaceutical Ingredient, the ICH M7 functionality within the Nexus suite can be utilised and the calculation is provided.

  • A table is produced which users are able to edit, comment on and save. Users can add their own mutagenicity and carcinogenicity data to the table to assist with their own expert review.

  • Supporting data is provided within the interface to aid an expert’s call. This includes mutagenicity and carcinogenicity data that is used within the Nexus suite. If you have your own data stored in Vitic, the Nexus suite can automatically import it, organise it and use it to make the calculation.

  • The ICH M7 functionality in the Nexus suite can process all of the relevant impurities from a synthetic scheme at once. The results, including any of the user’s own expert annotations, can be saved and stored.



  1. ICH M7 Guideline
  2. OECD Guidance Document on the Validation of (Q)SAR Models
  3. Dobo K. L., Greene N., Fred C., Glowienke S., Harvey J. S., Hasselgren C, et al. (2012). 'In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: an industry survey'. Regul. Toxicol. and Pharmacol. 62(3), 449-55. https://doi.org/10.1016/j.yrtph.2012.01.007
  4. Sutter A., Amberg A., Boyer S., Brigo A., Contrera J. F., Custer L. L., et al. (2013). 'Use of in silico systems and expert knowledge for structure-based assessment of potentially mutagenic impurities'. Regul. Toxicol. and Pharmacol. 67(1), 39-52. https://doi.org/10.1016/j.yrtph.2013.05.001
  5. Waechter, F (2019) ICH M7 - Risk assessment for mutagenic impurities and control strategies

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