Toward regulatory acceptance and improving the prediction confidence of in silico approaches: a case study of genotoxicity

ABSTRACT

Introduction: Genotoxicity is an imperative component of the human health safety assessment of chemicals. Its secure forecast is of the utmost importance for all health prevention strategies and regulations.

Areas covered: We surveyed several types of alternative, animal-free approaches ((quantitative) structure–activity relationship (Q)SAR, read-across, Adverse Outcome Pathway, Integrated Approaches to Testing and Assessment) for genotoxicity prediction within the needs of regulatory frameworks, putting special emphasis on data quality and uncertainties issues.

Expert opinion: (Q)SAR models and read-across approaches for in vitro bacterial mutagenicity have sufficient reliability for use in prioritization processes, and as support in regulatory decisions in combination with other types of evidence. (Q)SARs and read-across methodologies for other genotoxicity endpoints need further improvements and should be applied with caution. It appears that there is still large room for improvement of genotoxicity prediction methods. Availability of well-curated high-quality databases, covering a broader chemical space, is one of the most important needs. Integration of in silico predictions with expert knowledge, weight-of-evidence-based assessment, and mechanistic understanding of genotoxicity pathways are other key points to be addressed for the generation of more accurate and trustable results.

KEYWORDS:

• Genotoxicity
• in silico
• (Q)SAR
• read-across
• AOP
• IATA
• uncertainties
• mutagenicity
• weight-of-evidence
• regulatory framework

Article highlights

• In silico prediction of genotoxicity for bacterial mutagenesis has sufficient reliability, while improvements are needed for other genotoxicity endpoints.

• Development of Adverse Outcome Pathways for genotoxicity can increase the predictivity of in silico methods and allow for implementation of predictive models for intermediate key events and development of IATA.

• Integration of evidence –at the best of professional judgement - has a primary role for reaching trustable conclusions.

• Expansion of well curated, high-quality databases, covering a broader chemical space, is needed.

• In order to increase confidence in genotoxicity predictions and to meet regulatory requirements, greater standardization and validation efforts and more effective integration of evidence are necessary.

Abbreviation glossary

(Q)SAR, (quantitative) structure–activity relationship; SAR, structure–activity relationships; IATA, Integrated Approaches to Testing and Assessment; AOP, Adverse Outcome Pathway; KE, key event; KER, key event relationship; MIE, molecular initiating event; AO, adverse outcome; MoA, mode of action; ECHA, European Chemicals Agency; EFSA, European Food Safety Authority; REACH, European Regulation on Registration, Evaluation, Authorisation and Restriction of Chemicals; OECD, Organization for Economic Co-operation and Development; 3Rs, the principles of the 3Rs (replacement, reduction, and refinement) ICH M7, Guideline for Assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk; WoE, weight-of-evidence

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.