Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities

  title={Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities},
  author={Elena Fioravanzo and Arianna Bassan and Manuela Pavan and Aleksandra Mostrag-Szlichtyng and Andrew Paul Worth},
  journal={SAR and QSAR in Environmental Research},
  pages={257 - 277}
The toxicological assessment of genotoxic impurities is important in the regulatory framework for pharmaceuticals. In this context, the application of promising computational methods (e.g. Quantitative Structure–Activity Relationships (QSARs), Structure–Activity Relationships (SARs) and/or expert systems) for the evaluation of genotoxicity is needed, especially when very limited information on impurities is available. To gain an overview of how computational methods are used internationally in… 

The Consultancy Activity on In Silico Models for Genotoxic Prediction of Pharmaceutical Impurities.

Two main applications of in silico methods are presented: support and optimization of drug synthesis processes by providing early indication of potentialgenotoxic impurities and regulatory evaluation of genotoxic potential of impurities in compliance with the ICH M7 guideline.

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

It appears that there is still large room for improvement of genotoxicity prediction methods, and availability of well-curated high-quality databases, covering a broader chemical space, is one of the most important needs.

Latest advances in computational genotoxicity prediction

In silico prediction of genotoxicity is a fundamental part of screening strategies for the assessment genotoxic impurities in drug products and the concept of using chemical similarity to infer mutagenic potential from one of known activity to another whose activity is unknown remains a scientific challenge.

'In silico' toxicology methods in drug safety assessment

This review will summarize current state-of-the-art scientific data on the use of in silico methods in toxicity testing, taking into account their shortcomings, and highlighting the strategies that should deliver consistent results, while covering the applications of inSilicon methods in preclinical trials and drug impurities toxicity testing.

Carcinogenicity Assessment for Risk Factors in Food::Current Issues and a Proposal

In the future, in silico and in vitro approaches will be powerful tools for screening genotoxic and carcinogenic potentials of a number of chemicals/agents and WOE approaches based on MOA may be extremely useful.

In silico prediction of the mutagenicity of nitroaromatic compounds using a novel two-QSAR approach.



The Applicability of Software Tools for Genotoxicity and Carcinogenicity Prediction: Case Studies relevant to the Assessment of Pesticides

This report presents research results obtained in the framework of a project on the Applicability of Quantitative Structure-Activity Relationship (QSAR) analysis in the evaluation of the

Review of QSAR Models and Software Tools for Predicting of Genotoxicity and Carcinogenicity

The most useful models are those which are implemented in software tools and associated with transparent documentation on the model development and validation process, and these require more specialised expertise than other tools that are aimed primarily at end-users such as risk assessors.

An update on the genotoxicity and carcinogenicity of marketed pharmaceuticals with reference to in silico predictivity

  • R. Snyder
  • Biology
    Environmental and molecular mutagenesis
  • 2009
Supporting evidence is presented for the idea that the presence of an N‐dialkyl group or piperidine aryl ketone may somehow be associated with genotoxicity, perhaps through DNA intercalation and consequent DNA topoisomerase II inhibition.

Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices.

Predictivity and Reliability of QSAR Models: The Case of Mutagens and Carcinogens

Overall, the (Q)SAR-based predictions are able to significantly enrich the target of safer chemicals, contribute to the organization and rationalization of data, elucidate mechanisms of action, and complement data from other sources.

Prediction of the Rodent Carcinogenicity of 60 Pesticides by the DEREKfW Expert System

The capacity of the DEREKfW expert system to qualitatively predict the rodent carcinogenicity and the genotoxic potential of 60 pesticides recently registered in Switzerland was tested and the percentage of false negatives was found to be 31%.

The Expanding Role of Predictive Toxicology: An Update on the (Q)SAR Models for Mutagens and Carcinogens

  • R. BenigniT. Netzeva Chihae Yang
  • Environmental Science
    Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews
  • 2007
Findings from the survey on (Q)SARs for mutagenicity and carcinogenicity are summarized, key aspects are discussed, and a broader view towards future needs and perspectives is given.