6533b833fe1ef96bd129b593

RESEARCH PRODUCT

Applications of Chemoinformatics in Predictive Toxicology for Regulatory Purposes, Especially in the Context of the EU REACH Legislation

Rafael GozalbesJesús Vicente De Julián-ortiz

subject

0301 basic medicineEngineeringbusiness.industryManagement scienceLegislationContext (language use)Predictive toxicology010501 environmental sciencescomputer.software_genre01 natural sciences03 medical and health sciences030104 developmental biologyCheminformaticsData miningbusinesscomputer0105 earth and related environmental sciences

description

Chemoinformatics methodologies such as QSAR/QSPR have been used for decades in drug discovery projects, especially for the finding of new compounds with therapeutic properties and the optimization of ADME properties on chemical series. The application of computational techniques in predictive toxicology is much more recent, and they are experiencing an increasingly interest because of the new legal requirements imposed by national and international regulations. In the pharmaceutical field, the US Food and Drug Administration (FDA) support the use of predictive models for regulatory decision-making when assessing the genotoxic and carcinogenic potential of drug impurities. In Europe, the REACH legislation promotes the use of QSAR in order to reduce the huge amount of animal testing needed to demonstrate the safety of new chemical entities subjected to registration, provided they meet specific conditions to ensure their quality and predictive power. In this review, the authors summarize the state of art of in silico methods for regulatory purposes, with especial emphasis on QSAR models.

https://doi.org/10.4018/ijqspr.2018010101