In silico toxicology protocols

https://doi.org/10.1016/j.yrtph.2018.04.014Get rights and content
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Highlights

  • General outline of in silico toxicology protocols is described.

  • A reliability score for predictions alongside experimental data is discussed.

  • A checklist for performing an expert review of the in silico results is outlined.

  • A hazard assessment framework is proposed that includes in silico results.

Abstract

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

Keywords

In silico
In silico toxicology
Computational toxicology
Predictive toxicology
QSAR
Expert alert
Expert review

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