The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches

There is international interest in using alternatives to animal testing, including (Q)SARs, in chemical hazard assessments. The regulatory acceptance of alternative methods requires principles for considering the scientific rigour of methods and their results. The OECD (Q)SAR assessment Framework (QAF) was developed as guidance for regulators when considering (Q)SAR models and predictions in chemical evaluation. The QAF builds on existing principles for evaluating models and, learning from the longstanding regulatory experience in assessing (Q)SAR predictions, establishes new principles for evaluating predictions and results from multiple predictions. Assessment elements, identified for all principles lay out criteria for assessing the confidence and uncertainties in (Q)SAR models and predictions, while maintaining the flexibility necessary to adapt to different regulatory contexts and purposes. Using the QAF, assessors can consistently and transparently evaluate and decide on the validity of (Q)SARs, and model developers and users have clear requirements to meet. The publication of the QAF is expected to increase the regulatory use and acceptance of (Q)SARs and may become an example to build similar prescriptive frameworks for other new approach methodologies (NAMs). This article provides an overview of the main scientific aspects of the QAF guidance and provides context for how this guidance can promote the use of alternative methods in chemical assessments.

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Publication Details

Journal
Computational Toxicology
Published
2024-08-12
DOI
https://doi.org/10.1016/j.comtox.2024.100326
Citations
27
Primary Topic
Delphi Technique in Research
Type
article
Field-Weighted Citation Impact
30.56
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article

The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches

Patience Browne, Olga Tcheremenskaia, Cecilia Bossa, Chiara Laura Battistelli et al.
27 citations
Computational Toxicology
Delphi Technique in Research
30.56
article

The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches

Patience Browne, Olga Tcheremenskaia, Cecilia Bossa, Chiara Laura Battistelli, Andrea Gissi
article en
27 citations

Abstract

There is international interest in using alternatives to animal testing, including (Q)SARs, in chemical hazard assessments. The regulatory acceptance of alternative methods requires principles for considering the scientific rigour of methods and their results. The OECD (Q)SAR assessment Framework (QAF) was developed as guidance for regulators when considering (Q)SAR models and predictions in chemical evaluation. The QAF builds on existing principles for evaluating models and, learning from the longstanding regulatory experience in assessing (Q)SAR predictions, establishes new principles for evaluating predictions and results from multiple predictions. Assessment elements, identified for all principles lay out criteria for assessing the confidence and uncertainties in (Q)SAR models and predictions, while maintaining the flexibility necessary to adapt to different regulatory contexts and purposes. Using the QAF, assessors can consistently and transparently evaluate and decide on the validity of (Q)SARs, and model developers and users have clear requirements to meet. The publication of the QAF is expected to increase the regulatory use and acceptance of (Q)SARs and may become an example to build similar prescriptive frameworks for other new approach methodologies (NAMs). This article provides an overview of the main scientific aspects of the QAF guidance and provides context for how this guidance can promote the use of alternative methods in chemical assessments.

Computational ToxicologyVol. 31
Organisation de Coopération et de Développement Economiques (FR), Istituto Superiore di Sanità (IT), Finnish Safety and Chemicals Agency (FI), European Chemicals Agency
Openalex Percentile: Top 0%
Delphi Technique in Research
30.56
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The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches — Patience Browne, Olga Tcheremenskaia, et al. · Computational Toxicology (2024) | TGRS Research Map | TGRS