Issue 4, 2023

Towards higher scientific validity and regulatory acceptance of predictive models for PFAS

Abstract

Per- and polyfluoroalkyl substances (PFAS) are widespread in the environment. Properly developed QSAR/QSPR models can be used to assess the impact of these chemicals on humans and the environment. This work assesses 38 in silico models developed for this group of compounds, which mainly show physicochemical (22), and also toxic (8) and ecotoxic (8) properties. The evaluation of the models was carried out based on the (Q)SAR Model Reporting Format (QMRF), which was found in the QSAR Database (5) or was prepared manually, according to the information contained in scientific publications based on the QMRFEditor-v3.0.0 format (33). We based our evaluations on an individual assessment of each of the OECD principles described in the document and then summing up everything together. During the analysis, we identified 22 models as scientifically valid and could be used in the prediction of new compounds. Twelve of them contained all the information necessary to reproduce the model, and another 10, despite the lack of some information, are still reproducible. The other 16 models do not contain enough information to reproduce them and therefore they are scientifically invalid. The present work allows identifying the remaining gaps, needs, and recommendations that should be considered in further development of predictive models in the PFAS area.

Graphical abstract: Towards higher scientific validity and regulatory acceptance of predictive models for PFAS

Supplementary files

Article information

Article type
Critical Review
Submitted
17 Nov 2022
Accepted
04 Jan 2023
First published
10 Feb 2023
This article is Open Access
Creative Commons BY-NC license

Green Chem., 2023,25, 1261-1275

Towards higher scientific validity and regulatory acceptance of predictive models for PFAS

A. Sosnowska, N. Bulawska, D. Kowalska and T. Puzyn, Green Chem., 2023, 25, 1261 DOI: 10.1039/D2GC04341F

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. You can use material from this article in other publications, without requesting further permission from the RSC, provided that the correct acknowledgement is given and it is not used for commercial purposes.

To request permission to reproduce material from this article in a commercial publication, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party commercial publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements