Cargando…
Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides
BACKGROUND: In silico methods for toxicity prediction have increased significantly in recent years due to the 3Rs principle. This also applies to predicting reproductive toxicology, which is one of the most critical factors in pesticide approval. The widely used quantitative structure–activity relat...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545887/ https://www.ncbi.nlm.nih.gov/pubmed/35748219 http://dx.doi.org/10.1002/bdr2.2062 |
_version_ | 1784804918650994688 |
---|---|
author | Weyrich, Anastasia Joel, Madeleine Lewin, Geertje Hofmann, Thomas Frericks, Markus |
author_facet | Weyrich, Anastasia Joel, Madeleine Lewin, Geertje Hofmann, Thomas Frericks, Markus |
author_sort | Weyrich, Anastasia |
collection | PubMed |
description | BACKGROUND: In silico methods for toxicity prediction have increased significantly in recent years due to the 3Rs principle. This also applies to predicting reproductive toxicology, which is one of the most critical factors in pesticide approval. The widely used quantitative structure–activity relationship (QSAR) models use experimental toxicity data to create a model that relates experimentally observed toxicity to molecular structures to predict toxicity. Aim of the study was to evaluate the available prediction models for developmental and reproductive toxicity regarding their strengths and weaknesses in a pesticide database. METHODS: The reproductive toxicity of 315 pesticides, which have a GHS classification by ECHA, was compared with the prediction of different in silico models: VEGA, OECD (Q)SAR Toolbox, Leadscope Model Applier, and CASE Ultra by MultiCASE. RESULTS: In all models, a large proportion (up to 77%) of all pesticides were outside the chemical space of the model. Analysis of the prediction of remaining pesticides revealed a balanced accuracy of the models between 0.48 and 0.66. CONCLUSION: Overall, predictions were only meaningful in rare cases and therefore always require evaluation by an expert. The critical factors were the underlying data and determination of molecular similarity, which offer great potential for improvement. |
format | Online Article Text |
id | pubmed-9545887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95458872022-10-14 Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides Weyrich, Anastasia Joel, Madeleine Lewin, Geertje Hofmann, Thomas Frericks, Markus Birth Defects Res Research Articles BACKGROUND: In silico methods for toxicity prediction have increased significantly in recent years due to the 3Rs principle. This also applies to predicting reproductive toxicology, which is one of the most critical factors in pesticide approval. The widely used quantitative structure–activity relationship (QSAR) models use experimental toxicity data to create a model that relates experimentally observed toxicity to molecular structures to predict toxicity. Aim of the study was to evaluate the available prediction models for developmental and reproductive toxicity regarding their strengths and weaknesses in a pesticide database. METHODS: The reproductive toxicity of 315 pesticides, which have a GHS classification by ECHA, was compared with the prediction of different in silico models: VEGA, OECD (Q)SAR Toolbox, Leadscope Model Applier, and CASE Ultra by MultiCASE. RESULTS: In all models, a large proportion (up to 77%) of all pesticides were outside the chemical space of the model. Analysis of the prediction of remaining pesticides revealed a balanced accuracy of the models between 0.48 and 0.66. CONCLUSION: Overall, predictions were only meaningful in rare cases and therefore always require evaluation by an expert. The critical factors were the underlying data and determination of molecular similarity, which offer great potential for improvement. John Wiley & Sons, Inc. 2022-06-24 2022-08-15 /pmc/articles/PMC9545887/ /pubmed/35748219 http://dx.doi.org/10.1002/bdr2.2062 Text en © 2022 The Authors. Birth Defects Research published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Weyrich, Anastasia Joel, Madeleine Lewin, Geertje Hofmann, Thomas Frericks, Markus Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides |
title | Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides |
title_full | Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides |
title_fullStr | Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides |
title_full_unstemmed | Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides |
title_short | Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides |
title_sort | review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: a case study on pesticides |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545887/ https://www.ncbi.nlm.nih.gov/pubmed/35748219 http://dx.doi.org/10.1002/bdr2.2062 |
work_keys_str_mv | AT weyrichanastasia reviewofthestateofscienceandevaluationofcurrentlyavailableinsilicopredictionmodelsforreproductiveanddevelopmentaltoxicityacasestudyonpesticides AT joelmadeleine reviewofthestateofscienceandevaluationofcurrentlyavailableinsilicopredictionmodelsforreproductiveanddevelopmentaltoxicityacasestudyonpesticides AT lewingeertje reviewofthestateofscienceandevaluationofcurrentlyavailableinsilicopredictionmodelsforreproductiveanddevelopmentaltoxicityacasestudyonpesticides AT hofmannthomas reviewofthestateofscienceandevaluationofcurrentlyavailableinsilicopredictionmodelsforreproductiveanddevelopmentaltoxicityacasestudyonpesticides AT frericksmarkus reviewofthestateofscienceandevaluationofcurrentlyavailableinsilicopredictionmodelsforreproductiveanddevelopmentaltoxicityacasestudyonpesticides |