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Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation
High-throughput (HT) in vitro to in vivo extrapolation (IVIVE) is an integral component in new approach method (NAM)-based risk assessment paradigms, for rapidly translating in vitro toxicity assay results into the context of in vivo exposure. When coupled with rapid exposure predictions, HT-IVIVE s...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099212/ https://www.ncbi.nlm.nih.gov/pubmed/35573278 http://dx.doi.org/10.3389/ftox.2022.894569 |
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author | Moreau, Marjory Mallick, Pankajini Smeltz, Marci Haider, Saad Nicolas, Chantel I. Pendse, Salil N. Leonard, Jeremy A. Linakis, Matthew W. McMullen, Patrick D. Clewell, Rebecca A. Clewell, Harvey J. Yoon, Miyoung |
author_facet | Moreau, Marjory Mallick, Pankajini Smeltz, Marci Haider, Saad Nicolas, Chantel I. Pendse, Salil N. Leonard, Jeremy A. Linakis, Matthew W. McMullen, Patrick D. Clewell, Rebecca A. Clewell, Harvey J. Yoon, Miyoung |
author_sort | Moreau, Marjory |
collection | PubMed |
description | High-throughput (HT) in vitro to in vivo extrapolation (IVIVE) is an integral component in new approach method (NAM)-based risk assessment paradigms, for rapidly translating in vitro toxicity assay results into the context of in vivo exposure. When coupled with rapid exposure predictions, HT-IVIVE supports the use of HT in vitro assays for risk-based chemical prioritization. However, the reliability of prioritization based on HT bioactivity data and HT-IVIVE can be limited as the domain of applicability of current HT-IVIVE is generally restricted to intrinsic clearance measured primarily in pharmaceutical compounds. Further, current approaches only consider parent chemical toxicity. These limitations occur because current state-of-the-art HT prediction tools for clearance and metabolite kinetics do not provide reliable data to support HT-IVIVE. This paper discusses current challenges in implementation of IVIVE for prioritization and risk assessment and recommends a path forward for addressing the most pressing needs and expanding the utility of IVIVE. |
format | Online Article Text |
id | pubmed-9099212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90992122022-05-14 Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation Moreau, Marjory Mallick, Pankajini Smeltz, Marci Haider, Saad Nicolas, Chantel I. Pendse, Salil N. Leonard, Jeremy A. Linakis, Matthew W. McMullen, Patrick D. Clewell, Rebecca A. Clewell, Harvey J. Yoon, Miyoung Front Toxicol Toxicology High-throughput (HT) in vitro to in vivo extrapolation (IVIVE) is an integral component in new approach method (NAM)-based risk assessment paradigms, for rapidly translating in vitro toxicity assay results into the context of in vivo exposure. When coupled with rapid exposure predictions, HT-IVIVE supports the use of HT in vitro assays for risk-based chemical prioritization. However, the reliability of prioritization based on HT bioactivity data and HT-IVIVE can be limited as the domain of applicability of current HT-IVIVE is generally restricted to intrinsic clearance measured primarily in pharmaceutical compounds. Further, current approaches only consider parent chemical toxicity. These limitations occur because current state-of-the-art HT prediction tools for clearance and metabolite kinetics do not provide reliable data to support HT-IVIVE. This paper discusses current challenges in implementation of IVIVE for prioritization and risk assessment and recommends a path forward for addressing the most pressing needs and expanding the utility of IVIVE. Frontiers Media S.A. 2022-04-29 /pmc/articles/PMC9099212/ /pubmed/35573278 http://dx.doi.org/10.3389/ftox.2022.894569 Text en Copyright © 2022 Moreau, Mallick, Smeltz, Haider, Nicolas, Pendse, Leonard, Linakis, McMullen, Clewell, Clewell and Yoon. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Toxicology Moreau, Marjory Mallick, Pankajini Smeltz, Marci Haider, Saad Nicolas, Chantel I. Pendse, Salil N. Leonard, Jeremy A. Linakis, Matthew W. McMullen, Patrick D. Clewell, Rebecca A. Clewell, Harvey J. Yoon, Miyoung Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation |
title | Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation |
title_full | Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation |
title_fullStr | Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation |
title_full_unstemmed | Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation |
title_short | Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation |
title_sort | considerations for improving metabolism predictions for in vitro to in vivo extrapolation |
topic | Toxicology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099212/ https://www.ncbi.nlm.nih.gov/pubmed/35573278 http://dx.doi.org/10.3389/ftox.2022.894569 |
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