Ellison, CM, Hewitt, M and Przybylak, K 2022, 'In silico models for hepatotoxicity' , in: In Silico Methods for Predicting Drug Toxicity (2nd edition) , Methods in Molecular Biology (2425) , Springer, pp. 355-392.
Full text not available from this repository. (Request a copy)Abstract
In this chapter, we review the state of the art of predicting human hepatotoxicity using in silico techniques. There has been significant progress in this area over the past 20 years but there are still some challenges ahead. Principally, these challenges are our partial understanding of a very complex biochemical system and our ability to emulate that in a predictive capacity. Here, we provide an overview of the published modeling approaches in this area to date and discuss their design, strengths and weaknesses. It is interesting to note the diversity in modeling approaches, whether they be statistical algorithms or evidenced-based approaches including structural alerts and pharmacophore models. Irrespective of modeling approach, it appears a common theme of access to appropriate, relevant, and high-quality data is a limitation to all and is likely to continue to be the focus of future research. [Abstract copyright: © 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.]
| Item Type: | Book Section |
|---|---|
| Editors: | Benfenati, E |
| Schools: | Schools > School of Environment and Life Sciences |
| Journal or Publication Title: | Methods in molecular biology (Clifton, N.J.) |
| Publisher: | Springer |
| Series Name: | Methods in Molecular Biology |
| ISBN: | 9781071619599 (hardcover); 9781071619629 (softcover); 9781071619605 (ebook) |
| ISSN: | 1064-3745 |
| Related URLs: | |
| SWORD Depositor: | Publications Router |
| Depositing User: | Publications Router |
| Date Deposited: | 16 May 2022 11:57 |
| Last Modified: | 16 May 2022 11:57 |
| URI: | https://usir.salford.ac.uk/id/eprint/63325 |
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