In silico models for hepatotoxicity

Ellison, CM; Hewitt, M; Przybylak, K

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.]

Citation

Ellison, C., Hewitt, M., & Przybylak, K. (2022). In silico models for hepatotoxicity. In E. Benfenati (Ed.), In Silico Methods for Predicting Drug Toxicity (2nd edition) (355-392). Springer. https://doi.org/10.1007/978-1-0716-1960-5_14

• Online Publication Date: Jan 1, 2022
• Publication Date: Jan 1, 2022
• Deposit Date: May 16, 2022
• Pages: 355-392
• Series Title: Methods in Molecular Biology
• Series Number: 2425
• Book Title: In Silico Methods for Predicting Drug Toxicity (2nd edition)
• ISBN: 9781071619599-(hardcover);-9781071619629-(softcover);-9781071619605-(ebook)
• DOI: https://doi.org/10.1007/978-1-0716-1960-5_14
• Publisher URL: https://doi.org/10.1007/978-1-0716-1960-5_14
• Related Public URLs: https://doi.org/10.1007/978-1-0716-1960-5