Literature DB >> 31753250

Quantitative Systems Toxicology Approaches to Understand and Predict Drug-Induced Liver Injury.

Paul B Watkins1.   

Abstract

The DILI-sim Initiative is a public-private partnership using quantitative systems toxicology to build a model (DILIsym) capable of understanding and predicting liver safety liabilities in drug candidates. The effort has provided insights into mechanisms underlying dose-dependent drug-induced liver injury (DILI) and interpatient differences in susceptibility to dose-dependent DILI. DILIsym may be useful in identifying drugs capable of causing idiosyncratic hepatotoxicity. DILIsym is used to optimize interpretation of traditional and newer serum biomarkers of DILI. DILIsym results are considered in drug development decisions. In the future, it may be possible to use DILsym predictions to justify reduction in size of some clinical trials.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  DILI; DILIsym; Modeling; QST; Simulation

Mesh:

Substances:

Year:  2019        PMID: 31753250     DOI: 10.1016/j.cld.2019.09.003

Source DB:  PubMed          Journal:  Clin Liver Dis        ISSN: 1089-3261            Impact factor:   6.126


  4 in total

1.  Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI).

Authors:  Eni Minerali; Daniel H Foil; Kimberley M Zorn; Thomas R Lane; Sean Ekins
Journal:  Mol Pharm       Date:  2020-06-08       Impact factor: 4.939

Review 2.  Challenges and Future of Drug-Induced Liver Injury Research-Laboratory Tests.

Authors:  Sabine Weber; Alexander L Gerbes
Journal:  Int J Mol Sci       Date:  2022-05-27       Impact factor: 6.208

3.  Navigating Between Right, Wrong, and Relevant: The Use of Mathematical Modeling in Preclinical Decision Making.

Authors:  Anna Kondic; Dean Bottino; John Harrold; Jeffrey D Kearns; C J Musante; Aleksandrs Odinecs; Saroja Ramanujan; Jangir Selimkhanov; Birgit Schoeberl
Journal:  Front Pharmacol       Date:  2022-04-12       Impact factor: 5.988

4.  The Challenge of Interpreting Alanine Aminotransferase Elevations in Clinical Trials of New Drug Candidates.

Authors:  Rachel J Church; Paul B Watkins
Journal:  Clin Transl Sci       Date:  2020-10-28       Impact factor: 4.689

  4 in total

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