Literature DB >> 23258593

High lipophilicity and high daily dose of oral medications are associated with significant risk for drug-induced liver injury.

Minjun Chen1, Jürgen Borlak, Weida Tong.   

Abstract

UNLABELLED: Drug-induced liver injury (DILI) is a leading cause of drug failure in clinical trials and a major reason for drug withdrawals from the market. Although there is evidence that dosages of ≥100 mg/day are associated with increased risk for hepatotoxicity, many drugs are safe at such dosages. There is an unmet need to predict risk for DILI more reliably, and lipophilicity might be a contributing factor. We analyzed the combined factors of daily dose and lipophilicity for 164 US Food and Drug Administration-approved oral medications and observed high risk for hepatotoxicity (odds ratio [OR], 14.05; P < 0.001) for drugs given at dosages ≥100 mg/day and octanol-water partition coefficient (logP) ≥3. This defined the "rule-of-two." Similar results were obtained for an independent set of 179 oral medications with 85% of the rule-of-two positives being associated with hepatotoxicity (OR, 3.89; P < 0.01). Using the World Health Organization's Anatomical Therapeutic Chemical classification system, the rule-of-two performed best in predicting DILI in seven therapeutic categories. Among 15 rule-of-two positives, 14 were withdrawn from hepatotoxic drugs, and one was over-the-counter medication labeled for liver injury. We additionally examined drug pairs that have similar chemical structures and act on the same molecular target but differ in their potential for DILI. Again, the rule-of-two predicted hepatotoxicity reliably. Finally, the rule-of-two was applied to clinical case studies to identify hepatotoxic drugs in complex comedication regimes to further demonstrate its use.
CONCLUSION: Apart from dose, lipophilicity contributes significantly to risk for hepatotoxicity. Applying the rule-of-two is an appropriate means of estimating risk for DILI compared with dose alone.
Copyright © 2012 American Association for the Study of Liver Diseases.

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Year:  2013        PMID: 23258593     DOI: 10.1002/hep.26208

Source DB:  PubMed          Journal:  Hepatology        ISSN: 0270-9139            Impact factor:   17.425


  68 in total

1.  A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the 'rule-of-two' model.

Authors:  Minjun Chen; Chun-Wei Tung; Qiang Shi; Lei Guo; Leming Shi; Hong Fang; Jürgen Borlak; Weida Tong
Journal:  Arch Toxicol       Date:  2014-06-11       Impact factor: 5.153

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4.  Evaluation of DILI Predictive Hypotheses in Early Drug Development.

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Review 5.  Strategies for Early Prediction and Timely Recognition of Drug-Induced Liver Injury: The Case of Cyclin-Dependent Kinase 4/6 Inhibitors.

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8.  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 9.  Pathogenesis of idiosyncratic drug-induced liver injury and clinical perspectives.

Authors:  Robert J Fontana
Journal:  Gastroenterology       Date:  2013-12-31       Impact factor: 22.682

10.  Relationship between characteristics of medications and drug-induced liver disease phenotype and outcome.

Authors:  Raj Vuppalanchi; Raghavender Gotur; K Rajender Reddy; Robert J Fontana; Marwan Ghabril; Andrzej S Kosinski; Jiezhun Gu; Jose Serrano; Naga Chalasani
Journal:  Clin Gastroenterol Hepatol       Date:  2013-12-20       Impact factor: 11.382

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