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Human Liver Microphysiological System for Assessing Drug-Induced Liver Toxicity In Vitro
Published on: January 31, 2022
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Evaluation of DILI Predictive Hypotheses in Early Drug Development
1Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California , San Francisco, California 94143-0912, United States.
Chemical Research in Toxicology
|March 4, 2017
Summary
Predicting drug-induced liver injury (DILI) is crucial. The Biopharmaceutics Drug Disposition Classification System (BDDCS) shows Class 2 drugs have higher DILI severity, offering a useful benchmark for new prediction methods.
Area of Science:
- Pharmacology
- Drug Development
- Toxicology
Background:
- Drug-induced liver injury (DILI) is a major cause of drug failure and withdrawal.
- DILI risk is linked to daily dose and hepatic metabolism, but early dose prediction is uncertain.
Purpose of the Study:
- To comprehensively analyze published DILI prediction hypotheses.
- To evaluate the Biopharmaceutics Drug Disposition Classification System (BDDCS) against existing DILI prediction methods.
Main Methods:
- Analysis of DILI warnings in FDA-approved drug labels and withdrawal status.
- Comparison of BDDCS classification with methods like Rule of 2 and BSEP inhibition.
- Evaluation of DILI prediction metrics against BDDCS.
Main Results:
- Higher doses (≥50 mg/day) increase DILI potential but aren't solely predictive.
- BDDCS Class 2 drugs exhibit the highest DILI severity.
- Most evaluated methods, without known clinical dose, offer no significant improvement over BDDCS.
Conclusions:
- The BDDCS classification is a valuable tool for evaluating new DILI prediction algorithms.
- Differentiating BDDCS Class 2 from Class 1 drugs enhances DILI risk assessment for extensively metabolized compounds.
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