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Updated: Apr 21, 2026
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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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Methodology to assess clinical liver safety data
Michael Merz1, Kwan R Lee, Gerd A Kullak-Ublick
1Discovery and Investigative Safety, Novartis Institutes for BioMedical Research, Klybeckstrasse 141, WKL-135.1.78, 4057, Basel, Switzerland, michael.merz@novartis.com.
Drug Safety
|October 30, 2014
Summary
Graphical data exploration and outlier detection enhance liver safety assessments in clinical trials. These methods improve the evaluation of drug-induced liver injury (DILI) by considering time-dependent data and extreme values.
Area of Science:
- Hepatology
- Clinical Pharmacology
- Biostatistics
Background:
- Liver safety data analysis requires multivariate and time-dependent approaches.
- Current standard assessment tools (tables, listings, narratives) have limitations.
- Drug-induced liver injury (DILI) assessment needs effective evaluation of extreme values.
Purpose of the Study:
- To discuss best practices for assessing DILI in clinical trials.
- To explore advanced methods for liver safety data interpretation.
- To improve the completeness and accuracy of liver safety evaluations.
Main Methods:
- Systematic graphical data exploration with predefined templates.
- Interactive graphical workflows for team-based analysis.
- Statistical outlier detection for identifying extreme values.
Main Results:
- Graphical workflows enhance completeness of evaluation and support hypothesis generation/testing.
- Interactive analysis facilitates identification of suitable graphics for reporting.
- Statistical outlier detection is more relevant than central tendency measures for DILI.
Conclusions:
- Systematic graphical exploration and outlier detection can significantly improve clinical liver safety data assessment.
- These methods offer potential for better interpretation of DILI.
- Advanced analytical approaches are crucial for robust drug safety evaluations.
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