4.6 Article

Overview of Causality Assessment for Drug-Induced Liver Injury (DILI) in Clinical Trials

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DRUG SAFETY
卷 44, 期 6, 页码 619-634

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ADIS INT LTD
DOI: 10.1007/s40264-021-01051-5

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This manuscript evaluates the challenges and complexity of causality assessment for drug-induced liver injury (DILI) and proposes a minimal data set and best practices for assessing causality.
Causality assessment for suspected drug-induced liver injury (DILI) during drug development and following approval is challenging. The IQ DILI Causality Working Group (CWG), in collaboration with academic and regulatory subject matter experts (SMEs), developed this manuscript with the following objectives: (1) understand and describe current practices; (2) evaluate the utility of new tools/methods/practice guidelines; (3) propose a minimal data set needed to assess causality; (4) define best practices; and (5) promote a more structured and universal approach to DILI causality assessment for clinical development. To better understand current practices, the CWG performed a literature review, took a survey of member companies, and collaborated with SMEs. Areas of focus included best practices for causality assessment during clinical development, utility of adjudication committees, and proposals for potential new avenues to improve causality assessment. The survey and literature review provided renewed understanding of the complexity and challenges of DILI causality assessment as well as the use of non-standardized approaches. Potential areas identified for consistency and standardization included role and membership of adjudication committees, standardized minimum dataset, updated assessment tools, and best practices for liver biopsy and rechallenge in the setting of DILI. Adjudication committees comprised of SMEs (i.e., utilizing expert opinion) remain the standard for DILI causality assessment. A variety of working groups continue to make progress in pursuing new tools to assist with DILI causality assessment. The minimum dataset deemed adequate for causality assessment provides a path forward for standardization of data collection in the setting of DILI. Continued progress is necessary to optimize and advance innovative tools necessary for the scientific, pharmaceutical, and regulatory community.

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