A novel phenotype-based drug-induced liver injury causality assessment tool (DILI-CAT) allows for signal confirmation in early drug development.

Journal Article (Journal Article)

BACKGROUND: Drug-induced liver injury (DILI) requires accurate case adjudication, with expert opinion being the current best practice. AIM: We utilised a novel DILI causality assessment tool (DILI-CAT), which uses drug-specific liver injury phenotypes, to examine potential DILI in early phase ximelagatran clinical development. METHODS: We conducted a retrospective analysis of liver injury events from four Stroke Prevention using an ORal Thrombin Inhibitor in Atrial Fibrillation (SPORTIF) trials, in which patients were randomised to receive oral ximelagatran or adjusted-dose warfarin. A stepwise process was used with iterative adjustments. The DILI phenotype was characterised by latency, R-value, and AST/ALT ratio. A scoring algorithm was applied to liver events to assess how closely the liver events matched the Interquatile-Range for the working phenotype for each of the three parameters. FINDINGS: Data from 3115 patients included in the SPORTIF trials as above were available. The initial ximelagatran phenotype was developed based on five liver injury cases from the ximelagatran arm and was then validated against an additional eight cases (5 ximelagatran, 3 warfarin); in these eight cases, there was a statistically significant difference in the total DILI-CAT scores of the two drugs (p = 0.016) between ximelagatran and warfarin. Together, these ten ximelagatran cases generated a second, refined ximelagatran phenotype, which was validated against an additional 75 cases (53 ximelagatran/22 warfarin)-again with statistically significant different DILI-CAT ximelagatran vs. warfarin scores (p < 0.001). CONCLUSION: DILI-CAT, a clinically intuitive, data-driven, computer-assisted scoring algorithm, is a useful tool for early detection of drug's hepatotoxicity in clinical drug development.

Full Text

Duke Authors

Cited Authors

  • Hermann, RP; Rockey, DC; Suzuki, A; Merz, M; Tillmann, HL

Published Date

  • April 2022

Published In

Volume / Issue

  • 55 / 8

Start / End Page

  • 1028 - 1037

PubMed ID

  • 35266155

Pubmed Central ID

  • PMC9164935

Electronic International Standard Serial Number (EISSN)

  • 1365-2036

Digital Object Identifier (DOI)

  • 10.1111/apt.16836


  • eng

Conference Location

  • England