ArticleFrontiers in toxicology2026
AI-enhanced clinical trial-in-a-dish platform for improved DILI risk classification and mechanistic insights into hepatotoxicity.
Article in Frontiers in toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Drug-induced liver injury (DILI) remains a leading cause of clinical trial attrition and post-marketing drug withdrawals. Its prediction is hindered by the limited physiological relevance and interindividual variability captured in conventional preclinical models. To overcome this, we developed a human serum-derived educated spheroid system incorporating human blood sera from donors to generate liver spheroids that recapitulate human hepatic diversity. This platform enables clinical trial-in-a-dish studies and supports acute and chronic treatment regimens. Using a panel of drugs spanning the full DILI risk spectrum, we evaluated hepatotoxic potential through a proprietary AI-driven algorithm that integrates severity and incidence metrics at therapeutic concentrations. Our platform reliably distinguished low-risk from high-risk DILI compounds and recapitulated both dose-dependent and idiosyncratic toxicity profiles. Notably, ximelagatran-induced DILI was only detected under chronic exposure conditions, mirroring clinical outcomes. Transcriptomic profiling revealed innate immune activation in DILI-positive individuals. STRING analysis further implicated HLA-DRB1 and HLA-DQA1 interactions via
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