Mechanism-based drug safety testing using innovative <i>in vitro</i> liver models: from DILI prediction to idiosyncratic DILI liability assessment

Idiosyncratic drug-induced liver injury (iDILI) remains unpredictable. As adverse responses arise in a small fraction of patients, drugs often fail in later drug development stages or post-approval, thereby tremendously increasing costs and putting patients at risk, highlighting the need for accurate early identification of iDILI liabilities. Using articles from the last five years (PubMed), iDILI risk factors are described, <i>in vitro</i> liver models and mechanism-based readout strategies are evaluated on their potential to enable iDILI liability assessment. Various <i>in vitro</i> liver models are established for disease modeling and DILI prediction. Drawbacks for each of these seem inevitable, making the evaluation of their application domain and iDILI liability assessment potential crucial. A tiered approach could be considered, whereby compounds are initially screened and flagged using simple fit-for-purpose models for DILI prediction, followed by multicellular liver models that integrate the current knowledge of iDILI onset in combination with mechanistic readouts. Multiplexing models within an integrated mechanism-based testing strategy could improve the safety assessment accuracy. Defined <i>in vitro</i> models should integrate critical hepatocyte intrinsic risk factors as well as adaptive immune system components to refine iDILI liability assessment.

特发性药物性肝损伤（Idiosyncratic Drug-Induced Liver Injury, iDILI）至今仍难以预测。由于仅少数患者会出现此类不良反应，药物常在后期研发阶段或获批上市后宣告失败，不仅大幅推高研发成本，还会使患者面临健康风险，因此亟需精准早期识别可引发iDILI的药物隐患。本文依托PubMed数据库近五年的文献，阐述了iDILI的危险因素，并评估了各类体外（in vitro）肝模型及基于机制的检测读出策略在iDILI隐患评估中的应用潜力。目前已建立多种体外肝模型用于疾病建模及药物性肝损伤（Drug-Induced Liver Injury, DILI）预测，但此类模型均存在难以避免的局限性，因此评估其适用范围及iDILI隐患评估能力至关重要。可考虑采用分层评估策略：首先利用简易的适配型模型对化合物进行DILI预测初筛与标记，随后借助整合当前iDILI发病机制认知的多细胞肝模型，并结合机制性检测读出手段开展后续评估。将多种模型整合至基于机制的一体化检测策略中，可提升安全性评估的精准度。理想的体外模型应整合关键的肝细胞内在危险因素及适应性免疫系统组分，以优化iDILI隐患评估效果。