A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the 'rule-of-two' model

Abstract

Drug-induced liver injury (DILI) is a major cause of drug failures in both the preclinical and clinical phase. Consequently, improving prediction of DILI at an early stage of drug discovery will reduce the potential failures in the subsequent drug development program. In this regard, high-content screening (HCS) assays are considered as a promising strategy for the study of DILI; however, the predictive performance of HCS assays is frequently insufficient. In the present study, a new testing strategy was developed to improve DILI prediction by employing in vitro assays that was combined with the RO2 model (i.e., 'rule-of-two' defined by daily dose ≥100 mg/day & logP ≥3). The RO2 model was derived from the observation that high daily doses and lipophilicity of an oral medication were associated with significant DILI risk in humans. In the developed testing strategy, the RO2 model was used for the rational selection of candidates for HCS assays, and only the negatives predicted by the RO2 model were further investigated by HCS. Subsequently, the effects of drug treatment on cell loss, nuclear size, DNA damage/fragmentation, apoptosis, lysosomal mass, mitochondrial membrane potential, and steatosis were studied in cultures of primary rat hepatocytes. Using a set of 70 drugs with clear evidence of clinically relevant DILI, the testing strategy improved the accuracies by 10 % and reduced the number of drugs requiring experimental assessment by approximately 20 %, as compared to the HCS assay alone. Moreover, the testing strategy was further validated by including published data (Cosgrove et al. in Toxicol Appl Pharmacol 237:317-330, 2009) on drug-cytokine-induced hepatotoxicity, which improved the accuracies by 7 %. Taken collectively, the proposed testing strategy can significantly improve the prediction of in vitro assays for detecting DILI liability in an early drug discovery phase.

Fig. 1

An illustration of a high-content screening assay and its measurement of DNA damage. The left side displays the images from the HCS assay, including the treatment with zafirlukast and the DMSO control. The right side shows 10 half-sequence doses and their dose–response curve. The EC₅₀ of DNA damage was calculated from this dose–response curve

Fig. 2

Flowchart of the new testing strategy integrating the in vitro assays with the RO2 model. Specifically, the in vitro assay was applied to the negatives predicted from the RO2 model to further stratify candidate selection and thereby improve the sensitivity. The drugs predicted to be positive by the RO2 model are not considered for further experimental test. The numbers of drugs requiring experimental tests are listed in Tables 4 and 5

Fig. 3

Overview of the measured cellular endpoints of the HCS assay. a The distribution of measured cellular endpoints. b The distribution of harmless ratio grouped by drug label sections, including Box Warning, Warnings and Precautions, Adverse Reactions, and No Match. Two-sided t-tests were applied to compare the harmless ratios of Box Warning, Warnings and Precautions, or Adverse Reactions groups versus the No Match group, and the derived p values were marked