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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.

SUBMITTER: Chen M

PROVIDER: S-EPMC5753582 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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

Chen Minjun M Tung Chun-Wei CW Shi Qiang Q Guo Lei L Shi Leming L Fang Hong H Borlak Jürgen J Tong Weida W

Archives of toxicology 20140611 7

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 str ...[more]

PMID: 24958025

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Project description:ObjectiveWhile existing guidelines support the treatment of intracranial hypertension in severe traumatic brain injury (TBI), it is unclear when to suspect and initiate treatment for high intracranial pressure (ICP). The objective of this study was to derive a clinical decision rule that accurately predicts intracranial hypertension.MethodsUsing Delphi methods, the authors identified a set of potential predictors of intracranial hypertension and a clinical decision rule a priori by consensus among a group of 43 neurosurgeons and intensivists who have extensive experience managing severe TBI without ICP monitoring. To validate these predictors, the authors used data from a Latin American trial (n = 150; BEST TRIP). To report on the performance of the rule, they calculated sensitivity, specificity, and positive and negative predictive values with 95% confidence intervals. In a secondary analysis, the rule was validated using data from a North American trial (n = 131; COBRIT).ResultsThe final predictors and the clinical decision rule were approved by 97% of participants in the consensus working group. The predictors are divided into major and minor criteria. High ICP would be considered suspected in the presence of 1 major or ≥ 2 minor criteria. Major criteria are: compressed cisterns (CT classification of Marshall diffuse injury [DI] III), midline shift > 5 mm (Marshall DI IV), or nonevacuated mass lesion. Minor criteria are: Glasgow Coma Scale (GCS) motor score ≤ 4, pupillary asymmetry, abnormal pupillary reactivity, or Marshall DI II. The area under the curve for the logistic regression model that contains all the predictors was 0.86. When high ICP was defined as > 22 mm Hg, the decision rule performed with a sensitivity of 93.9% (95% CI 85.0%-98.3%), a specificity of 42.3% (95% CI 31.7%-53.6%), a positive predictive value of 55.5% (95% CI 50.7%-60.2%), and a negative predictive value of 90% (95% CI 77.1%-96.0%). The sensitivity of the clinical decision rule improved with higher ICP cutoffs up to a sensitivity of 100% when intracranial hypertension was defined as ICP > 30 mm Hg. Similar results were found in the North American cohort.ConclusionsA simple clinical decision rule based on a combination of clinical and imaging findings was found to be highly sensitive in distinguishing patients with severe TBI who would suffer intracranial hypertension. It could be used to identify patients who require ICP monitoring in high-resource settings or start ICP-lowering treatment in environments where resource limitations preclude invasive monitoring.Clinical trial registration no.: NCT02059941 (clinicaltrials.gov).

Dataset Information

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

Publications

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

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