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

Minjun Chen, Chun Wei Tung, Qiang Shi, Lei Guo, Leming Shi, Hong Fang, Jürgen Borlak, Weida Tong

Research output: Contribution to journalArticle

35 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1439-1449
Number of pages11
JournalArchives of Toxicology
Volume88
Issue number7
DOIs
Publication statusPublished - Jan 1 2014
Externally publishedYes

Fingerprint

Chemical and Drug Induced Liver Injury
Liver
Assays
Testing
Pharmaceutical Preparations
Screening
Drug Discovery
Cell Nucleus Size
Mitochondrial Membrane Potential
DNA Fragmentation
DNA Damage
Hepatocytes
Drug therapy
Apoptosis
Cytokines
Rats

Keywords

  • DILI
  • Drug safety assessment
  • Drug-induced liver injury
  • High-content screening assay
  • Primary rat hepatocytes

ASJC Scopus subject areas

  • Toxicology
  • Health, Toxicology and Mutagenesis
  • Medicine(all)

Cite this

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; Tung, Chun Wei; Shi, Qiang; Guo, Lei; Shi, Leming; Fang, Hong; Borlak, Jürgen; Tong, Weida.

In: Archives of Toxicology, Vol. 88, No. 7, 01.01.2014, p. 1439-1449.

Research output: Contribution to journalArticle

Chen, Minjun ; Tung, Chun Wei ; Shi, Qiang ; Guo, Lei ; Shi, Leming ; Fang, Hong ; Borlak, Jürgen ; Tong, Weida. / A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the 'rule-of-two' model. In: Archives of Toxicology. 2014 ; Vol. 88, No. 7. pp. 1439-1449.
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