FDA-approved drug labeling for the study of drug-induced liver injury

Chen, Minjun; Vijay, Vikrant; Shi, Qiang; Liu, Zhichao; Fang, Hong; Tong, Weida

doi:10.1016/j.drudis.2011.05.007

Cited by 345 publications

(334 citation statements)

References 33 publications

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Section: Drugs and Dili Classificationmentioning

confidence: 99%

“…Two classification methods for DILI risk in humans with a concordance of approximately 90 % have been reported (Chen et al 2011). In one approach, drugs were classified by most-, less-, and no-DILI concern according to the DILI concern disclosed in the FDAapproved drug labels (Chen et al 2011). In another independent approach, drugs were categorized into four hepatotoxic groups (Greene et al 2010): NE (no evidence for hepatotoxicity in any species), WE (weak evidence for human hepatotoxicity with <10 case reports, but generally considered not to present a risk for liver injury in humans), HH (evidence for hepatotoxicity in humans), and AH (animal hepatotoxicity observed, not tested in humans).…”

Section: Drugs and Dili Classificationmentioning

confidence: 99%

“…Cell loss Fraction cell loss relative to negative control wells High-content screening of 38 drugs was studied at a maximum concentration of 200 μM using a total of 9 selected cellular parameters The classification of human DILI was determined by the Chen et al and Greene et al approaches (Greene et al 2010;Chen et al 2011). Specifically, a drug is defined as human hepatotoxicity positive if it is classified as most-DILI-concern or HH, or as negative if it is classified as no-DILI-concern or NE.…”

Section: Endpoint Descriptionmentioning

confidence: 99%

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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

et al. 2014

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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 Correspondence to: Weida Tong. Jürgen Borlak and Weida Tong have contributed equally to the manuscript.Disclaimer: The views presented in this article do not necessarily reflect current or future opinion or policy of the US Food and Drug Administration. Any mention of commercial products is for clarification and not intended as endorsement. Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-014-1276-9) contains supplementary material, which is available to authorized users. HHS Public AccessAuthor manuscript Arch Toxicol. Author manuscript; available in PMC 2018 January 04.Published in final edited form as:Arch Toxicol. 2014 July ; 88(7): 1439-1449. doi:10.1007/s00204-014-1276-9. Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript reduce the potential failures in the subsequent drug development program. In this regard, highcontent 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.

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Section: Drugs and Dili Classificationmentioning

confidence: 99%

Section: Drugs and Dili Classificationmentioning

confidence: 99%

Section: Endpoint Descriptionmentioning

confidence: 99%

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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

et al. 2014

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“…76 Because DILI is a serious problem in health care, there is an urgent need to have biomarkers that can provide information for early detection, sufficient sensitivity of the injury, types of DILI, and prognosis of the injuries. 77 Markers that can serve as predictors of response to treatment in patients with DILI are also in need. 49 The advancement of various high throughput global molecular profiling technologies for proteins and nucleic acids has the potential to lead to more informative biomarkers.…”

Section: Approaches For New Biomarker Discoverymentioning

confidence: 99%

Biomarkers for drug-induced liver injury

Shi

Hong

Senior

et al. 2010

Expert Review of Gastroenterology & Hepatology

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Abstract:The liver plays a central role in metabolizing xenobiotics; therefore, it is highly susceptible to toxicity from these chemicals. Certain drugs, when taken in overdose and sometimes even when used within therapeutic range, may cause injury to the organ. Druginduced liver injury is now not only a leading cause of acute liver failure in the US, but is also a leading reason for discontinuation of drugs in development and for regulatory actions against previously approved drugs. The current clinical biomarkers to detect and monitor drug-induced liver injury are inadequate in terms of sensitivity and/or specificity, prompting the need for more informative biomarkers. The development of high throughput proteomics, genomics, and metabolomics technologies has the potential to fulfill such demand. The discipline of systems toxicology may add to our understanding of perturbed xenobiotic networks, which may lead to network-specific surrogate markers and therapeutic means to stop or reverse xenobiotic-induced liver injury.

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“…The consequences in affected patients may be marked symptomatic liver damage, or even acute liver failure, and currently it is not possible to predict and identify "at risk" patients prior to their exposure to the relevant drugs [1,2]. Because of this, unexpected "idiosyncratic" human DILI continues to be a leading cause of failed development of new drugs, of withdrawal from use of previously licensed drugs and of cautionary labeling that restricts prescribing [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Noninvasive Preclinical and Clinical Imaging of Liver Transporter Function Relevant to Drug-Induced Liver Injury

Kenna

Waterton

Baudy

et al. 2018

Methods in Pharmacology and Toxicology

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Imaging technologies can evaluate many different biological processes in vitro (in cell culture models) and in vivo (in animals and humans), and many are used routinely in investigation of human liver diseases. Some of these methods can help understand liver toxicity caused by drugs in vivo in animals, and druginduced liver injury (DILI) which arises in susceptible humans. Imaging could aid assessment of the relevance to humans in vivo of toxicity caused by drugs in animals (animal/human translation), plus toxicities observed using in vitro model systems (in vitro/in vivo translation). Technologies and probe substrates for quantitative evaluation of hepatobiliary transporter activities are of particular importance. This is due to the key role played by sinusoidal transporter mediated hepatic uptake in DILI caused by many drugs, plus the strong evidence that inhibition of the hepatic bile salt export pump (BSEP) can initiate DILI. Imaging methods for investigation of these processes are reviewed in this chapter, together with their scientific rationale, and methods of quantitative data analysis. In addition to providing biomarkers for investigation of DILI, such approaches could aid the evaluation of clinically relevant drug-drug interactions mediated via hepatobiliary transporter perturbation.

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FDA-approved drug labeling for the study of drug-induced liver injury

Cited by 345 publications

References 33 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

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

Biomarkers for drug-induced liver injury

Noninvasive Preclinical and Clinical Imaging of Liver Transporter Function Relevant to Drug-Induced Liver Injury

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