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Arch Toxicol. 2019 Jun;93(6):1609-1637. doi: 10.1007/s00204-019-02492-9. Epub 2019 Jun 27.

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations.

Author information

1
Leibniz Research Centre for Working Environment and Human Factors at the Technical University of Dortmund (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany. albrecht@ifado.de.
2
Department of Statistics, TU Dortmund University, 44227, Dortmund, Germany.
3
Leibniz Research Centre for Working Environment and Human Factors at the Technical University of Dortmund (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany.
4
Simcyp (A Certara Company), Sheffield, UK.
5
Department of R&D Global Biostatistics, Epidemiology and Medical Writing, Merck KGaA, Darmstadt, Germany.
6
In Vitro Toxicology and Biomedicine, Department of Biology, University of Konstanz, Universitätsstr. 10, PO Box M657, 78457, Constance, Germany.
7
InSphero AG, Wagistrasse 27, 8952, Schlieren, Switzerland.
8
Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt.
9
Experimental Hepatology Unit, Instituto de Investigación Sanitaria La Fe, Valencia, Spain.
10
Department of General-, Visceral- and Transplantation Surgery, Charité University Medicine Berlin, 13353, Berlin, Germany.
11
Department of Hepatobiliary Surgery and Visceral Transplantation, University of Leipzig, Leipzig, Germany.
12
Department Food Safety, German Federal Institute for Risk Assessment, Max-Dohrn-Str. 8-10, 10589, Berlin, Germany.
13
College of Veterinary Medicine, Yunnan Agricultural University, Kunming, 650201, Yunnan, People's Republic of China.
14
Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, An-Najah National University, PO Box 7, Nablus, Palestine.
15
Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Einsteinweg 55, PO Box 9502, 2300 RA, Leiden, The Netherlands.
16
Clariant Produkte (Deutschland) GmbH, Am Unisyspark 1, 65843, Sulzbach, Germany.
17
Medicines Evaluation Board: Pharmacology, Toxicology, Pharmacokinetics, Utrecht, The Netherlands.
18
Department of Medical Biology, Vascular Biology Research Group, University of Tromsø, NO-9037, Tromsø, Norway.
19
Investigational Toxicology, Drug Discovery, Pharmaceuticals, Bayer AG, 42096, Wuppertal, Germany.
20
Institute for Clinical Pharmacology and Toxicology, Charité, Universitätsmedizin Berlin, Berlin, Germany.
21
Institute for Diabetes and Cancer, Helmholtz Center Munich, 85764 Neuherberg, Germany and Joint Heidelberg-IDC Translational Diabetes Program, Inner Medicine 1, Heidelberg University Hospital, Heidelberg, Germany.
22
German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany.
23
Primacyt Cell Culture Technology GmbH, Schwerin, Germany.
24
Biobank Under the Administration of the Human Tissue and Cell Research Foundation, Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany.
25
Systems Pharmacology, Bayer AG, Leverkusen, Germany.
26
Translational Disease Systems Biology, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
27
Institute of Neurophysiology and Center for Molecular Medicine Cologne (CMMC), University of Cologne (UKK), Robert-Koch-Str. 39, 50931, Cologne, Germany.
28
Leibniz Research Centre for Working Environment and Human Factors at the Technical University of Dortmund (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany. hengstler@ifado.de.

Abstract

Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity.

KEYWORDS:

3D culture; Alternative methods; Cryopreserved; Cultivated hepatocytes; Hepatotoxicity; Performance metrics

PMID:
31250071
DOI:
10.1007/s00204-019-02492-9

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