Drug-Drug Combinations Can Enhance Toxicity as Shown by Monocyte-Derived Hepatocyte-like Cells From Patients With Idiosyncratic Drug-Induced Liver Injury

Benesic, Andreas; Jalal, Kowcee und Gerbes, Alexander L. (2019): Drug-Drug Combinations Can Enhance Toxicity as Shown by Monocyte-Derived Hepatocyte-like Cells From Patients With Idiosyncratic Drug-Induced Liver Injury. In: Toxicological Sciences, Bd. 171, Nr. 2: S. 296-302

Abstract

Drug-induced liver injury (DILI) is a major cause for acute liver failure and regulatory actions on novel drugs. Individual patient characteristics are the main determinant of idiosyncratic DILI, making idiosyncratic DILI (iDILI) one of the most challenging diagnoses in hepatology. Individual drug-drug interactions might play a role in iDILI. However, the current approaches to iDILI diagnosis are focused on single drugs as causative agents. For the present analysis, 48 patients with acute liver injury who took 2 drugs and who were diagnosed as iDILI were investigated. A novel in vitro test was employed using monocyte-derived hepatocyte-like cells (MH cells) generated from these patients. iDILI diagnosis and causality were evaluated using clinical causality assessment supported by Roussel-Uclaf Causality Assessment Method. In 13 of these 48 patients (27%), combinations of drugs increased toxicity in the MH test when compared with the single drugs. Interestingly, whereas in 24 cases (50%) drug-drug combinations did not enhance toxicity, in 11 cases (23%) only the combinations caused toxicity. The incidence of severe cases fulfilling Hy's law was higher in patients with positive interactions (57% vs 43%;p = .04), with acute liver failure occurring in 40% versus 8% (p = .01). The most common drug combinations causing increased toxicity were amoxicillin/clavulanate (8 of 9 cases) and diclofenac in combination with steroid hormones (4 of 9 cases). Drug-drug interactions may influence the incidence and/or the severity of idiosyncratic DILI. MH cell testing can identify relevant drug-drug interactions. The data generated by this approach may improve patient safety.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 1096-6080
• Sprache: Englisch