Use of Quantitative Systems Toxicology (QST) to Identify Potential Intrinsic Mechanisms of Toxicity

Authors: Battista C, Shoda LKM, Watkins PB, Groettrup-Wolfers E, Rottmann A, Raschke M, Generaux GT
Conference: AAPS
Keywords: AAPS 2022, ALT elevations, hepatotoxicity, machine learning PBPK QST(P) marriage, PBPK modeling, QST modeling
Software: DILIsym®
Division: DILIsym Services

Purpose

BAY1128688, a selective inhibitor of aldo-keto reductase family 1 member C3 (AKR1C3), was in clinical trials as a potential therapy to provide pain relief for women with endometriosis. Although no liver toxicity was observed in rats and cynomolgus monkeys after 13 weeks of treatment and in humans after 4 weeks of treatment, clinical development was prematurely terminated due to posttreatment hepatotoxicity following administration of 30mg QD or 60mg BID for 12 weeks. This finding prompted use of DILIsym®, a QST model, to determine possible mechanisms contributing to the observed drug-induced liver injury (DILI)2,3. Although bilirubin elevations >2x upper limit of normal (ULN) and alanine aminotransferase (ALT) elevations >2xULN were observed in some individuals while on treatment, severe ALT elevations >3xULN were mostly observed at the end-of-treatment visit (12 weeks after
starting treatment) or after treatment cessation. The timing for hepatotoxicity presents an opportunity to explore mechanisms that may increase risk for delayed hepatotoxicity in susceptible individuals using DILIsym.

By Christina Battista, Lisl KM Shoda, Paul B Watkins, Esther Groettrup-Wolfers, Antje Rottmann, Marian
Raschke, Grant T Generaux

Presented at American Association of Pharmaceutical Scientists (AAPS) Pharm Sci 360 Boston, Massachusetts October 16-19, 2022