Related Experiment Video
Updated: Jun 20, 2026

Modeling Chemotherapy Resistant Leukemia In Vitro
Published on: February 9, 2016
Quantitative Systems Toxicology Modeling Informed Safe Dose Selection of Emvododstat in Acute Myeloid Leukemia
Kyunghee Yang1, Ronald Kong2, Robert Spiegel2
1Quantitative Systems Pharmacology Solutions, Simulations Plus Inc., Research Triangle Park, North Carolina, USA.
Abstract:
Clinical investigation of emvododstat for the treatment of solid tumors was halted after two patients who were heavily treated with other anticancer therapies experienced drug-induced liver failure. However, preclinical investigations supported that emvododstat at lower doses might be effective in treating acute myeloid leukemia (AML) and against severe acute respiratory syndrome-coronavirus 2 as a dihydroorotate dehydrogenase inhibitor. Therefore, a quantitative systems toxicology model, DILIsym, was used to predict liver safety of the proposed dosing of emvododstat in AML clinical trials. In vitro mechanistic toxicity data of emvododstat and its desmethyl metabolite were integrated with in vivo exposure within DILIsym to predict hepatotoxicity responses in a simulated human population. DILIsym simulations predicted alanine aminotransferase elevations observed in prior emvododstat clinical trials in patients with solid tumors, but not in the prospective AML clinical trial with the proposed dosing regimens. Exposure predictions based on physiologically-based pharmacokinetic modeling suggested that reduced doses of emvododstat would produce clinical exposures that would be efficacious to treat AML. In the AML clinical trial, only eight patients experienced aminotransferase elevations, all of which were mild (grade 1), all resolving within a short period of time, and no patient showed symptoms of hepatotoxicity, confirming the prospective prediction of liver safety. Overall, retrospective DILIsym simulations adequately predicted the liver safety liabilities of emvododstat in solid tumor trials and prospective simulations predicted the liver safety of reduced doses in an AML clinical trial. The modeling was critical to enabling regulatory approval to proceed with the AML clinical trial wherein the predicted liver safety was confirmed.
More Related Videos
00:05In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
06:08Assessment of Chimeric Antigen Receptor T Cell-Associated Toxicities Using an Acute Lymphoblastic Leukemia Patient-Derived Xenograft Mouse Model
Published on: February 10, 2023
Related Concept Videos
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses
Drug Dosing in Renal Diseases: Dose Adjustments Based on Drug Clearance and Elimination Rate Constant
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
Drug Toxicity: Overview
Drug Toxicity: Risk factors
Drug Toxicity: Dose-Dependent Reactions