Senior Scientist I
Yuezhe earned her Ph.D. in Biomedical Sciences from the University of Connecticut. Her thesis work aimed to understand molecular mechanisms that link diabetes with ciliopathy, a group of rare diseases. Other fields of experience include systems biology, machine learning, and mathematical modeling. More recently, she focused on developing physiologically based pharmacokinetic (PBPK) models to get a better mechanistic understanding of drugs’ pharmacokinetics.
October 19, 2026
Yuezhe Li, Jimena Davis, Timothy Knab, Cole Zmurchok, and Daniel C. Kirouac
Submitted to the 2026 American Conference on Pharmacometrics (ACoP 2026), an International Conference on Pharmacometrics in the US (ICoP – US).
Antibody-drug conjugates (ADCs) are a rapidly evolving class of oncology therapeutics designed to expand the therapeutic index of potent cytotoxic payloads by leveraging the specificity of monoclonal antibodies. Despite clinical successes, many ADC candidates fail in late-stage development due to dose-limiting toxicities or insufficient efficacy. To support preclinical evaluation and de-risk ADC development, a modular, customizable PBPK-QSP platform using the open-source Julia package ModelingToolkit.jl was developed. This platform integrates a whole-body PBPK submodel to characterize ADC and payload biodistribution with a QSP submodel designed to predict both potential off-target toxicities and anti-tumor efficacy.
June 13, 2025
Presented at ASCPT Annual Meeting 2025. The virtual population-based lymphoma QSP model enabled systematic exploration of alternate drug combinations, dosing schemes, clinical covariates and resultant effect on anti-tumor activity in silico. The results of the LOTIS-7 study (NCT04970901), a platform study evaluating loncastuximab tesirine in combination with glofitamab, will soon be available to assess the accuracy of the model predictions.
May 19, 2025
Co-developed with CSL Behring, this research introduces a high-resolution model that simulates hepatocyte turnover, episomal retention and coagulation factor IX (FIX) expression in virtual patients treated with Etranacogene Dezaparvovec ( HEMGENIX). The model captured clinical variability before recent clinical readouts were available, and projects FIX expression durability over two decades.