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.
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.
December 6, 2024
Presented at ACoP 2024. The poster introduces a framework for developing physiologically based pharmacokinetic (PBPK) models that incorporate partial differential equations (PDEs) to account for spatial drug distribution, using open-source Julia tools. This approach simplifies the integration of spatial components into PBPK models, demonstrated through a case study on naphthalene diffusion, and is applicable to various pharmacometric models requiring spatial considerations, such as topical, inhaled, and antitumor therapies.