March 2019: New Member Profile

Published on 3/1/2019 12:00:00 AM

Weize Huang, PharmD, University of Washington, Seattle, Washington

In May of 2013, Dr. Huang received his Bachelor Degree of Science in Biochemistry with Highest Distinction and Honors from Purdue University. In that program, his research focused on experimental cancer biology. From there he went to the University of Washington, School of Pharmacy to pursue his PharmD and become a clinical pharmacist. Coming from a mixed background of basic science research and therapeutic utilization in clinical settings, Dr. Huang thinks that the field of clinical pharmacology and translational medicine is “an amazing bridge that connects both.” After earning his PharmD and completing a summer internship at Boehringer Ingelheim under the supervision of Drs. Jin Zhou and Sebastian Haertter, Dr. Huang joined the University of Washington PhD pharmaceutics program under the mentorship of Dr. Nina Isoherranen. He is deeply fascinated by the field because it not only facilitates the clinical applicability of scientific findings but also provides a constructive framework to evaluate the experimental hypotheses and guide future work.

Dr. Huang's PhD projects have a focus on pharmacometric modeling and simulation, which utilizes mathematics and computer science to illustrate, quantify, and predict the interactions among therapeutic drugs, human physiology, and disease progression. His projects aim to establish a dynamic physiologically based mechanistic kidney model to predict drug renal clearance and drug disposition inside the kidney. He hopes to understand the rate‐determining steps of the drug renal elimination process and renal intracellular accumulation. His goal is to explore the potential drug‐disease interaction between predominantly renally eliminated drugs/nephrotoxic drugs and kidney disease progression.

According to Dr. Huang, the implementation of patient care is currently transitioning from empirical practice to evidence‐based practice, from qualitative projection to quantitative prediction and from populational perspective to personal perspective. With millions of patients afflicted with kidney diseases, Dr. Huang and his colleagues hope to develop an evidence‐based model that enables quantitative prediction of optimal therapeutic dose and frequency to maximize the systemic clinical outcome and minimize the renal toxicity for the characteristic patient population.

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