AI-Driven Precision Medicine in Kidney Transplantation
Haojie Zhu, Professor of Pharmacy at the University of Michigan, College of Pharmacy
Haojie Zhu is a Professor in the Department of Clinical Pharmacy, University of Michigan College of Pharmacy. He graduated from China Pharmaceutical University with a major in Pharmacy and subsequently received his M.S. and Ph.D. in Pharmacology from the same University. He also holds an MBA degree from Nanjing University. He was a licensed Pharmacist as well as a trained Dentist in China. Dr. Zhu completed his postdoctoral training in pharmacogenomics and pharmacokinetics at the Medical University of South Carolina. His research focuses on identifying genetic variants and environmental regulators that impact the pharmacokinetics and pharmacodynamics of various therapeutic agents using an integrated multiomics approach (e.g., genomics, proteomics, and metabolomics) and machine learning. The generated information can be used to guide the personalized use of medications, maximizing efficacy while minimizing the risk of adverse effects.
This presentation focuses on AI-driven precision medicine in kidney transplantation, with two main projects. The first project explores the use of machine learning to predict tacrolimus trough concentrations in kidney transplant recipients, addressing the challenges of optimizing tacrolimus dosing during the early post-transplantation period. The second project focuses on predicting allograft rejection in kidney transplant recipients by utilizing LC-MS/MS-based metabolomics and machine learning. The studies suggest that machine learning models, such as XGBoost and LSTM, can improve the attainment of target tacrolimus trough concentrations, and that combining metabolomics and machine learning is a promising approach for predicting rejection risk in kidney transplant recipients.