Dr. Edginton’s research focuses on improving the confidence of physiologically-based pharmacokinetic (PBPK) model outcomes through understanding model inputs and developing modeling workflows.
Dr. Abdullah Hamadeh is a Research Associate at the School of Pharmacy, University of Waterloo. He holds a Ph.D. in control systems engineering from the University of Cambridge and has conducted postdoctoral research in systems and synthetic biology at MIT.
Dr. Hamadeh specializes in developing optimization algorithms for complex systems, with a primary focus on applications in pharmacokinetic modeling, systems pharmacology, and epidemiology. His current research initiatives involve the development of learning algorithms that fuse experimental data and pharmacokinetic models to derive mechanistic insights that inform topical drug development and chemical risk assessment. Dr. Hamadeh is also a software developer and contributor to the Open Systems Pharmacology modeling platform.
Sam is a PhD candidate being co-supervised by Dr. Edginton and Dr. Wong. She is currently studying the pharmacoeconomics of hemophilia A gene therapy, focusing on generating high-quality data from real-world sources to allow for more accurate cost-effectiveness analysis modelling to mitigate algorithmic bias. She has won numerous awards during her time in the Edginton/Wong labs, including the SMDM Lee B Lusted Milt Weinstein Award 2024, Donald J. & Kathleen McDougall Graduate Scholarship 2024, Christine & David Edwards Studies Travel Grant (2022, 2023, 2024), and the Provost Doctoral Entrance Award (PDEA) for Women 2023 when she transitioned from the MSc program to the direct to PhD program.
She obtained a BMath in Honours Mathematical Studies with minors in Applied Mathematics and Biology from the University of Waterloo. She has previously worked with Dr. Ingalls from Waterloo Applied Mathematics on an algorithm to link signalling network analysis with metabolic pathway analysis.
D.
Dr. Chelle has a background in Health Engineering and has been working at the University of Waterloo, School of Pharmacy, since 2017.
His work at UW focuses on Population PK modeling with research interests including data analysis, Bayesian forecasting and development of R code based tools.
He is also involved the several projects including WAPPS-Hemo (www.wapps-hemo.org) which aims at empowering hemophilia treatment by facilitating individualized dosing; the development of an R toolbox for the Open System Pharmacology Suite and the development of a dosing tool for the treatment of neonates having patent ductus arteriosus.
Katherine obtained her Bachelor's of Medical Sciences, with an honours' specialization in Biochemistry and major in Pharmacology, from Western University in 2025.
Ruby is the Research Administrative Assistant for Dr. Andrea Edginton.
Dagmar obtained her PhD degree in Statistics from the Statistics and Actuarial Science Department at UW after developing methodology for the analysis of longitudinal survey data. She has provided statistical consultation on a variety of PK/PD projects and delivered courses on advanced statistics for the application of pharmacokinetic NLME models. Dagmar's current role is population PK modeling in the WAPPS-Hemo project.
Shirley holds a Bachelor of Science in Biochemistry and a Master of Science in Pharmacy, earned at the University of Waterloo. Her Master's thesis was on Alzheimer's disease drug discovery, earning the 2023-2024 Dean of Science award and the Memorial poster award at the 2023 Canadian Society for Pharmaceutical Sciences conference. Additionally, she has expertise in developing bioanalytical methods with over 5 years of industry experience quantifying drugs in biological matrices for pre-clinical studies. Now, in her Ph.D. pursuit, Shirley's passion for pharmacometrics drives her work on physiologically-based pharmacokinetic models, with a focus on advancing neonatal drug exposure assessment during maternal therapy and lactation. This work aims to provide a vital means of assessing infant risk when considering the continuation of medical treatments during pregnancy and breastfeeding.
Yicui is a PhD student specializing in Physiologically Based Pharmacokinetic (PBPK) modeling, using PK-Sim, MoBi, R, and Python. During her Master’s, Yicui developed pediatric PBPK models for heart failure drugs (e.g., digoxin, milrinone, levosimendan), incorporating age-specific physiology and pathophysiological characteristics of pediatric patients using -Sim. Yicui additionally built a CYP3A4-based drug-drug interaction (DDI) model and performed interspecies scaling to predict first-in-human doses for new drug candidates before clinical development, in collaboration with industry.