Journal of In Silico & In Vitro Pharmacology

Jun Li
Faculty of Pharmacy, University of Montreal, QC H3T 1J4, Canada.

Biography

Jun Li is trained as a mathematician. He has a strong background in mathematics, namely in nonlinear analysis and stochastic processes, complemented with excellent skills in computer programming and simulation. After his Ph. D in mathematics, he was attracted in applying his knowledge in the modeling & simulation methodology in pharmaceutical science. With many years’ efforts, he has become an established expert in the field with even an industrial experience by working on data management, analysis and modeling. This poly background formed his great adaptability and creativity in the newly coined multidisciplinary research of pharmacometrics. He has worked on a number of multidisciplinary projects with very fruitful research results, as evidenced by the number of publications and scientific events. He is now actively involved in training students at different levels from undergraduate, to graduate and postdoc, ranging across various disciplines and departments (Polytechnique, maths and pharmaceutical sciences).

Research Interest

My research in Pharmacometrics, a new discipline of quantitative pharmacology, mainly involves the modeling, metric and problem solving methodology. It is rooted in the nonlinearity and variability in a complex biological system. While the formal is issued from the adaptability of a bio-system to the host environment, the latter guarantees the diversity for surviving of selection. In general speaking, this interest comprises the model construction, model characterization, and model centered problem solving. The first involves the mechanistic modeling of pharmaceutical and physiological process while the variability is centered; The second is the rationality and estimation of some important pharmacological parameters, stability and robustness of proposed methods, etc. The third is the mathematical analysis of the model with the goal to give a quantitative solution to a pharmacological problem and a web or mobile solution as beyond.