Knowledge-based Mathematical Systems
Overview: Drug development has been performed by integrating clinical observations and information from medical tests. However, this “trial and error” approach is becoming more challenging and unfeasible by the steep increase in the amount of different pieces of information and the complexity of large datasets. A systematic and tractable approach that integrates a variety of biological and medical research data into mathematical models and computational algorithms is crucial to harness knowledge to understand why some patients respond differently compare to others.
State of the art: At present, several pharmaceutical companies aim to integrate experimental and clinical knowledge on the drug candidate into mathematical modeling to facilitate quantitative decision making in order to influence the discovery and development of drugs.
Our research in Quantitative Pharmacology aims to: