As a pharmacometrician, I have an arsenal of tools that can help you with your research needs. Currently, I am applying these tools in oncology and tuberculosis research as part of the Research Data Integration group at A*STAR.
Characterizing drug exposure across different model systems allows us to better understand the exposure response within each system and translate it across different species. This is especially important in cancer, where there is an urgent need for new chemotherapeutics and optimal dosing, but no systematic methods to translate findings from in vitro to animal to clinical.
Despite making up more than 60% of the world’s population, Asian genomes are under characterized. The understanding of how our genetic makeup affects how our body handles drugs is thus scant. Using model informed dose optimization strategies, we aim to prioritize clinically important drug-gene sets for pharmacogenomic testing and their new optimized doses when 1 or more pharmacogenomic variants are present.