My research involves understanding drug safety in vulnerable populations using big healthcare datasets. I am particularly interested to understand how mathematics can advance the prediction of the safety of drugs at a population level. I have employed various mathematical models to characterise the safety profile of drugs that have not been fully explored and understood in clinical trials. Accurately predicting adverse effects is critical to my research. Recently, I have developed a keen interest in Machine Learning approaches that can help predict adverse effects of drugs that are most likely to happen based on adverse effects collected from adverse event reporting systems and large primary and secondary healthcare datasets. In addition, as part of a development award from NIHR, I am now investigating how artificial intelligence can help identify new disease clusters in patients with immune-mediated inflammatory conditions.
As part of my fellowship with the IMI, I am keen to leverage the institute’s mathematical innovation by developing strategic collaborations with the IMI to lead future funding applications or other collaborative opportunities. In addition, working alongside the IMI, I am interested in forging stronger ties between industry and academia.