As a clinical pharmacological modeller I am interested in parameterising the relationship between drug levels and the drug effect. These so called pharmacokinetic-pharmacodynamic models can be used to optimise dosing regimens and the design of prospective clinical trials using computer simulations.

Here at the University College London Institute for Global Health my main research focus is around three themes.

• First, I study in-vivo pharmacokinetic-pharmacodynamic properties of anti-tuberculosis drugs and explore candidate biomarkers for cure. To that end I have been designing and running population pharmacokinetic-pharmacodynamic studies and observational cohorts in the UK and abroad.
• Moreover, I investigate biomarkers for bacterial sub-populations that are able to survive treatment. To that purpose I have setup in-vivo mimicking in-vitro experiments (hollow fibre experiment of infection) at UCL.
• Lastly, I am one of the co-founders of PKPDai, an initiative that brings together quantitative pharmacometric knowledge into a single open-source platform, thereby making it amenable to the application of machine learning. We have been leveraging natural language processing as due to the size of publicly available data manual curation is not a viable option.