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I started my career in 2013 as a biochemist at Swansea University, with a photochemistry dissertation in the application of Förster resonance energy transfer between DNA dyes. I then undertook the Applied Biopharmaceutical Biotechnology with Entrepreneurship MSc at the University of Nottingham, which included an industrial research project at Marstons PLC in Burton-on-Trent that aimed to improve the microbiological performance of their bright beer tanks. Following this, I worked for a short while as a food microbiology laboratory technician at Intertek, which involved processing and testing food samples for pathogens. I began the Transformative Pharmaceutical Technologies PhD in 2019, which included an industrial project at Pfizer in Sandwich that worked to incorporate their ADDoPT machine learning model to predict compounds' powder flow from their physical characteristics. My thesis, in collaboration with Croda, aimed to optimise the structure of excipients with respect to their ability to improve biotherapeutic protein formulations by preventing aggregation. This was done by undertaking molecular dynamics simulations of excipients' interaction with model proteins, the application of a quantitative structure-activity relationship (QSAR) machine learning model to formulate design hypotheses for novel excipients, followed by the synthesis and characterisation of those excipients.

I started in the Cheminformatics group in April 2024, using neural networks in a drug discovery context, both in the de novo structure generation of compounds, as well as in QSAR modelling.