Predictive science for drug delivery
Senior Scientist, Pharmaceutical Sciences at AstraZeneca.
I build predictive models for lipid nanoparticles and biologics, so fewer animal studies are needed to develop them. I am based in Cambridge, UK.
PRELIVE, running in your browser
Move the sliders for cholesterol, PEG, DSPC and particle size, and watch predicted mRNA delivery change across liver, spleen, kidney, bone marrow, lung, heart, brain and whole blood.
This is the model published alongside the paper, reproduced here under CC BY 4.0.
Research
What I work on
Formulation optimisation for drug delivery, worked from four angles.
Reducing reliance on animal testing
A good enough prediction is a study that does not need running.
Lipid nanoparticle organ and cell tropism
Which cell a nanoparticle reaches is decided by its chemistry.
Predictive biopharmaceutics
Predicting how much of a subcutaneous dose reaches the bloodstream, before dosing humans.
Cheminformatics, high-throughput screening and machine learning for formulation
Cheminformatics, QSAR and high-throughput screening decide which lipid is worth making.
Selected work
Publications
Advancing Cellular-Specific Delivery: Machine Learning Insights into Lipid Nanoparticles Design and Cellular Tropism
Advanced Healthcare Materials
PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing
Advanced Functional Materials
Predicting human subcutaneous bioavailability of monoclonal antibodies using an integrated in-vitro/in-silico approach
Journal of Controlled Release