PhD Studentship: EPSRC Supported EngD A Digital Twin of The Human Stomach Combining Multiphysics and Artificial Intelligence

This project aims to develop a digital twin of the human stomach that integrates first-principles mathematical modelling with machine learning. The model will simulate the complex mechanics, chemistry, and neural feedback of the stomach, including motility, secretion, and emptying, dynamically adapting to the physicochemical properties of food.

Validated against in-vivo data such as MRI scans, the digital twin will replicate the gastric environment’s response to different pharmaceutical dosage forms. This will enable detailed predictions of disintegration and dissolution profiles, informing Physiologically Based Pharmacokinetic (PBPK) platforms. The insights will help optimise drug formulations, predict in-vivo performance, and reduce the need for physical trials.

In collaboration with GSK, this novel approach supports faster, cost-effective drug development with lower environmental impact. Beyond pharmaceuticals, the project offers significant potential to explore personalised medicine and patient-centric drug formulations, making it a unique opportunity for innovation at the intersection of computational modelling, AI, and healthcare.

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