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Closed-loop Interpretable AI for Biological Systems

The value of engineering approaches to biology is amply demonstrated: understanding virus interactions and engineering vaccines; engineering CAR-T cells equipped with sensing and logic devices to precisely tune their immunotherapeutic response; sustainable bio-based production of chemicals to minimise environmental impact. 

To tackle the complexity of biological systems design and achieve even more ambitious results, more reliably and in less time, we need an innovative new approach, so that bio-based manufacturing and engineered cell therapies are the norm instead of the exception. 

Using interpretable Artificial Intelligence (AI) to direct the design and implementation of new biological systems is a radical approach that will transform our ability to predictably engineer biological systems. Recently, this research initiative received an award of £1.5 m of funding as part of the AI-4-EB consortium, which aims to further research in the intersection of Artificial Intelligence and Engineering Biology.

Led by Professor Geoff Baldwin and Professor Guy-Bart Stan.

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