Applications of AI in anti-ageing drugs

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The ageing population is one of the most significant health and economic issues facing the UK economy and there is great need to produce strategies for alleviating this socioeconomic burden. Anti-ageing in this case is living a healthy life until death, not living for ever. We have written an Artificial Intelligence (AI) protocol that learns from the compounds that increase lifespan in the DrugAge database (DrugAge: Database of Ageing-Related Drugs (senescence.info)) and can then use that knowledge to search other databases for compounds that may also increase lifespan. The DrugAge database is based on metabolic studies of the worm Caenorhabditis Elegans, which shares 80% of its metabolism with Humans but only lives a short time. It is obviously unethical and very time consuming to study these effects on humans directly. We intend to develop this technology to produce new pharmaceuticals to contribute to healthy ageing in Humans. Marco will use a combination of molecular modelling using the industry standard software MOE and AI programming in Python to develop this area. We have active collaborations with Prof Richard Wu in FHMS who can test compounds for efficacy in cell and animal models and a start-up company looking at Watercress extract in this area as well as with a team of evolutionary biologists at UCL, so there will be opportunities for Marco to develop his knowledge of these areas both academically and in industry.