Applications of AI in anti-ageing drugs

人口老龄化是英国经济面临的最重要的健康和经济问题之一，非常需要制定减轻这一社会经济负担的战略。在这种情况下，抗衰老是健康地生活直到死亡，而不是永远活着。我们已经编写了一个人工智能（AI）协议，该协议从DrugAge数据库（DrugAge：与药物相关的药物数据库（senescence.info））中增加寿命的化合物中学习，然后可以使用这些知识来搜索其他数据库中也可能增加寿命的化合物。DrugAge数据库是基于对线虫秀丽隐杆线虫的代谢研究，秀丽隐杆线虫与人类共享80%的代谢，但寿命很短。直接研究这些对人类的影响显然是不道德的，而且非常耗时。我们打算开发这项技术来生产新的药物，为人类的健康老龄化做出贡献。Marco将结合使用行业标准软件莫伊的分子建模和Python中的AI编程来开发这一领域。我们与FHMS的Richard Wu教授积极合作，他可以在细胞和动物模型中测试化合物的功效，一家初创公司正在研究这一领域的豆瓣菜提取物，以及与UCL的进化生物学家团队合作，因此Marco将有机会在学术和工业上发展他对这些领域的知识。

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.