AI for drug discovery is a rapidly expanding application of AI and data science techniques. UK pharmaceutical companies have a key role to play, but the current drug discovery process is widely regarded as slow and inefficient. On average, it costs approximately $1.3 billion and ten years to bring a new therapeutic drug to market, and this cost is expected to increase. AI can play a role to reduce drug discovery costs and timelines by leveraging large scientific databases, evaluating potential drug candidates in silico, and accelerating high content screening assays through automated data analysis.
Research ongoing at DERI within this space takes a broad approach to drug discovery, with work spanning the translational research to genetic and genomic methods for target identification, as well as the development of machine learning, AI and data integration methods for application to complex biomedical datasets. Research takes a truly interdisciplinary approach, harnessing computational biology to impact on increasing challenges.
Find out more about our researchers working in this space on our Team pages, and through our Doctoral Training Programme in Drug Discovery.