News

Queen Mary partner with industry to train next generation of ‘AI-native’ biological scientists

Queen Mary University of London are partnering with Exscientia, MSD and Heptares Therapeutics to deliver a new doctoral training programme that will train researchers to apply cutting-edge AI expertise to the discovery and development of new drugs.

Published on:
Queen Mary student in a laboratory
Queen Mary student in a laboratory

The programme, which is part of the Biotechnology and Biological Sciences Research Council (BBSRC) Collaborative Training Partnerships (CTPs) scheme, will offer 21 students the opportunity to conduct ground-breaking Artificial Intelligence (AI) research at the interface of industry and academia.  

Queen Mary’s new Digital Environment Research Institute (DERI) will act as the hub for the programme and students will benefit from Queen Mary’s world-leading research environment, which includes state-of-the-art high performance computing and transferrable training resources.

Students will be supervised by researchers from Queen Mary’s Faculty of Science and Engineering and Faculty of Medicine and Dentistry, and co-supervised by industrial partners. This will allow students to build research expertise in AI and its relevance to drug discovery whilst developing transferrable skills through industrial placements.

Developing AI talent

It is known that AI can accelerate key steps in the drug discovery process, but its potential to revolutionize the pharmaceutical industry depends on the ability to recruit talented interdisciplinary postdoctoral researchers who possess both deep computational skills and a solid understanding of key biological concepts. It is hoped that graduates from the programme will help to bridge the existing skills gap and support this rapidly growing sector of the UK bioeconomy.

The announcement of the new CTP follows the publication of the Government’s first national AI strategy and will support plans to develop the next generation of AI talent.  

Professor Conrad Bessant, Academic Principal Investigator for the new programme and Professor of Bioinformatics at Queen Mary, said: “Researchers with a strong grounding in molecular bioscience allied to proven experience in data science and AI are in particularly high demand. Our new PhD Programme is specifically designed to produce such researchers, by offering research projects exclusively at this biology-data science interface and providing the experiences and training needed to succeed in this space.”

Professor Greg Slabaugh, Director of the Digital Environment Research Institute (DERI) and Professor of Computer Vision and AI at Queen Mary, said: “The decision to host the CTP training in Queen Mary’s new flagship Digital Environment Research Institute further emphasises the institute’s position at the interface of science, engineering and medicine, and our ambitions to drive multidisciplinary working and cross-sector collaboration.”

Professor Viji Draviam, Director of Industrial Innovation at Queen Mary’s School of Biological and Behavioural Sciences, Faculty of Science and Engineering, said: "Queen Mary has funded six of the doctoral studentships and aims to significantly increase the number of industry partnerships within the Biopharma sector. Through this effort, Queen Mary is also keen to promote Equality, Diversity and Inclusion of underrepresented groups in the AI sector for biosciences research.''

Professor Mike Barnes, Professor of Bioinformatics and Director of the Centre for Translational Bioinformatics and Peter J. McCormick, Reader in Molecular Pharmacology (William Harvey Research Institute, Faculty of Medicine and Dentistry), said: “We are delighted in this cross-faculty and cross-disciplinary training programme with our industrial partners to train the next generation of drug discovery researchers.”

Advancing the frontiers of drug discovery

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 approaches could help 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.

The programme aims to advance the frontiers of bioscience discovery in areas underpinning the development and delivery of novel therapeutic drugs, with a special emphasis on technology development, pharmaceuticals, structural biology, systems biology and ageing based on the extensive expertise of Queen Mary researchers within these areas.

The new Industry-Academia partnership will develop talented researchers with skills in multiple disciplines at the intersection of biology, medicine and engineering to address existing challenges in the drug discovery process.

More information

 

For media information, contact:

Sophie McLachlan
Faculty Communications Manager (Science and Engineering)
email: sophie.mclachlan@qmul.ac.uk