Laboratory Informatics Guide 2020


AI


accelerates drug


discovery pipelines


As the potential for AI and machine learning methods in drug development is realised, companies and organisations are partnering to better understand and develop these technologies, writes Sophia Ktori


Bayer recently launched LifeHub UK, the seventh of the company’s global LifeHub centres, which are pioneering collaborative research to accelerate the development of new solutions to global health and nutrition challenges. Te new UK centre, sited at Reading’s Green


Park, joins existing LifeHub facilities at what Bayer terms innovative hotspots in Berlin, Boston, California, Lyon, Singapore and Tokyo/ Osaka. One of the first companies to move into the


Developments in


experimental techniques and high throughput and high content tests at the cellular and molecular level mean that we now have greater amounts of high-quality data


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new UK LifeHub is UK clinical AI firm Sensyne Health, which is working with Bayer to develop AI-enabled automated image analysis solutions for disease diagnosis. Te project will combine Bayer’s existing expertise in the radiology field with Sensyne’s access to millions of anonymised UK National Health Service (NHS) records and imaging data, accessed through Sensyne’s partnership with NHS Trusts. ‘Te ultimate aim is not only to use


AI-enabled technologies to speed disease detection, but also to help provide informed insight that will help direct treatment decision making,’ commented Abel Archundia-Pineda, head of digital transformation and IT at Bayer Pharmaceuticals. ‘We are going to see an unprecedented


positive technological revolution in healthcare in the next 10 years, and a large part of that


will be driven by clinical artificial intelligence – the application of machine learning methods involving clinical expertise from researchers,’ added Lord Paul Drayson, Sensyne Health CEO. ‘Te current medical discovery system involves interpreting enormous volumes of diverse information. By using clinical AI, we are able to analyse vast volumes of data in a short period of time. Tis data-driven approach to discovery can


help transform the future of drug development resulting in more coherent diagnoses for sufferers of poorly understood chronic diseases, identifying comorbidities and speeding up the pathway to treatment. It could also lead to personalised treatment plans with a much higher likelihood of success, based on analysis of, for example, the link between genetics and responsiveness to different treatments. Data can also be used to help find novel therapeutic treatments and uncover new uses for existing drugs, all while saving time searching for a diagnosis, reducing cost, decreasing the pressures on the UK NHS workforce, and ultimately improving patient outcomes.’


Data drives new approaches to medicine Te collaboration between Bayer and Sensyne builds on an initial agreement, announced in


www.scientific-computing.com/LIG20


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