Cardiovascular disease is a broad, varied and serious condition affecting the heart or blood vessels, and is the leading cause of death globally. As well as being associated with damage to arteries in the heart it affects other organs such as the brain, kidneys and eyes. The NHS identifies cardiovascular disease as a clinical priority and the leading condition where lives can be saved over the next ten years. The disease currently affects seven million people in the UK and accounts for one in four premature deaths(1).
There is an immediate and essential need to help improve patient care and advance the clinical development of treatments for cardiovascular disease. The costs of clinical trials for cardiovascular disease are high and the risk of failure in late-stage clinical trials is significant. Consequently, investment in cardiovascular drug development over the last 20 years has been declining2. Breakthroughs in the development process for new cardiovascular disease medicines are required.
In July 2019 Sensyne Health signed a two-year pharmaceutical collaboration with Bayer to accelerate the clinical development of new treatments for cardiovascular disease using Sensyne Health’s proprietary Clinical AI technology platform.
The Sensyne Health Clinical AI platform analyses de-identified and anonymised linked genotypic and phenotypic data sets. AI is then used to analyse the data to answer specific clinically relevant questions and generate new discovery hypotheses. This enables improvements in pharmaceutical development, clinical trial design and the discovery of new medicines.
Sensyne Health is working with Bayer to address clinical development challenges by asking clinically relevant questions of de-identified and anonymised data sets provided by its partner NHS Trusts using AI. Sensyne Health will use statistical approaches together with complex machine learning methodologies such as the “deep clustering” algorithms licensed from the University of Oxford. Sensyne Health will also use its proprietary algorithms configured to analyse noisy, sparse electronic patient record data alongside innovative approaches such as causal inference. This project employs a truly interdisciplinary approach that benefits from the cardiovascular disease expertise and drug development capabilities of Bayer with the AI capabilities of Sensyne Health together with the deep clinical expertise and longitudinal patient data sets relevant to cardiovascular disease resident in the NHS.
The collaboration will initially focus on ways to improve the identification of heart failure and stroke across patient populations, and gain a deeper understanding of the varied forms of the disease that patients suffer from. Our aim is to design clinical trials for new cardiovascular drugs which have a higher success rate in Phase II and Phase III.
(1) NHS England: Cardiovascular disease (CVD), https://www.england.nhs.uk/ourwork/clinical-policy/cvd/,accessed 20/05.
(2) Cardiovascular Drug Development: Is it Dead or Just Hibernating?, Fordyce et al; Journal of the
American College of Cardiology, Volume 65: Issue 15, pp.1567–1582, 21 April 2015, https://www.sciencedirect.com/journal/journal-of-the-american-college-of-cardiology/vol/65/issue/15.