UK-based Sensyne Health has formed a research collaboration alliance with the University of Oxford’s Big Data Institute (BDI) for the development and assessment of clinical artificial intelligence (AI) and digital technology to manage and treat chronic diseases.

Under the three-year project, the healthcare technology company will leverage BDI’s population health, clinical informatics and machine learning expertise.

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Sensyne Health will get access to longitudinal datasets for patients in the NHS Trusts. The company will also use its Clinical AI capabilities and data from the digital health applications meant for chronic diseases management.

“Clinical AI will be used to analyse vital information captured from patient-clinician consultations during long-term management of chronic disease.”

The objective is to build unique new datasets, adding to those currently available for analysis by the company. It is expected that the data will enable a better understanding of chronic diseases, in turn driving drug discovery and development.

Clinical AI will be used to analyse vital information captured from patient-clinician consultations during long-term management of chronic disease.

The captured data is also expected to facilitate remote monitoring of patients using digital health tools and wearables in order to track disease progression and inform clinical care.

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Sensyne Health CEO Paul Drayson said: “This new collaboration with the BDI is designed to apply world-class data science to the growing burden of chronic disease on society, and create an effective partnership between the NHS, industry and academia that delivers scalable improvements to patient care, accelerates the discovery and development of new medicines and shares the commercial value created with our partner NHS Trusts and the University of Oxford.”

The partnership will also advance Sensyne’s in-house SH-001 project, investigation the clinical associations and consequences of diurnal changes in blood pressure.

SH-001 found nocturnal surges in blood pressure in a subset of hospitalised patients.