Sensyne Health and OMNY Health Sign Teaming Agreement to Support Breakthrough Research Through the Power of Real World Data and AI

Oct 15, 2021

Sensyne and OMNY will collaborate to develop new proposals to life sciences companies and healthcare providers to use real world data and advanced analytical tools to improve patient outcomes and accelerate the development of new medicines

The Teaming Agreement allows OMNY to engage Sensyne’s data analytics tools and consulting services and provides Sensyne with the potential to access OMNY Health’s 22 million de-identified patient records

Dover, DE and Atlanta, GA. Oxford, U.K. October 13, 2021: Sensyne Health plc (LSE: SENS) (“Sensyne”), the ethical Clinical AI company, and OMNY Health (“OMNY”), a leading US-based real world data company, today announced a strategic teaming relationship.

The arrangement establishes a nimble framework under which Sensyne can subscribe to data offerings via the OMNY Health Platform, which features more than 22 million de-identified patient records across broad therapeutic areas in support of Sensyne’s data analytics work for life science companies. In addition, Sensyne and OMNY have agreed to work together on commercial projects for life science clients to advance and accelerate ethical medical research.  By bringing biopharma clients a joint offering with OMNY real-world data and Sensyne machine learning expertise, both companies—and their health system partners—will have more opportunities to support important life sciences research.

The OMNY data network complements Sensyne’s existing global medical research dataset of 22.1 million patients, ethically sourced through strategic partnerships with US health systems and the UK’s National Health Service (NHS) trusts. With representation from  over 50,000 providers across 40 states, the OMNY Health Platform also offers control, security, and data governance to maximize the utility of information while maintaining compliance with US regulations.  Sensyne will now have a new avenue to access data from OMNY’s catalog of over 22 million unique patient records, significantly enhancing the scale of real world data on which Sensyne can apply its advanced machine learning and bringing the possible combined total of de-identified patient data available for collaborative research to over 44m patients.  

Derek Baird, President, North America, Sensyne Health said:

“This relationship has been forged on a mutual belief in the power of real-world data to support breakthrough insights and discoveries. The team at OMNY, like us, appreciate the complexity of working with longitudinal clinical records, and the trust that health systems place in our companies to analyse de-identified patient data in an ethical, secure, and responsible way.  We share common philosophies and missions, and complementary approaches in responsibly using real-world data to accelerate life science research for clients. This is an exciting alliance, and we are thrilled to be working together.”

Mitesh Rao, MD, CEO, OMNY Health said:

“OMNY Health embraces the opportunity to work with Sensyne Health’s world-class machine learning team and data science professionals, and is thrilled for Sensyne to join the platform.  We aim to revolutionize the healthcare ecosystem through our equality-driven data network while unlocking transformative real world data partnerships across the life sciences industry. This collaboration with Sensyne Health creates even greater possibilities to apply emerging technologies to the unparalleled data we’ve assembled, enabling both companies to ethically innovate on behalf of our respective partners, and most importantly, to create better outcomes for patients.”
Sensyne is working with life science partners on different types of research projects across multiple disease areas. The actionable insights from OMNY’s longitudinal patient data sets will help them with synthetic control arms, patient stratification, patient identification and selection, plus important late-phase clinical trial design, commercialisation, and health economic pricing decisions.

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