Datavant, Real Chemistry form precision medicine partnership

By Jenni Spinner contact

- Last updated on GMT

(Who_I_am/iStock via Getty Images Plus)
(Who_I_am/iStock via Getty Images Plus)

Related tags: Datavant, Artificial intelligence, machine learning, Data management, Rare disease

The two firms will work together on solutions to connect de-identified, first-party data to real-world data to help advance precision medicine development.

Real Chemistry has announced it is working with Datavant to connect de-identified pharmaceutical data with real-world data (RWD). The partnership reportedly will use Real Chemistry’s, a platform that uses machine learning to uncover misdiagnosed and undiagnosed patients.

Our strengthened partnership enhances our mission of accelerating the commercialization of precision medicine​,'' said Jonathan Woodring, executive vice president and general manager at “By enabling the connection of clinical trial data, specialty pharmacy data, HUB data, and natural history or registry data with broad claims datasets, the journey to diagnosis is shortened, therapies are more personalized, and clinical trials benefit from real-world insights while protecting patient privacy​.”

Pharmaceutical companies and research partners increasingly have been interested in advancing precision therapeutics and gene therapies. However, diagnosis of such patients can be difficult, which means such patient populations tend to be underserved.’s RWD technology reportedly includes more than 300m de-identified patient journeys and 65b anonymized social determinants of health signals. According to Datavant, connecting the data streams can support the creation of customized machine learning models, which can be harnessed to improve the discovery and mapping of the diagnostic and treatment paths of patients dealing with rare and specialty diseases.

The machine learning models use comprehensive RWD assets for longitudinal evaluation. According to the collaborators, the partnership will help to advance these offerings by giving life-science firms the ability to deidentify and securely connect their own data to’s data.

The intent is to help elevate the training of’s machine learning models, thereby adding increased precision to the task of identifying small patient populations with acute medical needs.

''As pioneers in identifying rare disease patient populations through machine learning, recognizes the value in connecting first-party data to real-world data for greater modeling precisio​n,” said Travis May, president of Datavant. “We’re thrilled to partner with to advance life-saving specialty and rare disease treatments.​”

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