Clinerion, Patient iP partnership aims to globalize access to real world data

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(Image: Getty/CarlosAndreSantos) (Getty Images/iStockphoto)

To improve clinical trial design, site selection, and patient enrollment, the real-world data solutions firm Clinerion is partnering with Patient iP, a health data and analytics company.

The companies will use Clinerion’s patented Patient Network Explorer platform and Patient iP’s proprietary daTAscape asset. The goal is to better target clinical trial sites and accelerate trial enrollment globally, according to the companies.

Clinerion’s network in the Americas, Europe, and Asia, includes more than 17m patients across more than 100 hospitals. Most recently, the company added a Georgia-based hospital to its network, though it has been expanding its network significantly over the last few years through strategic partnerships. The Switzerland-based company also filed a patent for its anonymized patient identification technology in 2017.

The partnership looks to improve clinical trials through the combination of Clinerion’s network with Patient iP’s platform, which contains more than 16m ambulatory electronic health records (EHR) across 5,000 practice sites.

Michael Margiotta, chairman, founder, and CEO of Patient iP, said, With complementary technologies and expanding geographies, Patient iP and Clinerion looked for opportunities to take advantage of their strengths – large datasets and easy to use cohort building tools to optimize both trial design and recruitment.”

With a combined dataset of over 33m patient lives in 16 countries around the world, the companies saw an opportunity to make “a significant change in the way drug development teams operate,” Margiotta told us.

“In designing trials, teams must establish criteria they will use to include or exclude different patients. By using longitudinal, real-world data the team can quickly assess impact of different criteria on the potential pool of candidate patients,” he said.

Margiotta explained, “If your criteria are too limiting, analysis might show that you’ve excluded a large number of the patients who might be helped by the treatment you are researching, or that you are looking in the wrong places for those patients.”

“Leveraging our combined data, along with our global platform to optimize inclusion and exclusion criteria can help accelerate patient recruitment and ensure that the results are more broadly relevant,” he said.