Atropos Health aims to use generative AI to transform real-world clinical data into publication-grade evidence for healthcare. Credit: LALAKA / Shutterstock.

US-based healthcare data company Atropos Health has raised $33m in a Series B funding round led by investment management company Valtruis.

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The funding round involved participation from both new and existing investors, including McKesson Ventures, Cencora Ventures and Merck Global Health Innovation Fund, along with Presidio Ventures, Breyer Capital and Emerson Collective.

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Founded in 2019, Atropos Health aims to use generative AI technology to transform real-world clinical data into publication-grade evidence for healthcare.

The company’s proprietary ‘GENEVA OS’ operating system is designed to enable rapid and robust analysis of real-world data by streamlining the production of healthcare evidence.

It plans to use the funding to expand its role in the value-based care sector.

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Atropos Health’s evidence-generating applications are designed to support whole-person care and enhancing value-based performance.

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They are already being used by healthcare organisations such as Arcadia, a company that works to use data to improve patient outcomes.

The investment will also support the full-scale launch of ChatRWD, a platform designed to reduce the time required to produce real-world evidence through the use of a chat-based interface.

ChatRWD is built on the GENEVA OS and aims to maintain accuracy and transparency in clinical evidence production.

It operates within a large language model (LLM) independent framework to ensure data security and integrity.

Atropos Health CEO and co-founder Dr Brigham Hyde said: “Atropos Health is built on investment in scaling the production of high-quality, transparent and now real-time evidence production that matches the standards of the clinical and research communities.

“This funding round, which includes multiple major strategic stakeholders in healthcare ecosystem, is validation that our platform is rapidly becoming standard not only for automation and user experience, but also as trusted quality layer between healthcare data and critical evidence needed to better inform patient care, research and policy.”