AI is fundamentally dependent on data, but the vast majority of health data goes unused for understandable reasons — chiefly patient privacy, regulation and IP protection.

“This is the core underlying problem” of building AI solutions for life sciences and related areas like pharmaceutics, said German entrepreneur Robin Röhm. And not only that: collaboration when it comes to sensitive data can be a challenge. Apheris, Röhm’s startup, aims to address this through federated computing: making data securely accessible for AI model training without moving it by taking a decentralized approach.

Its customers include Roche and several hospitals, he said.

The core philosophy of federated computing is that “computations are executed locally where data resides, and only the outputs (e.g., model parameters) are aggregated centrally,” says Marcin Hejka, a co-founder and managing partner at OTB Ventures. Hejka has now co-led an $8.25 million Series A into Apheris alongside fellow deep tech investor eCAPITAL.

Hejka believes Apheris could become a critical component in the federated data networks that are starting to emerge. “We see a maturing ecosystem of third-party software tools (open-source federation engines, data quality tools, and security products),” he told TechCrunch. “Apheris also enables seamless integration with complementary privacy-enhancing technologies (homomorphic encryption, differential privacy, synthetic data).”

Apheris’s new funding comes in the wake of a pivot. Originally, Röhm and his co-founder Michael Höh started the company in 2019 with the goal of building a federated learning framework that competed with open source approaches, based on their experiences at their previous startup, Janus Genomics. But after raising a large seed round in 2022, the duo made a major pivot in 2023 to focus on the data owner side and double down on pharma and life sciences.

According to Röhm, this paid off. The startup found product-market fit with the new product it launched in the last quarter of 2023, and multiplied its revenue by 4 since then. Also backed by existing investors including Octopus Ventures and Heal Capital, its new round brings its total funding to $20.8 million, which will help the company hire senior talent with life science backgrounds, also on the commercial side.

The Apheris Compute Gateway, the software agent that serves as a gateway between local data and AI models, is already being used by the AI Structural Biology (AISB) Consortium, a joint initiative that sees members such as ​​AbbVie, Boehringer Ingelheim, Johnson & Johnson and Sanofi collaborate on AI-driven drug discovery.

Protein complex prediction will be one topic Apheris will further focus on with this new funding. While use-case agnostic, it understands that it can add value when there is very limited public data available, yet much more valuable and diverse data that won’t be unlocked unless life sciences companies feel safe doing so.

“Without addressing the data owners’ concerns in providing data to AI, we don’t think that the impact of AI can really be unlocked, and that’s ultimately the core mission of what we’re building,” Röhm said.