AI is fundamentally dependent on data, but the vast majority of health data is not used for understandable reasons – mainly patient privacy, regulation and IP protection.
“This is the main underlying problem” of building AI solutions for life sciences and related fields such as pharmaceuticals, 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 training AI models without moving it by taking a decentralized approach.
Its clients include Roche and several hospitals, he said.
The core philosophy of federated computing is that “computations are executed locally where the data resides, and only the results (eg 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 in Apheris alongside his deep-tech investor eCAPITAL.
Hejka believes that Apheris can become a critical component in the federated data networks that are beginning to emerge. “We see a mature 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’ new funding comes after 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 pair made a major pivot in 2023 to focus on the proprietary side of data and double down on pharma and life sciences.
According to Röhm, it 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 in the commercial side.
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 Consortium (AISB), 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 a topic that Apheris will focus on further with this new funding. While agnostic about use cases, he understands that he can add value when there is very limited public data available, but much more valuable and diverse data that will not be unlocked unless life science companies feel safe to do so.
“Without addressing the concerns of data owners in providing data to AI, we don’t think the impact of AI can really be unlocked, and that’s ultimately the core mission of what we’re building,” Röhm said.
