Apheris, a German startup, has raised $8.25 million in Series A funding to tackle the long-standing challenge of accessing health data for AI model training while ensuring patient privacy, regulation, and IP protection. The funding round, co-led by OTB Ventures and eCAPITAL, brings the company's total funding to $20.8 million.

The core problem, as identified by Apheris' founder Robin Röhm, is that the vast majority of health data remains unused due to concerns around patient privacy, regulation, and IP protection. This limitation hinders the development of AI solutions in life sciences and pharmaceuticals. Apheris aims to address this issue through federated computing, a decentralized approach that enables secure access to health data for AI model training without moving the data itself.

Federated computing, as explained by Marcin Hejka, co-founder and managing partner at OTB Ventures, involves executing computations locally where the data resides, and only aggregating the outputs centrally. This approach allows Apheris to provide a secure and decentralized solution for health data access, which is critical for the development of AI models in life sciences and pharmaceuticals.

Apheris' customers already include Roche and several hospitals, demonstrating the startup's ability to provide a valuable solution to the health data accessibility challenge. The company's new funding will be used to hire senior talent with life science backgrounds, both on the technical and commercial sides, to further develop its product and expand its reach.

The startup's journey to this point has not been without its challenges. Originally, Apheris was founded in 2019 with the goal of building a federated learning framework that competed with open-source approaches. However, after raising a large seed round in 2022, the company made a major pivot in 2023 to focus on the data owner side and double down on pharma and life sciences. This pivot has paid off, with the company finding product-market fit with its new product and multiplying its revenue by 4 since then.

Apheris' solution, the Apheris Compute Gateway, 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. The startup plans to further focus on protein complex prediction with its new funding, recognizing the value it can add in areas where public data is limited but diverse and valuable data remains locked away due to concerns around data sharing.

According to Röhm, Apheris' mission is to unlock the impact of AI in life sciences and pharmaceuticals by addressing the data owners' concerns around providing data to AI. The company's federated computing approach is designed to provide a secure and decentralized solution that can help achieve this goal.

The implications of Apheris' solution are far-reaching, with the potential to accelerate the development of AI models in life sciences and pharmaceuticals. As the health data accessibility challenge is addressed, the industry can expect to see significant advancements in areas such as AI-driven drug discovery and personalized medicine.