Apheris Reimagines Life Science's AI Data Bottleneck with Federated Computing

Artificial Intelligence (AI) is a fundamentally dependent on high-quality data. However, the vast majority of health-related data remains unused due to valid concerns about patient privacy, regulatory requirements, and intellectual property protection. This paradoxical situation has significant implications for the development of AI solutions in the life sciences industry.

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The Challenges of Collaboration

Robin Röhm, a German entrepreneur and co-founder of Apheris, identifies collaboration as one of the primary challenges when it comes to sensitive data. "Collaboration is hard when you’re dealing with sensitive data," he explains. "We need to ensure that we can provide access to this data while protecting patient privacy."

Introducing Federated Computing

Apheris addresses these concerns through federated computing, a decentralized approach to making data securely accessible for AI model training without moving it. This novel methodology ensures that computations are executed locally where the data resides, and only the outputs (e.g., model parameters) are aggregated centrally.

The Potential of Federated Computing

Marcin Hejka, co-founder and managing partner at OTB Ventures, highlights the potential of federated computing in an emerging ecosystem of third-party software tools. "We see a maturing ecosystem of third-party software tools (open source federation engines, data quality tools, and security products)," he notes. "Apheris enables seamless integration with complementary privacy-enhancing technologies (homomorphic encryption, differential privacy, synthetic data)."

Apheris’ Pivot and Funding

Apheris has recently undergone a significant pivot in its business strategy. Originally founded in 2019 as a federated learning framework, the company shifted its focus to the data owner side in 2023 after securing a large seed round in 2022. This decision paid off, with Apheris finding product-market fit with its new product and multiplying revenue by four since then.

New Funding and Future Plans

The startup has secured $8.25 million in Series A funding from OTB Ventures and CAPITAL, bringing its total funding to $20.8 million. This influx of capital will enable Apheris to hire senior talent with life science backgrounds and expand its commercial capabilities.

Key Applications and Partnerships

Apheris’ technology is already being used by the AI Structural Biology (AISB) Consortium, a joint initiative involving several pharmaceutical companies, including AbbVie, Boehringer Ingelheim, Johnson & Johnson, and Sanofi. With this new funding, Apheris will focus on developing its capabilities in protein complex prediction.

The Importance of Data Ownership

Röhm emphasizes the critical role that data ownership plays in AI development: "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."

Apheris and the Future of Life Sciences

As the life sciences industry continues to grapple with the challenges of data ownership and collaboration, Apheris is well-positioned to play a critical role in unlocking the potential of AI. With its innovative federated computing approach and growing partnerships with pharmaceutical companies, Apheris is poised to make a significant impact on the industry.

About Apheris

Apheris is a startup co-founded by Robin Röhm and Michael Höh that aims to address the challenges of data ownership and collaboration in the life sciences industry. With its headquarters in Germany, Apheris has secured funding from leading investors and has established partnerships with several pharmaceutical companies.