Bringing Trust and Structure to AI in Healthcare

 

From March 18–20, 2025, the global life science community gathered in Basel, Switzerland, for DIA Europe 2025 — one of the world’s most influential meetings shaping the future of drug development, data-driven innovation, and regulatory science.

Representing Tekkare, our Founder and Chief Technology Officer Robin Sarfati joined the session “AI in Action: Showcasing Real-World Solutions” to explore how we can move from promise to practice when it comes to artificial intelligence in healthcare.

At Tekkare, our mission is clear: to make AI reliable, explainable, and traceable — built on structured open data and ethical design. This commitment was at the heart of Robin’s talk in Basel.

Data limits that prevents from Trustable Intelligence

AI has transformed how we access and analyze information, but in healthcare, its real-world impact remains limited. Robin highlighted four major barriers that prevent AI from achieving clinical adoption:

  1. Fragmentation and heterogeneity of data — scattered sources, unstructured formats, and isolated databases.

  2. Lack of traceability and rigor — outdated or unverified datasets that make outputs unreliable.

  3. Fundamental limitations of large language models — powerful tools, but often disconnected from scientific context.

  4. Infrastructure needs — from secure storage to interoperable frameworks that ensure scalability and compliance.

These challenges explain why, despite impressive prototypes, AI still struggles to move from labs to hospitals and we talk about it more in our article series here.

Building the Infrastructure for Real-World AI

The Pillars of Responsible AI Adoption

During the session, Robin presented Tekkare’s framework for enabling real-world AI use cases, built on complementary pillars:

  1. Aggregated Data Platforms — unified access to verified, structured health information.

  2. Semantic Models — ontologies that organize data for AI understanding and traceability, exemplified by our OIP Databank® technology.

  3. AI Agents as a New Medium — intelligent, proactive systems designed for meaningful human interaction.

  4. Robust Infrastructure for Healthcare AI — secure, high-performance environments ensuring compliance and scalability.

This approach is already being deployed in European initiatives such as ERDERA, the €380M EU-funded consortium dedicated to rare diseases, where Tekkare leads the design of the data and monitoring system.

“At Tekkare, we believe that transparency and data structure are the foundations of trustworthy AI,” said Robin Sarfati. “When you combine open data with rigorous semantic modeling, you create a reliable ecosystem for innovation.”

A Global Conversation on AI and Healthcare

Collaborative Voices Driving Change

The “AI in Action” session gathered leading experts shaping the regulatory and scientific landscape of AI in healthcare:

  • Catarina Carrão, Clinical Evaluation & Benefit-Risk Assessment Specialist, BioSciPons

  • Cécile Mathilde Ollivier, VP Global Affairs, Critical Path Institute

  • Remco Munnik, President, IRISS Forum

  • Anna Litsiou, Director – Regulatory Policy, AstraZeneca

Moderated by Estelle Michael, the pitches explored how real-world evidence, data science, and multi-stakeholder collaboration can accelerate innovation while maintaining ethical and regulatory rigor.

Together, the speakers emphasized the same principle that drives Tekkare’s work: AI must be verifiable, contextualized, and beneficial to patients.

Looking Ahead

From Basel to the Future of Trustworthy AI

Our participation at DIA Europe 2025 reinforced Tekkare’s commitment to advancing open innovation with trust.
By bridging public data, semantic technology, and real-world AI, we aim to build digital ecosystems that empower health professionals, researchers, and policymakers to make faster, smarter, and safer decisions.

 

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