Recently, we joined health leaders, innovators, and researchers from across the globe at HLTH Europe in Amsterdam, one of the continent’s most influential gatherings for the future of health technology. Over three days, the conference brought together a wide cross-section of the industry to confront the questions shaping the next decade of medicine: how AI is changing clinical care, what it will take to move from human-in-the-loop systems to autonomous care, and who gets to benefit from the technology being built today.
For us, the standout moment came on the data equity panel, where our Co-Founder and CEO, Dr. Manasi Aichmüller-Ratnaparkhe, joined fellow panelists to discuss trust, representation, and cross-border data sharing in health AI.
Behind Every Data Point is a Patient
Figure: Dr. Manasi Aichmüller-Ratnaparkhe joins fellow panelists for "Data equity: Who owns healthcare AI's most valuable asset?" at HLTH Europe.
Manasi’s message throughout the panel drew on the conviction that has shaped PAICON since its founding: that 84% of the world’s population remains underrepresented in the datasets used to train, validate, and calibrate modern health AI.
All the policies are made by healthy people for healthy people. If you ask a patient, they are willing to give data.
The line captures something we have built our entire model around. The barrier to closing the data gap in global health has rarely been a lack of willingness on the part of patients and communities. It has been a lack of infrastructure to responsibly find, access, and integrate that data in the first place.
From Awareness to Infrastructure
What stood out most across the three days in Amsterdam was how far the conversation around data equity has moved. A few years ago, much of the discourse in health AI was still focused on establishing that the data gap existed at all, on convincing skeptical audiences that bias in training data was a real and measurable problem.
That debate is largely settled now. The conversations at HLTH Europe this year were no longer about whether diverse, representative data matters. They were about infrastructure: how to actually build the systems, partnerships, and governance frameworks that make global data access possible at scale, across borders, across institutions, and across the populations that have historically been left out of the evidence base entirely.
This is precisely the gap PaiX Navigator was built to close. As an agentic disease data platform, PaiX Navigator is designed to help researchers, clinicians, and life sciences teams find, access, and work with disease data from the populations medicine has overlooked for decades, not by simply identifying where the gaps are, but by providing the operational infrastructure to actually close them. If you are interested in learning more about PaiX Navigator or exploring a partnership with us, get in touch with our team.
Beyond the Panel
HLTH Europe’s agenda extended well beyond data equity. Sessions throughout the conference explored what it will take for health AI to move from today’s human-in-the-loop systems toward genuinely autonomous clinical care, with several speakers emphasizing that the path forward depends on treating AI implementation as an evolving process rather than a one-time product launch. Other conversations focused on the practical realities of bringing health technology to market: proving clinical evidence, securing reimbursement, and ensuring that tools are genuinely usable by the clinicians and patients they are designed for, a consideration that, as one speaker put it, is too often an afterthought until it becomes a costly one.
Across these conversations, a common thread emerged. The technical capability of health AI continues to advance quickly. The harder, more consequential work lies in making sure that capability serves the full diversity of patients it is meant to help.
Looking Ahead
For us, HLTH Europe reinforced both the urgency and the momentum behind our mission. The field is no longer asking whether the Remaining 84% deserves a place in the evidence base. It is asking who will do the work of bringing them into it, and how quickly.
We left Amsterdam grateful for the conversations, energized by the colleagues and partners we connected with, and more convinced than ever that the infrastructure for global health data equity needs to be built now.
