IHI organized a workshop in October 2024 examining how our projects have faced the challenges and exploited the opportunities regarding real-world data, digital health and artificial intelligence in Europe.

The workshop attendees discussed how challenges and opportunities could be addressed within the scope of future IHI public-private projects and how connections could be made to the emerging European Health Data Space (EHDS).

SYNTHIA, the first synthetic data project funded by IHI, was invited to join the discussions and was represented by two of our partners:

  • Guillermo Sanz, Head of Clinical Hematology at Hospital Universitari i Politècnic la Fe
  • Henri Souchay, Regional Clinical Research Manager at GE Healthcare

In April 2025, IHI released the report about the outcome of the discussions and its recommendations.

Key take aways of the report- valuable for all running and future Public-Private Partnership

  • The importance of the patient perspective: Engaging patients from the beginning to the end of a project is key to delivering transformative results. Patient perspectives help to design projects more effectively, provide continuous feedback throughout a project’s lifecycle and contribute to the scientific outcomes and overall success of a project by bringing in the lived experience of diseases. Several examples of IHI and IMI projects where the benefits of involving patients as partners and participants from the outset were highlighted.
  • The use of real-world data, digital health or AI applications are game-changers for many areas of health: Some examples of the potential impacts include faster diagnoses for people with rare diseases, more precise diagnostics for personalized care, improved medicine safety evaluations, the conduct of clinical trials in hard-to-reach populations, or the development of patient-centric markers of diseases. However, to use real-world data and AI safely and efficiently in healthcare systems, structure, scientific rigour and quality, trust, transparency, access and interoperability must be ensured.
  • Legitimacy and Trust: Legitimacy (i.e. making sure that actors have a legitimate reason to access data) and trust (i.e. making sure that access, analysis and outcomes are for the benefit of individuals and society, on the basis of transparency) are critical for research and the rolling-out of real-world data/real-world evidence, digital health and AI applications. It’s essential to ensure that the data that is used is of high quality, that AI tools are delivering trustworthy results, and that patient data will be used responsibly. However, transparency, legitimacy and trust can be elusive concepts and building a shared understanding is critical for the success of European Health Data Space (EHDS). Research projects in public-private partnerships are an opportunity to build transparency and trust between a large number of stakeholders across all sectors of health care for the future implementation of the EHDS.
  • Adopted standards drive utility, scale and value of real-world data: Real-world data is collected in many forms and in various ways and needs to be harmonised before it can be used effectively. For instance, several systems for standardizing real-world data for clinical research are currently in use in different areas - establishing consistent definitions and tools can enhance the efficiency and reliability of RWD applications. Public-private partnerships such as EHDEN have supported the adoption of standards at scale and have trained European companies, healthcare organizations and SMEs in the use of these standards. Building alignment and capacity is key for the success of the developing European Health Data Space (EHDS). It was noted that guidance is emerging on initiatives and standards in use.
  • The value of public-private partnerships: A lot of work still needs to be done – to further improve interoperability of data, to develop trustworthy AI tools, to facilitate the education of healthcare professionals that will generate and use real-world data and AI in their daily practice, and to find solutions to address the tensions between fostering data-driven innovation and ensuring data protection and privacy. We often refer to these public-private partnerships as precompetitive – they drive joint actions between many companies, government agencies, researchers, healthcare and patient organizations that aim to develop and deliver value for the health ecosystem as a whole. Ultimately, the goal and outcome of the joint research should be to provide clear guideline and inform regulation that drives uptake, applicability and value.
  • The European context: Any innovations using real-world data or AI will need to take the AI Act, Medical Devices Regulation and General Data Protection Regulation (GDPR) into consideration. New potential projects should support the operationalization of research in the European Health Data Space (EHDS) as well. IHI launched a call in 2025 aiming to develop a framework for safeguarding intellectual property within EHDS to support innovation. This is one example of public-private partnerships that offers an opportunity for companies, SMEs and research organizations to build capacity for driving innovation in a landscape of rapidly changing technology and innovation. Start with an end in mind: Early engagement with the technical companies who are making the devices that are retrieving real-world data, or those that are creating the AI tools, can minimize the risk of encountering difficulties at a later stage and will help drive progress from innovation to implementation.
  • Regulatory science: Regulators need to both uphold and advance standards to inform decision making and to facilitate novel medical products. For the practical use of real-world data and AI in healthcare settings, requirements at national and European level have to be considered. Public-private partnership projects can serve to deliver robust, tested, neutral data and methods to help regulators to make decisions on health innovations that are using real-world data and AI. These partnerships also develop important areas such as the use of real-world evidence and the definition and validation of digital and AI driven outcome measures.
  • Scaling and implementing innovation: IMI and IHI projects have delivered clear impact, but one of the key challenges is how to ensure that the infrastructures, frameworks, tools, and other results are sustained and adapted past the project’s end and continue to deliver benefits to the health and research community. During the workshop, the participants highlighted the need to determine how to scale and implement project innovation and consider longevity from the earliest phase of the project – when the grant proposal is being written. IHI provides guidance building from project experiences. Options include forming non-profit legal entities or securing support from other funding sources or from private companies to continue the work. 

For more reports or other typs of information, visit the IHI website >