Health Technology Assessment (HTA) and regulatory engagement are essential components of the SYNTHIA project, as it ensures that innovations in synthetic data are not only scientifically and technically sound but also meet the real-world requirements of healthcare decision-makers.

For synthetic data to be adopted in clinical and policy contexts, it must be trusted by HTA bodies, regulators, and payers who evaluate the safety, effectiveness, and value of health interventions. Including HTA and regulatory perspectives in SYNTHIA ensures that the tools, use cases, and methodologies developed are not only scientifically robust, but also relevant and acceptable to the stakeholders who assess the effectiveness and value of medical innovations.

This alignment is essential to support future use of synthetic data in submissions for reimbursement, coverage decisions, and health policy, thereby increasing the likelihood that SYNTHIA’s innovations can be adopted and scaled in healthcare systems across Europe.

By integrating HTA early into the project, SYNTHIA aims to align its outputs with the evidence standards that govern healthcare reimbursement and regulatory approval processes.

This work is led through Work Package 9: 'Regulatory & HTA Considerations and Real-Life Synthetic Data Application', co-led by SYNTHIA Partners NICE (the National Institute for Health and Care Excellence) and Pfizer. 

An important activity has been assembling an HTA and Regulatory Advisory Group, comprising experts from organisations across Canada, England, Germany, Greece, Ireland, Netherlands, Norway, Poland, Scotland, Spain, Sweden, Ukraine and Wales. The aim of this group is to embed the views of HTA and Regulatory stakeholders across the project, ensuring consideration is given to how this kind of data might eventually be used and accepted in real-life settings.

SYNTHIA HTA and Regulatory Advisory Group

On April 2, 2025, the first HTA and Regulatory Advisory Group meeting was held. Nineteen external HTA and regulatory representatives attended the 3-hour workshop as well as a number of SYNTHIA members representing the different work packages and use cases within the project.

Attendees were provided with an introduction to the SYNTHIA project, by the project coordinator Leonor Cerdá Alberich​ from Health Research Institute Hospital La Fe (IIS La Fe). In addition an overview of the six SYNTHIA use cases and an update on initial results from a literature review were presented. By using polls, voting exercises and interactive whiteboards, attendees of the meeting explored the topics of how synthetic data was currently being used within their organisations, if at all; what the potential opportunities for synthetic data are both now and in the future; and current concerns and considerations for its use in HTA and regulatory settings. Whilst a small number of attendees were more experienced in synthetic data, current use appears to be minimal and mostly restricted to purposes outside of formal HTA and regulatory decision-making, aligning with the emerging literature review findings. There was a general sense though that there is potential value in synthetic data though and that there are a number of ways that it could potentially be of use, particularly around supporting data privacy and possibly data augmentation. A range of concerns about data quality, understandability and resource impact were discussed, with a clear steer that there is a need to develop consensus evidence and reporting standards if this type of data is to be accepted by HTA and regulatory bodies in the future. Read about the key findings below.

"Synthetic data has lots of potential as a tool among others which can support the increasing use of data to drive decision making, both for HTA and regulators. There are already examples where synthetic data is used routinely to support analysis, for example, to test code prior to use on real data. Through SYNTHIA we will understand the potential for other higher fidelity uses, for example, in training prediction models, or to be used in place of real data where there are difficulties accessing real data sources. However, such uses will require careful consideration around whether synthetic data is generated robustly, and whether it sufficiently protects privacy. SYNTHIA will help us to explore these issues for HTA and regulatory settings.”

Steve Duffield, Associate Director – Real World Evidence Methods 
National Institute for Health and Care Excellence (NICE) - SYNTHIA Partner 

“One of the key challenges in regulatory and HTA submissions is providing sufficient contextual data—especially in cases of small or single-arm trials, or a comparator arm in the trial which may not generalize to every country. Synthetic data may offer an additional method to contextualize clinical trial information. An opportunity lies in using synthetic data to enhance—not replace—clinical trial evidence. But to realize its potential, we need to feel confident that the science and dissemination of synthetic data can bring more clarity, not more confusion, to regulators and HTAs. The SYNTHIA consortium of multi-stakeholder partners is playing a leading role in advancing that effort."

Marco DiBonaventura, Senior Director, HTA, Value & Evidence Team Lead, Hematology & Biosimilars
Pfizer - SYNTHIA Partner

The Work Package 9 team is currently undertaking on the use and perceptions of synthetic data in HTA and regulatory contexts. Over the course of the next 5 years, the team plans to work with the advisory group and others to develop best practice recommendations for the use of synthetic data.

Key findings of the first meeting SYNTHIA HTA and Regulatory Advisory Group

Current use and perception of value

Synthetic data is not currently being used by most of the organisations represented in the group, as far as attendees were aware. For those already using it, it is for purposes other than formal decision-making, for example in research or exploring how it can support evidence generation. Nearly two-thirds of participants, said their organisation was considering the use of synthetic data. 
When asked about the potential value of synthetic data, the majority of participants felt there was either ‘some’ or ‘high’ potential value for both decision-making and other purposes, though more so for purposes other than formal decision-making. 

Opportunities for use of synthetic data

A range of opportunities for the use of synthetic data in HTA and regulatory settings were discussed including facilitating data sharing/privacy preservation, supporting evidence gaps e.g. when RCT data is unavailable, data augmentation and training HTA models.  Some participants expressed a current lack of knowledge and familiarity in being able to say how this type of data could be used in practice. 

Considerations and concerns around Synthetic Data

The following areas were discussed:

  • Definition and scope of synthetic data
  • The complexity of the methods used to generate synthetic data, and to what degree these methodologies are transparent and understandable
  • The quality of synthetic data including accuracy, validity, reliability and completeness, and how we balance privacy with data fidelity
  • The need for criteria to assess the reliability of the methods used to generate synthetic data and the validity of the synthetic data generated.
  • The need to consider ethical and equality issues within synthetic data
  • The potential resourcing impacts/training needs within HTA and regulatory organisations to assess synthetic data
  • The need to align HTA and regulatory expectations and standards on synthetic data use, where possible

Implications for the SYNTHIA project

The discussions from the first HTA and Regulatory meeting highlight a number of key points for the SYNTHIA project to consider:

  • Avoid creating new definitions of synthetic data – it creates unnecessary confusion
  • Be clear on the project’s scope of what is being considered as synthetic data e.g. are in silico methods included?
  • Through use cases, seek to provide examples of high-quality synthetic data generation, that is well documented
  • For those new to the idea of synthetic data, clearly spell out why synthetic data is needed or what it adds over real data to support use cases
  • Alignment between regulatory and HTA bodies on the value of, acceptable use and required standards for synthetic data is important and should be championed within the project
  • Be able to articulate the project’s position on whether synthetic data is considered personal data, and which circumstances this is or isn’t the case
  • Use learning from the use cases to understand appropriate criteria for showing the validity, fidelity and accuracy of synthetic data.

If you are interested to learn more please send an email to contact@ihi-synthia.eu and we will connect you with Michael Bell, key contact for SYNTHIA Partner NICE.