Journeys, experiences and best practices on computer modelled and simulated regulatory evidence

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Journeys, experiences and best practices on computer modelled and simulated regulatory evidence is the result of a recent collaboration from InSilicoUKMHRA, the Royal Academy of Engineering and the PHG Foundation.

In the era of AI and digital health innovation, the importance and value of computer modelled and simulated evidence (CM&S evidence) for clinical trials is increasing, yet uncertainty from industry and academia remains on its regulatory acceptability. In response, a cross-regulator workshop was held to discuss what uncertainty, lessons to be learnt, and barriers and enablers exist to increase confidence in its regulatory acceptability. 

This workshop report, freely available to download from InSilicoUK, therefore provides insight into what is hoped to be initial discussions between some of the key stakeholders on the acceptability of CM&S in several sectors, including for health.

Key findings include:

  • Consensus statement: Discussion was had on the possibility of creating a regulatory consensus statement to ease stakeholder uncertainty and signal regulatory openness towards CM&S generated evidence. The statement could also indicate regulatory support for undertaking health economic analyses to highlight the value of CM&S methods for generating evidence and encourage further industry adoption.
  • Public engagement: A top priority is exploring public acceptance and trust within relevant regulatory pathways. Increased public engagement initiatives such as Citizen’s Jury events are needed to understand the public’s concerns, to ensure transparency and to earn trust.
  • Development of generalisable principles: The development of good simulation practices and standards that support sound regulatory evidence with an emphasis on CM&S methods at both generalised and sector-specific levels are needed, and initial steps have been made by looking at adapting HM Treasury’s Aqua Book to keep pace with the ever-changing AI and digital innovation space.
  • International standard-setting and harmonisation: There is a need to look at developing mock or pre-submission processes for CM&S methods of evidence generation, as well as efforts to harmonise international standards in the medium to longer term.
  • Encouragement of future cross-sector discussions: There is a good, cross-sector appetite to both continue collaborative efforts to maintain momentum generated by the July workshop, and to use such dialogues to continue to learn from each other's experiences, including with the addition of further key stakeholders in future collaborative discussions.

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