Almost £1m awarded to MHRA will advance projects to innovate AI and microbiome regulation and develop synthetic clinical trial data.
A grant of £970,688 is set to be given to the Medicines and Healthcare products Regulatory Agency (MHRA) to advance three key projects, which support one of the Agency’s core principles: unlocking scientific and digital innovation that keeps pace with the changing needs of patients, to ensure it delivers world-leading research innovation that focuses on protecting and improving patient health.
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Funded through the Department for Business, Energy and Industrial Strategy (BEIS) Regulators’ Pioneer Fund, the projects will develop synthetic data for clinical trials, produce a methodology to facilitate the safe introduction of complex ‘black-box’ artificial intelligence (AI) products in clinical settings, and enhance regulation to ensure the UK is the place to launch advanced microbiome products that can support the development of personalised medicine.
Synthetic data in clinical trials
According to the organisation, the first project has been awarded £750,387 to tackle the challenges of finding control groups for clinical trials, through the development of alternative synthetic datasets.
The project, estimated to take between 12-18 months to complete, aims to create a successful, entirely artificial control group to help change the way clinical trials are performed in common and rare diseases.
Dr Puja Myles, Director of the Clinical Practice Research Datalink (CPRD) at the MHRA explained: “This funding will allow us to [create] synthetic datasets that mimic real patient data for use in clinical trials.”
“This provides researchers with high-fidelity data that replicates the complex clinical relationships in real primary care data while protecting patient privacy, as they are wholly synthetic,” continued Myles.
Currently, patients are at risk of being randomly assigned to control groups and thus denied access to treatments that could improve their symptoms or extend their life, the regulatory body acknowledged.
Myles added: “This funding could revolutionise how clinical trials are conducted, giving patients access to potentially life-changing treatments, saving money that could be better spent on more advanced research while providing highly reliable results for the clinical researchers.”
A methodology that allows for complex AI algorithm interpretability
The second project, awarded £167,863, will produce a workable methodology to determine how to safely introduce complex ‘black-box’ artificial intelligence (AI) products into clinical settings, to allow clinicians to be confident that the decision from the AI device is appropriate and suitable in that specific context. Thus, this will help clinicians gain an understanding of what factors the algorithm considered and the weight it assigned them, so the individual can see how the algorithm reached its decision and therefore whether to overrule it or not.
Professor Johan Ordish, Head of Software and AI at the MHRA shared: “The transparency and explainability of AI has a key relationship with the safety as well as usability of [next-gen] devices. By producing a methodology that supports the regulation of both transparent and complex AI models, it will help us to make this vision a reality.”
Designing effective regulation guidance for microbiome therapeutics in the UK
The third project has been awarded £52,438 to explore the development of regulation guidelines around regulating microbiome therapeutics and diagnostics.
Dr Nicola Rose, Deputy Director for Research and Development at the MHRA explained: “The study of microbes associated with the human body has the potential to [allow] us to move towards a new era of personalised medicines. However, the absence of specific guidelines can delay the approval process for companies looking to bring their expertise and their pioneering treatments to the UK. We… will work with our extended network of scientists, clinicians, companies and regulators, both nationally and internationally, to capture the requirements needed for effective guidance.”
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