New MHRA Data Strategy underscores role of real-world evidence for timely regulatory decision-making

The UK Medicines and Healthcare products Regulatory Agency has launched its first Data Strategy for 2024–2027, outlining a comprehensive plan to leverage data, digital technology, and real-world evidence to prioritize patient safety and public health and foster innovation in healthcare regulation.

Medicines and Healthcare products Regulatory Agency (MHRA), the UK’s regulatory body,  has introduced its Data Strategy at a time of rapid technological evolution, described as the ‘fourth industrial revolution’ and cultivated by big data, advanced analytics and emerging digital technologies, coupled with artificial intelligence (AI) and machine learning (ML). According to Dr June Raine, Chief Executive Officer of the MHRA, “Never before has science and technology converged with such velocity and potential for tangible impact,” on healthcare and medical products. The MHRA Data Strategy is built on five core themes, each linked to specific deliverables, and outlines a clear vision for capitalizing on these innovations while addressing existing challenges within the broader health data landscape.

“By delivering this strategy, working in close collaboration with partners both within the UK and internationally, we will use data to deliver timely, proportionate, and scientifically robust regulatory decisions which facilitate early access to medical products and safeguard public health.” Dr June Raine DBE, Chief Executive Officer, MHRA

Theme 1: Supporting data-driven innovation, early access, and interdisciplinary data science to underpin our regulatory framework

The MHRA Data Strategy emphasizes the use of real-world evidence (RWE) alongside traditional randomized controlled trials, aiming to streamline product development and potentially enable earlier patient access to innovative treatments. They refer to the value of real-world data (RWD) across the product lifecycle, providing opportunities including understanding natural history and disease heterogeneity, identifying clinical trial participants, and enhancing post-authorization surveillance. In line with global regulatory efforts, such as the US FDA’s Advancing RWE Program, the agency will continue to publish guidance on RWD/RWE and engage with international regulators to promote harmonization.

Key initiatives include launching a Scientific Dialogue Programme to provide early advice on real-world studies, piloting a Data, Methodology, and Endpoints Qualification process, and addressing underrepresentation in clinical research. The goal is to support innovative evidence generation while ensuring safety through proactive surveillance, ultimately improving access to new medicines and medical devices.

Theme 2: Enabling effective, timely, and proportionate regulatory decision-making through RWE

The Data Strategy references the UK’s vast health data resources, such as the Clinical Practice Research Datalink (CPRD) RWD research service, which provides anonymized patient data for research purposes from 65 million patients across the UK’s GP practices. However, the strategy also acknowledges challenges in the UK health data landscape, including issues with data silos, quality, linkage, and interoperability.

To address these issues, the MHRA plans to evaluate the role of common data models and federated analytics to generate scientifically robust RWE for regulatory decisions. The agency will also deliver secondary legislation and guidance to improve traceability of medical devices and strategically engage with device registries to enhance safety activities. Additionally, they aim to improve data linkage across care settings to generate actionable evidence for regulatory purposes.

Theme 3: Developing, extending, and integrating the MHRA’s capabilities in data and digital technologies

Recognizing the need for specialized expertise in areas such as data science, analytics, machine learning, and software engineering, the MHRA Data Strategy outlines plans to build the skills and infrastructure required to harness the full potential of these technologies.

The MHRA aims to foster a culture of collaboration and shared best practices across the organization. Key initiatives include establishing a Cross-Agency Data Science network to encourage knowledge sharing and innovation, and strengthening ties with the Graduate Programme to offer data and digital-focused placements.

Additionally, the agency will launch a Data Maturity Assessment programme to evaluate its internal data assets and implement an organization-wide data architecture with the principle of ‘collect once, use many times.’ This approach is designed to provide a comprehensive view of medical products. The MHRA also plans to operationalize data management environments to ensure best practices in data stewardship are followed.

Theme 4: Establishing, embedding, and expanding synergistic partnerships across the data ecosystem

With a strong network of academia, industry and public institutions, the MHRA aims to collaborate with stakeholders to enhance population health and wellbeing through data-driven regulatory science.

Achieving these goals will require extensive cooperation, and the MHRA plans to leverage its Centres of Excellence in Regulatory Science and Innovation to drive progress in data science for regulatory needs. This effort aligns with similar global initiatives, such as the European DARWIN and FDA Sentinel programs, which use new data sources and methodologies to enhance evidence generation and manage uncertainty.

The MHRA will also work towards international harmonization by collaborating with bodies like the International Council for Harmonisation (ICH) and the International Medical Device Regulators Forum (IMDRF) to standardize terminology and data. In addition, academic partnerships will be established to develop new analytical methods for improving the benefit-risk assessment of medical products. The agency will collaborate with UK partners to ensure the integration of high-quality, decision-ready data to support regulatory decisions.

Theme 5: Safely and responsibly harnessing the potential of artificial intelligence and advanced analytics throughout the product lifecycle

Recognizing the ‘revolutionizing’ abilities of AI and ML, the fifth theme of the MHRA Data Strategy focuses on harnessing these technologies to improve data-driven decision-making across the lifecycle of medical products. AI/ML, alongside advanced techniques like modelling and simulation, can process vast and complex datasets, uncovering patterns and associations that traditional methods would miss, while promising improvements in efficiency, productivity, and safety.

The MHRA is committed to applying these tools responsibly in regulatory contexts, ensuring they are used to generate RWE and reduce uncertainty in benefit-risk evaluations. Key initiatives include exploring natural language processing to improve pharmacovigilance, investigating the potential of generative AI and large language models, and evaluating advanced methods for detecting adverse event signals in medicines and medical devices.