Clinical trials for new cancer treatments take years to complete because recruiting patients, collecting data, and tracking outcomes is slow and labour-intensive. This project aims to speed that up by plugging routinely collected health data—such as GP records, hospital admissions, and cancer registries—directly into trial workflows. The problem is that most oncology trials still rely on manual processes: staff must identify eligible patients by hand, chase up follow-up data, and record outcomes from clinic visits. This is expensive, error-prone, and limits how many trials can run at once. The researcher will work across four large-scale trials at UCL’s MRC Clinical Trials Unit to learn how these trials operate, then develop methods for integrating healthcare systems data (HSD) into each stage—from patient identification to outcome capture. If successful, the work could make future cancer trials faster, cheaper, and more inclusive by reducing the burden on hospitals and patients. It would also help establish best practices and regulatory standards for using HSD, so other trial teams can adopt the same approach. The research is applied, not fundamental: it directly targets a bottleneck in the clinical trial pipeline, with the goal of getting effective treatments to patients sooner.
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Background Advancing cancer treatments through clinical trials is critical but takes many years due to the substantial resources required and significant logistical challenges. Digital technologies offer great potential to improve efficiency. An emerging area is incorporating ‘Healthcare systems data’ (HSD), routinely collected health datasets, into trials. This could streamline processes, including identifying eligible patients, supporting data collection and capturing outcomes. The MRC Clinical Trials Unit (CTU) at UCL provides comprehensive training on all aspects of large-scale academic oncology trials. It offers the additional opportunity to collaborate with leading methodologists in HSD and contribute clinical expertise on how this data can improve conduct of oncology trials. This research could accelerate the development of cancer treatments, improving patient outcomes. Aims 1. Gain comprehensive training and experience across four large-scale oncology trials encompassing planning, conduct, analysis and dissemination. 2. Use this experience to develop methods by which HSD can optimise oncology trials. 3. Advance my professional development by gaining specialist research skills, expanding my leadership capabilities and increasing my teaching expertise. Methods I will work within multidisciplinary trial teams, contributing to trial management and acquiring expertise in conduct through direct experience and training courses including ‘Pharmacovigilance’ and ‘Statistical aspects of Multi-Arm Multi-Stage Trials’. I will join the CTU-embedded Patient and Public Involvement and Engagement (PPIE) working group, to facilitate patient contributions across all trial aspects. I will collaborate with CTU-based methodologists connected with Health Data Research UK exploring how to integrate HSD to capture cancer outcomes in late-phase oncology trials. I will attend ‘Using HSD in trials’ and statistical analysis courses to conduct this research. I will explore patient perspectives on researchers accessing their HSD, supported by experienced qualitative researchers. I will enrol on the UCL leadership programme, and co-lead and teach on the UCL intercalated BSc in Clinical Trials. How results of research will be used I will build upon my previous experiences in early-phase trials, acquiring an understanding of practical, regulatory and ethical aspects of trials, preparing me for a career as a trialist. I will gain advanced research skills and establish networks through academic collaborations. I will contribute to presenting and publishing impactful trial results, methodology and protocol papers. HSD research will be published and presented at conferences and stakeholder forums comprising clinicians, data scientists and trialists. This will impact the broader trials community by influencing design of future trials, consolidating best practices and informing regulatory standards for using HSD.
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