Sinkove is developing an AI-driven solution designed to address challenges faced by traditional clinical research using radiology data, particularly those related to recruiting real patients for control groups. Recruitment for these control groups can be costly, time-consuming, and raises ethical considerations, especially when patients might receive placebos or less effective treatments. To mitigate these issues, Sinkove's approach creates virtual, in-silico representations of patients based on historical radiology data and electronic health records. Using generative AI techniques, specifically denoising diffusion models, the system generates synthetic radiology images and patient outcomes, effectively creating virtual control arms. This project aims to evaluate the feasibility and commercial potential of using digital twins to simulate standard-of-care disease progression and treatment outcomes in clinical trials. The AI learns from diverse datasets provided by global medical imaging providers to produce synthetic images accurately mimicking control group outcomes, significantly reducing the need for physical patient recruitment. Employing these AI-generated virtual control arms is expected to lower the costs and shorten the duration of clinical trials. Additionally, this approach addresses ethical concerns by minimizing patient exposure to placebos or suboptimal treatments, thereby enhancing patient safety and ethical integrity in clinical research. During this feasibility study, Sinkove will refine its AI models, validate the synthetic outcomes through pilot studies involving retrospective clinical trial data, and undertake a regulatory assessment to evaluate readiness for clinical application. The project includes establishing a secure, compliant infrastructure for synthetic data generation and validation. The anticipated outcomes include making clinical research more efficient, ethical, and potentially accelerating the delivery of life sciences products and services into healthcare. This initiative addresses a significant healthcare challenge with the potential to deliver substantial benefits to the UK life sciences sector and improve overall patient care.