GENz-trials: Revolutionizing Clinical Trials to Optimize Assessment of Healthcare Innovations

Objective

GENz-trials proposes a next-generation clinical trial framework that integrates data science, automation, and simulation technologies to transform how trials are designed, conducted, and evaluated. The strategy builds on three interlinked innovation pillars. i) Automation of critical trial workflows using generative AI for personalized informed consent, protocol drafting, monitoring, and regulatory submission, thereby reducing administrative burden and expediting trial initiation. ii) Artificial Intelligence (AI)-driven patient recruitment by analysing large-scale Electronic Health Records (EHRs), and real-world datasets to optimize matching between patients and trial protocols, improving enrolment rates, inclusiveness, and avoidance of patient dropout. iii) integration of Digital Twins (DTs) and Synthetic Control Arms (SCAs) for protocol optimization through in-silico simulation and enabling ethically sound alternatives to placebo groups, using real-world data to construct robust comparators with fewer enrolled participants. GENz-trials will serve as a platform for boosting innovation in the assessment of the added value of integrated healthcare solutions, providing a flexible and data-rich environment to evaluate not only pharmaceuticals, but also diagnostics, digital health tools, and therapeutic combinations, ultimately strengthening health technology assessment, regulatory decision-making, and reimbursement strategies. The GENz-trials framework will be unfolded in three phases: development of core tools; retrospective emulation of historical trials; and prospective validation through a Phase IV clinical equivalence trial comparing a generic anticoagulant with its branded counterpart. Through this phased strategy, GENz-trials aims to establish a more ethical, inclusive, and cost-effective paradigm for clinical research, accelerating the evaluation and deployment of life-saving healthcare innovations.