As the industry leader in innovation in clinical research, Medidata, a brand of Dassault Systèmes, introduced its Protocol Optimization solution at the American Society of Clinical Oncology (ASCO) 2025 meeting in Chicago.
Protocol Optimization is a new product and part of the Medidata Study Experience to reduce the complexity in protocol design, increase trial efficiency, and improve the experience for patients and trial sites.
AI-Driven Optimization for Smarter Clinical Trials
Medidata Protocol Optimization utilizes AI predictive modeling with digital protocols and state-of-the-art aggregated trial data to simulate study outcomes before the First Patient In (FPI). The predictive data on patient burden, site performance, and trial costs helps the research teams with informed choices early on in the design process.
This feeds into a conservative approach by reducing the number of mid-study amendments, which not only incurs additional costs but also delays patient enrollment and study progression. Effectively, this means faster recruitment, decreased operational costs, and improved execution of clinical trials, especially regarding the complexities of oncology research.
Transforming the Study Experience
Medidata’s unified Study Experience platform enables research teams to collaborate seamlessly across trial phases with real-time access to digital protocol data. By integrating Protocol Optimization into this framework, Medidata empowers sponsors and clinical researchers to identify risks, optimize trial parameters, and enhance the patient and site experience—all before the trial begins.
This innovation aligns with Medidata’s mission to accelerate drug development through smarter, AI-enabled solutions that minimize inefficiencies and improve outcomes.
Key Benefits of Medidata Protocol Optimization
Through predictive AI modeling, Medidata’s Protocol Optimization can anticipate the impact on patients and sites earlier in the process and allows research teams to identify areas to anticipate and address issues earlier than other protocols without Protocol Optimization.
Through its proactive nature, proven protocol optima can reduce unscheduled and costly amendments mid-study, while optimizing protocol feasibility, which will maximize the number of patients recruited, which will ultimately lead to savings on study time and cost overall.
To support the process, the Protocol Optimization Solution is embedded within the Medidata unified Study Platform to manage subjects, sites, and teams, integrating study management as well as using real-world data to advance project decision making, including transforming the clinical trial continuum.
Conclusion
In a continually evolving landscape of increasingly complex clinical trials, and especially with the cumulative complexity of oncology trials, Medidata’s Protocol Optimization represents a revolutionary solution for bringing together data, AI, and digital design to improve experience and outcomes while optimizing every step of the trial. ASCO 2025 is a crucial launch point for the forward-looking, patient-centric, efficient, and future-ready clinical trial.
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