Archives: Agenda

• Empirical Data quantifying the magnitude of the problem
• Identification of Opportunities to optimise protocol design and improve clinical trial performance
• Case examples of strategies and their impact

• Opportunities most resonating within panel member companies
• Strategies and tactics to address these opportunities
• Implementation challenges and how to overcome them
• Areas of future focus and opportunity

Moderator: Ken Getz, Executive Director, Research Professor (PHCM), Tufts Center for the Study of Drug Development

Harnessing the convergence of high-fidelity data with advanced AI is now essential for de-risking clinical trials and accelerating therapies to patients. What if the distance between a draft protocol and a validated study execution plan was reduced to a single, unified simulation?

Join Medidata’s Rob Buka for a deep dive into the future of holistic trial design and planning. Learn how advanced modeling and simulation capabilities within a central workspace can revolutionize trial operations. This session will illustrate Medidata’s strategy for optimizing protocol design, predicting trial outcomes, and achieving greater clinical and operational success in the next generation of drug development.

• Reframing clinical readiness in oncology: Why trial success is increasingly determined upstream—through mechanistic validation, patient stratification, and translational alignment before first-in-human dosing.
• Clinical Trials in a Dish platform: How patient-derived iPSC and organoid disease models can be deployed to predict responder populations, evaluate combination strategies, and inform biomarker-guided trial design.
• Leveraging academic ecosystems: Integrating biobanks, molecular datasets, and investigator networks to accelerate translational insight and enable more targeted, recruitment-efficient oncology trials.
• Capital-efficient development strategies: Using functional precision modeling to reduce late-stage attrition, optimize cohort sizing, and deploy clinical budgets with greater signal-to-cost discipline.

• Aligning in-house capacity to outsourcing needs to ensure your biotech sticks to budget
• Understanding when it is time to outsource to ensure sufficient oversight and management of all vendors
• Looking ahead to identify your biotech needs to integrate services seamlessly into current processes

• A 50-year retrospective on the escalating costs, stagnant timelines, and the attrition crisis in general and oncology drug development
• An analysis of the “Biomarker Revolution” and its profound historical influence on phase transition success rates, clinical trial durations, and evolving reimbursement models
• How integrating predictive biomarkers into clinical design eliminates the “noise” of non-responders and can multiply the overall probability of drug approval by a factor of five
• The Omios Biologics Solution: How we are utilizing a proprietary computational platform to develop the first biomarker-guided, systemic oncolytic viruses

• Understanding the biological mechanisms that drive treatment resistance in oncology
• Using biomarkers to identify patients most likely to benefit from targeted therapies
• Applying functional genomics to uncover new therapeutic targets and resistance pathways