Evidence generation in clinical research has undergone a transformation over the past decade, with growing demands for diverse data to meet regulatory requirements and support commercial claims. This demand is particularly acute in oncology, where multiple competing products demand robust and innovative trial designs.

In Phase 3 studies, researchers increasingly aim to demonstrate statistical significance across more than one primary endpoint. This webinar introduces a novel software implementation that efficiently simulates multiple endpoints and rigorously tests generated data to optimize trial planning.

During this session, our experts will demonstrate how native workflows in the software can be applied to design and optimize an oncology clinical trial with three concurrent endpoints:

• Overall Response Rate (ORR)
• Progression-Free Survival (PFS)
• Overall Survival (OS)

They will also demonstrate how these built-in features can be combined with R programs to leverage simulated data for each endpoint and build a multi‑state model, enabling more realistic trial scenarios.

Register now to learn, through a real case study, how software‑driven simulation enables statisticians and trial planners to optimize study design and communicate decisions more effectively across drug development teams.

Moderator

J. Kyle Wathen, Vice President, Scientific Strategy and Innovation

Speakers

Valeria Mazzanti, Associate Director, Customer Success

Julija Saltane, Senior Innovation & Software Engineer