At AZ, we re-defined our feasibility approach placing emphasis on indication landscape assessments and early strategic engagement with sites. Maximizing indication landscaping, we build foundational datasets that subsequent projects can leverage. This means our downstream design assessment and protocol feasibility is more efficient, and our investigators are engaged earlier in the process. Learn more about our re-designed feasibility process, tools, and how we collaborate to re-use insights for reliable predictability.

• Identify how using the right tools for remote training can improve the performance management of sites
• Exploring how best to implement virtual training to reduce protocol deviations
• Finding the right virtual training supplier who can simulate critical protocol challenges by using lifelike, online scenarios that allow learners to practice decision making in a consequence-free environment
• Remote Site Performance Management tech – what’s available and what would work with your study

This presentation will share the proposed advanced predictive modeling methodology and results to predict enrollment and key milestone dates (time to endpoint maturation). The methodology can be used to predict milestone dates for time-to-event trials like in Oncology and for fixed duration trials like in Rheumatology. R-shiny dashboard and a cloud-based application are also developed with the goal to help every study team. The talk will also share the evolution of our thinking, the process of development and the challenges we have faced thus far.

Using AI and analytics, we can speed clinical trial enrollment and accelerate overall clinical development timelines by predicting and including best performing sites into the study. An integrated set of data and advanced analytical tools allows users to identify best performing site based on historical performance and site health. Diversity and decentralized trials and their effect on site selection will be also discussed.

How Janssen’s Feasibility CoE leveraged data and analytics to deliver rapid enrolment across a diverse and representative participant group for Janssen’s phase 3 COVID-19 vaccine trial, Ensemble 1. In this presentation, we will share key strategies used to optimize site selection for Ensemble 1, to ensure diverse recruitment targets were met across age, ethnicity, and co-morbidities while also satisfying aggressive timelines, all through the evolving pandemic. This required a multi-faceted approach layering quantitative and qualitative data in support of the efforts which resulted in record breaking enrollment, 3 months from FPI to LPI, 43,000 patients enrolled with impressive diversity.

With the industry under more pressure than ever to ensure high success rates for clinical programs, we look at the key questions across the development cycle that if answered correctly can ensure a successful trial. We explore how, by leveraging the power of patient-centric data science and the world's largest clinical development database, biopharmaceutical companies are unlocking the insight required to ensure shorter cycle times, fewer amendments and deliver faster cures.

Sponsors and CROs need more than change management to operationalize decentralized trials. In this session, Kyle Hogan will outline the approaches sponsors and CROs can take to build value in the decentralized trial participant journey, from pre-implementation to study launch and monitoring. 

Delays in clinical trial patient enrollment are significant challenges for sponsors, especially for biomarker-targeted investigational therapies associated with rare genomic variants. Join us and discover the solutions offered by SOPHiA GENETICS, leveraging insights from multimodal datasets - including 770’000 genomic profiles - curated across 780+ healthcare institutions. We can better enable biomarker-driven clinical trials in oncology and inherited rare disorders to meet recruitment goals by identifying potential sites worldwide.

Inspired by the interplay between humans and machines in chess, during this presentation we will showcase to the audience how combining human intuition and machine intelligence can help create Superminds that amplify the power of making evidence driven decisions in trial design and site identification in today’s clinical trials environment.