Connecting Protocol Design Complexity with Trial Performance Outcomes

This event is now available on demand.

Event overview

Industry-wide, clinical trial protocols continue to increase in complexity over time. This webinar adds to the growing evidence of which elements of trial design and strategy correlate with lower study recruitment, increased timelines, and cost.

Connecting protocol complexity with trial outcomes provides insight to allow for better designed protocols that sites and patients want to participate in. Consequently, there is less potential for operational errors resulting in deviations and amendments and efficacy and safety is determined more efficiently, moving potential treatments more swiftly to patients who need them.

Three key take-aways

In this webinar, data science experts will present:

Design data gathered from a large sample of protocols conducted over a 10-year period, with associated trial performance metrics.
Results of the assessed statistical correlation of 28 protocol design variables with 18 trial performance outcomes to identify key outcomes correlated to complexity.
Where to critically focus during protocol development to mitigate impact of complexity on trial time, cost, and quality.

For any technical questions please contact Jordan Ramesh: jramesh@mjhlifesciences.com

Denise Messer
Design Analytics Director
IQVIA

Denise Messer is a design analytics director at IQVIA. She has over 25 years of experience in research and clinical trials, including expertise in clinical trial planning and design. She has spoken at conferences and has been published in industry journals covering topics such as assessing and scoring trial patient burden, highlighting the voice of the patient in trial design, and assessing protocol complexity.

At IQVIA, she helped develop the IQVIA Data-informed Protocol Assessment (DIPA), using data to highlight areas for protocol optimization before operationalization, including creation of a patient burden algorithm and protocol scoring benchmarks.

LinkedIn: https://www.linkedin.com/in/denise-messer-31a728a0

Steven Zhang
Global Analytics Manager
IQVIA

Steven Zhang is a global analytics manager at IQVIA. He has more than seven years of experience in the Healthcare Tech industry, with a strong expertise in data science and machine learning. He started his career working on leveraging AI to personalize treatment selection in depression.

As a data scientist for this IQVIA project, he was responsible for the data processing and exploration regarding both the enrollment strategy and operational metrics. Combined with insights on clinical trial protocols, Steven analyzed what factors from protocols contribute to complexity and their impact on study benchmarks such as cycle times and other trial performance outcomes.

Steven holds a Master of Science degree in Neuroscience from McGill University.

LinkedIn: https://ca.linkedin.com/in/stevenwzhang

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Connecting Protocol Design Complexity with Trial Performance Outcomes

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