Moneyball for Drug Development: How Causal Inference can Increase the Probability of Success in Clinical Trials

Discover an informative webinar that focuses on how studying oncological trial data and patient selection biomarkers can increase the probability of success (PoS).

The mantra “Correlation does not equal causation” is well known. However, causal inference, a new set of statistical techniques, can identify causal relationships and even derive experimental results and counterfactuals from historical data. In this webinar, the expert speakers will introduce causal inference and apply it to ten years of oncological clinical trial data, seeking opportunities to optimize trial design decision-making. But what if there was a proven process to identify trade-offs that could save precious resources when designing trials with the greatest probability of success?

The expert speakers will present results from studying patient selection biomarkers, which focus a trial on a subset of patients, possibly increasing the trial’s PoS. Conversely, this focus can reduce the patient population for which regulators approve a drug. To help companies consider this trade-off, the analysis provides unbiased, precise estimates of how much the focus increases a trial’s PoS. This analysis can help identify opportunities for underutilized biomarkers that can significantly impact PoS or where they are overutilized and their use offers little benefit in terms of PoS, unnecessarily reducing the target population.

The findings shared will empower sponsors to understand the impact of their choices better, de-risk pipelines and make more informed decisions regarding their clinical development strategies.

Register for this webinar today to learn how causal inference can revolutionize clinical trial design decision-making.

Speakers

Gary Summers, Director, Oncology Portfolio Decision Sciences, GSK

Gary Summers is a Director of Oncology Portfolio Decision Sciences at GSK, where he applies decision analysis to drug development. Complementing this work, Dr. Summers studies how uncertainty impacts decision-making.

His paper, “Friction and Decision Rules in Portfolio Decision Analysis,” won the 2021 Clemen-Kleinmuntz Best Paper Award. His computer game design that analyzes decision-making received US patents 7,349,838, 6,408,263 and 6,236,955. Dr. Summers has an MS and PhD in Management Science from Northwestern University.

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Andrew Rainboldt, Senior Data Scientist, Intelligencia AI

As a Senior Data Scientist at Intelligencia AI, Andrew Rainboldt spearheads work around innovative applications of Causal AI & Bayesian Statistics in clinical trial design. He is currently leading two projects. The first is developing a robust benchmarking application utilizing hierarchical Bayesian models to help clinical sponsors evaluate the baseline probability of technical and regulatory success (PTRS) for new oncology drug development programs. This process goes beyond traditional benchmarking by indication and therapeutic area. The second is developing causal models to improve decision-making in clinical design and development.

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