Covariate Adjustment in Randomized Clinical Trials Based on Latest FDA Guidance: Application to Composite Covariates

Life Sciences, Clinical Trials,
  • Wednesday, September 06, 2023

In May 2023, the US Food and Drug Administration (FDA) released its final guidance titled “Adjusting for Covariates in Randomized Clinical Trials (RCT) for Drugs and Biological Products”. It is difficult to overstate the importance of this guidance as baseline covariate adjustment is an integral part of any statistical analysis of RCTs. Covariate adjustment has become a standard statistical tool because of its simplicity and benefits, including increased study sensitivity and power.

In the guidance, the FDA provides many practical recommendations for correctly performing adjusted analyses in both linear and nonlinear models. However, while opening doors to innovative solutions, the FDA remains relatively vague on one of the most difficult and least understood aspects of covariate adjustment, how to select the covariates for the analysis:

“In some circumstances, these covariates may be known from the scientific literature. In other cases, it may be useful to use previous studies (e.g., a Phase II trial) to select prognostic covariates or form prognostic indices.”

One such innovative application of the guidance is the use of composite covariates such as Placebell, a placebo prognostic covariate developed by Cognivia.

Join this exclusive webinar to explore the latest FDA guidelines and the remarkable benefits of using prognostic covariates to enhance trial accuracy and improve assay sensitivity while complying with regulatory requirements. With a decade of experience developing prognostic covariates and assisting sponsors with adjustments, Cognivia will help you translate this critically important FDA guidance into practical recommendations for your next trial. The featured speakers will also delve into concrete applications of composite prognostic covariates.

Speakers

Samuel Branders, Cognivia

Samuel Branders, Data Mining Scientist Director, Cognivia

Samuel Branders is a Data Mining Scientist Director leading the statistical modeling at Cognivia since 2015 and has participated in the development of Placebell since the beginning. He graduated from the University of Louvain with a PhD in Machine Learning and Bioinformatics. During his PhD, he worked on survival analysis and prognostic models applied to cancer research with both biomedical and methodological/statistical contributions.

Message Presenter
Hervé Pagès, Cognivia

Hervé Pagès, Customer Solution Director, Cognivia

Hervé Pagès, a PharmD graduate from France’s Faculté de Médecine et de Pharmacie de Poitiers, boasts a distinguished pharmaceutical career spanning over two decades. He began as a Clinical Project Manager at Parexel in 2000 before assuming the role of Senior Clinical Project Manager at Eli Lilly in 2003. In 2007, Hervé became the Clinical Project Leader at Aepodia, where his exceptional leadership led to his promotion to CEO in 2018. Currently, he serves as the Customer Solution Director at Cognivia.

Message Presenter

Who Should Attend?

Companies and organizations conducting and analyzing randomized controlled trials (RCTs):

  • Pharmaceutical/Biotechnology companies, CROs
  • Tech Companies/Service Providers
  • CEO, CSO, CMO, CDO, COO VP, SVP, EVP, Sr. Director, Director, etc. of Clinical Development, Clinical Science, Clinical Operations, Regulatory, Clinical Project Management, Business Development and Clinical Scientists

What You Will Learn

Attendees will gain insights into:

  • A comprehensive review of the new FDA guidance on covariate adjustment in clinical trials
  • Exploring advantages of covariate adjustment with a prognostic composite covariate — maximizing trial efficiency in compliance with the FDA guidance
  • Navigating documentation and operational requirements for implementing analysis adjustment with a prognostic baseline covariate.

Xtalks Partner

Cognivia

Cognivia is the first and only company to combine quantification of patient psychology with artificial intelligence (AI)/machine learning (ML) to improve  measurement of therapeutic efficacy in clinical trials – and beyond. Cognivia technologies predict patient behavior and treatment response in clinical trials using predictive ML powered algorithms based on a quantitative understanding of patient psychological traits, expectations and beliefs collected via our own and specific questionnaires developed toward that objective. Cognivia aims at harnessing “the power of the mind” and quantifying this unique phenomenon to improve clinical trial success rates, de-risk drug development and ultimately improve healthcare.

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