Critical care has historically relied on explanatory, parallel-group randomized trials to generate evidence to inform practice. Such designs can be inefficient and expensive. COVID-19 has changed the landscape of critical care trials by advancing alternative, innovative, and efficient approaches to trial design, conduct, and analysis. This session will review these new methods, including platform trials, adaptive trials, Bayesian methods, pragmatic trials, and trials informing personalized treatment choices. Clinicians will learn how to interpret and apply results of these trials to practice. Researchers will learn how to use these methods to generate real-world, personalized evidence, improving care for critically ill patients.
• Apply knowledge acquired about novel trial designs to interpret and critique the results of future platform, adaptive, pragmatic, and personalized clinical trials
• Assess the strengths and limitations of novel trial designs in order to facilitate the implementation of results from future trials into clinical practice to improve patient outcomes
• Apply an understanding of "individual treatment effect" and "personalized medicine" to the manner in which they implement the results of clinical trials into clinical practice
Matthew Semler, MD, MSc
Michelle Gong, MS, MD
Ewan Goligher, MD, PhD
Jonathan Casey, MD, MSCR
Carolyn Calfee, MD, MSCR
Matthew Churpek, MD, MPH, PhD, ATSF
Matthew Semler, MD, MSc
Introduction: ABCs of Next-Gen RCTs
Platform Trials
Adaptive Trials and Bayesian Methods
Pragmatic Trials
Using Biomarkers for Precision Medicine in Clinical Trials
Using Machine Learning for Precision Medicine in Clinical Trials
Roundtable Discussion