Advances in inflammatory bowel disease (IBD) treatment have improved outcomes for many patients but personalizing therapy and predicting response to therapy is a huge challenge. This has led to underutilization of effective regimens, undertreatment, and suboptimal outcomes. This activity reviews how new and emerging clinical decision support tools can help providers bridge this gap by predicting individualized disease complication risk and response to therapy.
This activity is intended for clinicians who manage patients with inflammatory bowel disease (IBD).
Educational Objectives
Upon completion of this activity, participants should be better able to:
Apply novel, predictive decision support tools to stratify patients with inflammatory bowel disease (IBD) based on complication risk and disease severity in order to inform appropriate treatment initiation and timing
Integrate biologics into the treatment regimen for IBD based on individual probability of response to specific biologics
Identify patients with IBD being treated with biologics who require more aggressive treatment approaches, such as combination therapy and treat-to-target monitoring
Activity Faculty
Parambir Dulai, MD (Chair)
Assistant Professor
UC San Diego School of Medicine
San Diego, CA
Joshua Rubin, MD (Co-Chair)
Assistant Clinical Professor
UC San Diego School of Medicine
San Diego, CA