Nick Conley

Artificial intelligence is transforming the way we understand and manage complex diseases like IBD. This workshop offers a rare opportunity to explore how AI can accelerate discovery, improve patient stratification, and optimize clinical decision making.

Including interactive breakout with live, follow-along tutorial using commercial software to allow participants to build ML Models based on real IBD datasets, making predictions and exploring real-world applications of AI in drug development.

Key Topics to be Explored:

• Investigate innovative use cases that analyze thousands of clinical, molecular, and microbiome data points to identify key predictors of treatment response and relapse
• Using AI trained exclusively on IBD to classify cell types and quantify populations rapidly
• Understand the limitations of AI including hallucinations, bias, and the importance of specialized prompt engineering. Raise concerns of unpredictability and difficulties in validation for clinical use to overcome future roadblocks
• Highlight the potential to compensate for variability, applying computational approaches to analyze endoscopic videos and advanced imaging, linking visual patterns to clinical outcomes
• Apply tools to monitor clinical response and optimize treatment strategies in IBD, enabling more proactive and personalized care in real-world settings