Can AI Predict Drug Resistance and Guide Biologic Selection in IBD?

In this clip, Prof. Xin Chen asks Prof. Marietta Iacucci whether artificial intelligence can help predict drug resistance, assess related risks, and support biologic selection in inflammatory bowel disease, while also addressing concerns around data privacy and algorithm bias. Prof. Xin Chen is Deputy Director of the Department of Gastroenterology at the General Hospital of Tianjin Medical University. Prof. Chen is a Chief Physician and PhD Supervisor with active roles in digestive endoscopy, gastroenterology quality control, and medical-engineering collaboration in China. The responding expert is Prof. Marietta Iacucci, Professor of Gastroenterology at University College Cork and Consultant Gastroenterologist at University Hospitals MUH and CUH in Cork, Ireland. Prof. Iacucci is internationally recognized for work in IBD, endoscopy, histology, and AI-driven precision assessment, with leadership roles in ECCO, ESGE, and ASGE. Key highlights from this clip: ●Whether AI may help predict drug resistance and treatment response in IBD ●Why strong phenotyping and careful feature selection are essential before building predictive AI models ●How clinical, endoscopic, histologic, and molecular data may need to be layered together for meaningful prediction ●Why patient clustering and clearly defined methodology remain central to AI model development in IBD ●How data privacy, governance, and algorithm bias continue to shape real-world AI adoption ●Why clearer standards and society-led guidance will be important for broader regulatory and clinical implementationThis video is intended for medical education and professional discussion. #MedJ #IBD #InflammatoryBowelDisease #ArtificialIntelligence #PrecisionMedicine #Biologics #DrugResistance #Gastroenterology #Endoscopy #Histology #DataPrivacy #AlgorithmBias #MedicalEducation