About DISS2026

This year’s theme delves into the cutting-edge realms of biostatistics and data innovations within pharmaceutical development, particularly in the context of artificial intelligence (AI) and machine learning (ML).

The rapid advancements in biomedical technology, big data science, and AI have opened unprecedented opportunities for drug development. This evolution necessitates integrating diverse, state-of-the-art tools and methodologies into clinical trial research. Key areas of focus will include the application of machine learning and AI, the utilization of electronic health records, pragmatic trials, patient-centered trial designs, master protocols, adaptive trial design methodologies, and the effective use of historical controls and real-world evidence. Unlike traditional clinical development approaches, these innovative strategies demand the systematic extraction of insights from data collected through ongoing clinical trials and external sources. They also leverage AI and ML algorithms and analyze high-dimensional clinical, genomic, and imaging data as biomarkers for creating next-generation pharmaceutical products.  

The symposium will commence with a day dedicated to short courses, offering a robust and comprehensive foundation for the subsequent sessions. The following day and a half will feature an array of enriching experiences, including keynote addresses by industry leaders, engaging parallel sessions, and dynamic poster lightning talks.  

The Steering Committee and our local Organizing Committee extend a warm welcome to all participants. Your expertise in biostatistics and data innovations will undoubtedly enrich our discussions. Please do not hesitate to let us know if you require any assistance during your stay in Durham.

The Duke Industry Statistics Symposium (DISS) is organized by the Department of Biostatistics and Bioinformatics, Duke University School of Medicine and several industry and non-profit partners. The first symposium was established in 2013 to discuss challenging issues and recent advances related to the clinical development of drugs, biologics and devices and to promote research and collaboration among statisticians from industry, academia, and regulatory agencies.