The Stat4Onc Annual Symposium is a venue for interdisciplinary dialogue among clinical and quantitative scientists about cancer clinical trials. We seek participation by researchers from academia, industry, and regulatory agencies to share new research, discuss novel ideas, ask questions, and provide solutions for cancer clinical trials. Oncologists, statisticians, data scientists, and computational biologists can exchange views on trial design and conduct, drug development, and translation to patient care. Topics for this symposium include training for new generation of statisticians and clinicians, translational and precision oncology, master protocols, pediatric oncology research and drug development, populational cancer research, biomarkers and subgroups, real world data/evidence, and engagement of under-representative population in oncology research.
You must follow the instructions below, and submit your abstract by September 30, 2026, Eastern Time. The submission window will be open on June 2026.
Registration: You can submit your abstract without being registered. However, the presenting author must be registered at the time of the conference to present their work.
Abstract limit: You may submit up to two separate abstracts for consideration. The selection committee may select both, one or neither may be selected during the approval process (500 words max).
Abstract type: Submitted abstracts must fall in line with the themes of the conference. All submissions will receive equal consideration. We encourage researchers, in particular young researchers and trainees in academia, industry and government to submit the title and one-page abstract.
If selected for a poster: Once you have submitted an abstract it will be reviewed by the committee around the deadline date. You will be contacted once the committee has completed their review. If the abstract is accepted, students will be notified via email by October 15, 2026. They must also print and bring their posters to the conference on the first day. Detailed information will be sent via email.
Questions? If you have any questions about the process please email ming-hui.chen@uconn.edu.