BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Prof. Dr. Nick Cogan (Department of Mathematics Florida State Uni versity USA) DTSTART:20261007T140000Z DTEND:20261007T150000Z DTSTAMP:20261025T111949Z UID:AMIS/15 DESCRIPTION:Title: Br idging Mathematical Modeling and Experimental Data to Optimize Cancer Ther apy\nby Prof. Dr. Nick Cogan (Department of Mathematics Florida State University USA) as part of Asymptotic Methods in Statistics\n\n\nAbstract \nOptimizing cancer treatment will increasingly rely on close coupling bet ween experimental research and mathematical modeling. A central obstacle i n oncology is our incomplete understanding of how therapies reshape the tu mor microenvironment and how immune activity drives tumor regression. This gap is especially acute in aggressive cancers such as triple-negative bre ast cancer (TNBC)\, which lacks standard biomarkers and has limited treatm ent options. Our collaborative work develops a quantitative framework for studying combined immune and chemotherapeutic interventions. Using a novel radiolabeled T-cell tracking approach\, we follow immunomodulation over t ime and use these measurements to guide the design of optimal therapy sche dules. In this talk\, I will present ordinary differential equation (ODE) models of combination therapy dynamics and compare model performance with and without T-cell data. I will also discuss broader directions for this w ork\, including extensions to organ-level analysis and the use of optimal control methods to refine treatment strategies. By integrating experiment and theory\, we aim to strengthen the predictive power of cancer treatment models and move toward more effective\, personalized therapeutic protocol s.\n\nhttp://www.math.fsu.edu/~cogan\n LOCATION:https://researchseminars.org/talk/AMIS/15/ END:VEVENT END:VCALENDAR