Advances in Optimal Control Methods for Diverse Modeling Frameworks

Organizers:

Hannah Anderson (Moffitt Cancer Center), Kasia Rejniak, Moffitt Cancer Center

Description:

Optimal control is an optimization method that has largely been applied to ordinary differential equation models. However, biological systems are often modelled with other modeling frameworks, such as partial differential equations or agent-based models, to examine spatial aspects of the system. This mini-symposium will bring speakers addressing the application of optimal control methods for biological models in the context of each of these diverse modeling frameworks. We will specifically focus on the use of optimal control in treatment optimization, where a range of treatments and diseases will be considered. Optimization aims vary but include addressing drug efficacy, drug toxicity, administrative costs, and spatial constraints of disease growth. We will also evaluate the role of optimal control in the context of digital twins. Thus, this mini-symposium will highlight various modeling frameworks and a broad range of applications in mathematical biology.

Diversity Statement:

Our commitment to diversity is seen in our choice of speakers from different genders, institutions, geographical locations, and career stages. Speakers operate in a range of career stages, whether that be postdoctoral researcher, assistant, or full professor. While most of the institutions represented are American, South Korea is also represented. Further, the institutions vary in whether they are academic or cancer centers, and academic departments include both Mathematics and Systems Medicine.