Validation of new exercse models and therapy optimization

Type 1 diabetes (T1D) is a chronic autoimmune condition characterized by the body's inability to produce insulin; a hormone essential for regulating blood sugar levels. This lifelong condition poses a myriad of challenges for those diagnosed, ranging from the need for constant monitoring of blood glucose levels to the daily administration of insulin through injections or an insulin pump. Managing T1D can be a daunting and relentless task, as even minor miscalculations can result in severe health complications. Moreover, disturbances like physical activity, eating habits, and sleeping patterns can greatly affect the glycemic profile of a T1D patient. As the prevalence of T1D continues to rise worldwide, there is an urgent need for innovative therapies and technologies to improve the lives of individuals living with this condition. In this context, simulators and models play a crucial role, offering a means to better understand the intricacies of T1D and develop personalized treatment strategies. These tools enable healthcare professionals to tailor interventions to the unique needs of each patient, ultimately leading to more effective diabetes management and enhanced quality of life. This project has a primary objective of improving the accuracy of exercise models for individuals with T1D, which will be instrumental in constructing simulation environments and digital human twins of these patients. The initiative is anchored in utilizing the T1DEXI dataset for the development of these exercise models and comprises three distinct components.
The first segment aims to create a digital twin of T1D patients that can effectively simulate the dynamics of exercise, an area where current T1D simulators fall short. This will be accomplished through a data-driven approach, potentially employing deep generative models.
The second part focuses on developing exercise models tailored to gender, acknowledging the significant impact of sex and gender on how the body responds to health challenges, including diabetes. Variations in lifestyle, sex hormones, and body composition contribute to differing blood glucose regulation between men and women, as evidenced by research highlighting increased risks for women with type 1 diabetes compared to men in similar circumstances (Huxley, 2015).
The third and final part of the project involves optimizing therapies based on the exercise models created in the previous two phases. By better approximating the responses of type 1 diabetes patients to exercise and accounting for gender-related differences, this project seeks to pave the way for more personalized and effective therapy development.