Digital twins for oncology via imaging

Identifying optimal therapeutic regimens on a patient-specific basis via mechanism-based mathematical modeling and quantitative imaging
(Thomas Yankeelov, PhD, University of Texas Austin)
Our lab is focused on integrating quantitative imaging data with mechanism-based, mathematical models to predict treatment response.  In this presentation, we will discuss some of our preliminary efforts at building digital twins to achieve this goal.  We will begin by considering the I-SPY trials for breast cancer as a specific example of how the success of adaptive, population-based clinical trials indicate that digital twins can lead to the success of adaptive, individual-based, clinical trials.  Then we will emphasize the importance of physics and biology-based mathematical models for constructing digital twins. Finally, we will illustrate how these ideas are beginning to play out in predicting and optimizing neoadjuvant therapy for breast cancer.