CAREER: THEORY FOR DEVELOPING AN IMMUNE DIGITAL TWIN

About This Grant

Creating a software replica of all actionable knowledge about the immune system, an immune digital twin, has the potential to provide insights into many unknowns in biology, human health, and disease. The goal of this project is to initiate a construction of generic modules of immune cells and assemble them across multiple scales, enabling their reuse in response to various pathogenic insults. An immune digital twin could predict how an individual’s immune system may respond to an infection, how inflammation becomes harmful, or how therapies work before they are even tested on patients. To this end, this CAREER project will focus on two fundamental questions: What level of mathematical abstraction and granularity is required to represent an immune digital twin, and how can diverse data types — categorical, qualitative, and quantitative — be integrated to calibrate and validate its components? These research efforts will be complemented by the development of summer research programs for undergraduates aimed at introducing students to mathematics and STEM applications through the lens of digital twins. Courses and publicly available code will be specifically designed for undergraduate students interested in research, with the goal of bringing more students into digital twin science. To address the project's research questions, the first objective will bring forward the mathematical theory and concepts necessary to conceive a generic digital twin of an immune cell. The mathematical foundations of stability, identifiability, and well-posed immune digital twins will be developed. The second objective will integrate data from different labs into multi-scale algorithms to calibrate immune digital twins. The causal effects of these twins and calibration algorithms will be evaluated in a ground truth model that will provide a transparent setting for interrogating the proposed research questions. The third objective will leverage the previous two to create a blueprint of an immune cell. Ultimately, the research and educational activities of this project will contribute to national prosperity by developing new computational methods that advance digital twins capable of predicting immune responses in a virtual environment. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.