Center for multiscale immune systems modeling - the center of excellence (COE) is a research initiative that brings together experts from various fields to develop innovative solutions for multi-scale…

Center for multiscale immune systems modeling - the center of excellence (COE) is a research initiative that brings together experts from various fields to develop innovative solutions for multi-scale modeling in infectious and immune-mediated disease (IID). The COE consists of the: administrative core (AC), community development and education core (cdec), model and data sharing core (mdsc), and three research projects (RP). Each component plays a crucial role. The AC serves as a central hub, connecting various entities, and plays a critical role in pivoting COE resources during disease outbreaks. IT administers the opportunities fund, supporting proposals from investigators across niaid- sponsored modeling groups. The cdec will develop educational resources, build communities of practice and learning, organize research experiences for graduate students and postdoctoral fellows, and set up document sharing facilities, messaging platforms, and a centralized website to facilitate knowledge sharing. The mdsc will develop an informatics infrastructure that enables seamless integration of data and models across different scales, facilitating more accurate predictions and informed decision-making. The RPS focus on bridging models of host-virus interactions across biological scales. RP1 models humoral defense against viral pathogens, using antibody-antigen molecular dynamics at the molecule scale to understand the constraints limiting the evolution of immune repertoires at the individual scale. RP2 models the immune cell as a target of viral infection, using agent-based models of lymphoid tissue at the cell scale to inform host-pathogen dynamics at the individual scale. RP3 models the interactions between individuals and populations, using agent based models of host-pathogen interactions at the individual scale to inform stochastic epidemic models at the population scale. The research focuses on modeling a set of clinically important viruses, including HIV-1, sars-COV-2, epstein barr virus (EBV), and others. The models can be used to study disease pathogenesis, the effect of medical interventions, and disease transmission in heterogeneous population networks. Key strengths of the proposed COE are (1) the ability to coordinate administrative approaches and technologies for the infectious disease modeling community; (2) a collaborative environment that encourages knowledge sharing, innovation, and the development of cutting- edge solutions; (3) balanced representation of the experimental and computational communities within each core and RP; (4) extensive experience with IID modeling, team science, education, and community development; (5) robust informatics infrastructure for model and data sharing that already hosts large-scale NIH- funded projects; (6) exceptional strengths integrating generative deep learning with computational modeling in the mdsc and RPS, and (7) the importance of the proposed research to develop more accurate IID models that can inform public health policy and decision-making. The unique strengths of the proposed COE make IT an ideal platform for advancing IID research, developing innovative solutions to complex problems, and responding during infectious disease outbreaks, epidemics and pandemics.