Date: April 19, 2022
Speaker: Dr. T.J. Sego
Affiliation: Indiana University
Title: Enabling the Future of Biological and Biomedical Sciences with Advanced Modeling, Software and Computing
Abstract: Biological systems demonstrate immensely complex dynamics, where the properties, functions and processes at one scale emerge from underlying dynamics of smaller scales, from the molecular to organismal levels, over both short and long distances. Host-pathogen interactions during progression of infection present a strong example of such complexity, where whole-body responses emerge from highly localized events, and also result in highly localized events at multiple locations. Historically, research using mathematical modeling and simulation to characterize and understand progression of infection has targeted either systems-level or subcellular-level processes, such as modeling population dynamics or subcellular viral replication kinetics using ordinary differential equations (ODEs), often by generating models de novo and implementing single-use simulations with little to no apparent relevance for future refinement or integrated applications. This general neglect of emergence in biological systems, especially concerning the role and interactions of individual cells, and fragmented strategy of developing one-time modeling projects significantly inhibit biological and biomedical sciences from developing the quality of predictive capabilities accomplished in many areas of physics and modern engineering. As advances in computing technologies and artificial intelligence continue to enable solving more challenging computational problems, the paradigm of research in the life sciences must evolve to developing incremental, modular construction of complex models at, and across, various scales, and to implementing those models in advanced, reusable, large-scale simulations.
Dr. Sego’s research focuses on the development of complex, multi-method biological models and simulations over multiple scales during viral infection, and of simulation frameworks and technologies to enable their collaborative development, reuse and application in advanced computing environments. Dr. Sego’s recent work has developed and demonstrated the mathematical and simulation methodologies and computational capability to couple both subcellular- and systems-level modeling of host-pathogen interactions in the context of local, multicellular systems, and in a modular, reusable implementation that supports simultaneous co-development of model modules by collaborating, or even competing, research groups. This talk presents a series of overviews briefly introducing the CompuCell3D and Mechanica simulation environments, and highlighting select recent innovations, including the modular modeling and simulation of SARS-CoV-2 and influenza infection and host response, as well as the coupling of systems-level and localized, agent-based models and translation of information between them. Dr. Sego also briefly surveys his recent and current work as lead developer of CompuCell3D and Mechanica enabling large-scale modeling and simulation of advanced problems in biological complexity, and presents his vision for leveraging such new capabilities to develop innovative computational frameworks for collaborative, modular modeling and simulation of respiratory infection and host response.