Current simulations of biology are either physically accurate or scalable, but not both; in particular, models of a single whole useful cell are incomplete. The behavior of simple model organisms can be partially simulated, but knowledge gaps remain. Furthermore, simulations of more complex organisms such as E. coli remain elusive. Comprehensive and fully descriptive computational models of E. coli behavior, while complex, offer significant advantages, including an important opportunity to contextualize and align parameters across different dimensions of cell function and more utility for potential Department of Defense (DoD) stakeholders and use cases compared to simplified model organisms (e.g., a minimal cell).
The Simulating Microbial Systems (SMS) program seeks to create computational simulations that accurately predict the behavior of bacteria in various contexts. Specifically, SMS aims to create comprehensive, generalizable, and interpretable simulations of E. coli by leveraging recent innovations across two broad domains: (1) high-throughput and automated experimental test beds; (2) advanced computational techniques.
“The program seeks to dramatically accelerate progress towards a fully resolved computational model of E. coli, one of the most widely studied organisms in biology,” stated Dr. Christopher Bettinger, SMS program manager. “This program will bring to bear advances in physics-based computation that is parameterized using newly acquired data generated from high-throughput experiments. The result will be a comprehensive and extensive software package that will, in the future, help our DoD stakeholders design and execute microbiology experiments on a computer rather than in a laboratory.”
“There have been dramatic advances in applying neural networks and other techniques to simulate the dynamics of complex and uncertain systems in domains such as fluid mechanics, materials behavior, and combustion chemistry. SMS seeks to build on these innovations to forecast the dynamics of a complex biological system: E. coli bacterium,” added Bettinger.
SMS seeks interdisciplinary, comprehensive, and integrated workflows to generate unknown parameters from new data to inform computational models that can predict E. coli. SMS ultimately envisions unified experimental and computational workflows that can jointly address simulation development and data acquisition/curation. Wet lab microbiology and analytical experiments should consider software architecture, physics-based modeling, and analytical techniques as they generate and curate data. Similarly, simulation development should both leverage acquired data and inform future experiments. The output of the program will be a software package that can simulate E. coli behavior across many length scales.
The SMS program will include an ethical, legal, and societal implications (ELSI) plan to include discussions regarding human use of the technology following its development.
Information is available on the upcoming SMS Industry Day on SAM.gov.
https://www.darpa.mil/news-events/2024-08-14
Current simulations of biology are either physically accurate or scalable, but not both; in particular, models of a single whole useful cell are incomplete. The behavior of simple model organisms can be partially simulated, but knowledge gaps remain. Furthermore, simulations of more complex organisms such as E. coli remain elusive. Comprehensive and fully descriptive computational models of E. coli behavior, while complex, offer significant advantages, including an important opportunity to contextualize and align parameters across different dimensions of cell function and more utility for potential Department of Defense (DoD) stakeholders and use cases compared to simplified model organisms (e.g., a minimal cell).
The Simulating Microbial Systems (SMS) program seeks to create computational simulations that accurately predict the behavior of bacteria in various contexts. Specifically, SMS aims to create comprehensive, generalizable, and interpretable simulations of E. coli by leveraging recent innovations across two broad domains: (1) high-throughput and automated experimental test beds; (2) advanced computational techniques.
“The program seeks to dramatically accelerate progress towards a fully resolved computational model of E. coli, one of the most widely studied organisms in biology,” stated Dr. Christopher Bettinger, SMS program manager. “This program will bring to bear advances in physics-based computation that is parameterized using newly acquired data generated from high-throughput experiments. The result will be a comprehensive and extensive software package that will, in the future, help our DoD stakeholders design and execute microbiology experiments on a computer rather than in a laboratory.”
“There have been dramatic advances in applying neural networks and other techniques to simulate the dynamics of complex and uncertain systems in domains such as fluid mechanics, materials behavior, and combustion chemistry. SMS seeks to build on these innovations to forecast the dynamics of a complex biological system: E. coli bacterium,” added Bettinger.
SMS seeks interdisciplinary, comprehensive, and integrated workflows to generate unknown parameters from new data to inform computational models that can predict E. coli. SMS ultimately envisions unified experimental and computational workflows that can jointly address simulation development and data acquisition/curation. Wet lab microbiology and analytical experiments should consider software architecture, physics-based modeling, and analytical techniques as they generate and curate data. Similarly, simulation development should both leverage acquired data and inform future experiments. The output of the program will be a software package that can simulate E. coli behavior across many length scales.
The SMS program will include an ethical, legal, and societal implications (ELSI) plan to include discussions regarding human use of the technology following its development.
Information is available on the upcoming SMS Industry Day on SAM.gov.