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Challenges 3 & 4: Fusing data, processes and mechanisms across scales

Challenges 3 & 4: Fusing data, processes and mechanisms across scales. Jeffrey Holmes, U. Virginia Michael Henson, UMass Amherst Ross Carlson, Montana State U. David Zawieja, Texas A&M. Background. Challenge group 3: fusing data-rich and data-poor scales

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Challenges 3 & 4: Fusing data, processes and mechanisms across scales

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  1. Challenges 3 & 4: Fusing data, processes and mechanisms across scales Jeffrey Holmes, U. Virginia Michael Henson, UMass Amherst Ross Carlson, Montana State U. David Zawieja, Texas A&M

  2. Background • Challenge group 3: fusing data-rich and data-poor scales • PI leads: Mike Henson & David Zawieja • NIH POCs: Beth Lewandowski & Donna Lochner • Challenge group 4: fusing biological and behavioral processes as a result of interventions • PI leads: Jeffrey Holmes & Ross Carlson • NIH POCs: Wen Chen & Xujing Wang • Held joint Webex meeting on February 26 with email follow-up • Distilled verbal and written input into three areas: success stories, exciting developments, future challenges

  3. Success 1: Agent-based models • Over the past decade, ABMs have spread through the MSM community. • This approach is proving particularly useful for bridging data-rich and data-poor scales (e.g. cultured cells > in vivo tissues/organs). publications/year

  4. Success 2: Genome-scale metabolic models • Genome-scale metabolic models of microbes span genes, pathways and whole-species metabolism. • These multiscale models are being used industrially to guide cell engineering for biochemical production. • Commercial products • 1-3 propanediol • 1-4 butanediol

  5. Development 1: Patient-specific models • FDA-approved PSMs are now in clinical use for diagnosing CV disease.1,2 • Simulated or ‘virtual’ patient are being employed in regulatory filings.3 • MSM PIs have helped drive discussions on model V&V, an essential aspect of clinical applications. 1www.heartflow.com; 2http://www.medtronic.com/us-en/healthcare-professionals/products/cardiac-rhythm/cardiac-mapping/cardioinsight-mapping-vest.html; 3https://www.ncbi.nlm.nih.gov/pubmed/29305798

  6. Development 2: Cellular Signaling Models • Models of intracellular signaling networks are providing simulations with direct relevance to drug discovery and testing. • Integration of these models into MSMs are enabling prediction of whole-cell and multi-cell responses in complex contexts. PMC5314181 PMC4861657

  7. Future Challenges • Modeling approaches that reduce overparameterizationand improve parameter identifiability • Obtaining the quantitative data needed to determine parameters and verify coupling across scales • Establishing multidisciplinary teams with clinicians and experimentalists to facilitate model development & adoption • We propose that these issues be addressed explicitly in the next MSM U01 CFP, moving from building to using MSMs.

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