Federal grant · project grant (b)
Enhanced MDX: a Computational Model to Optimize Pre-analytical Pathogen Isolation From Whole Blood - Abstract Microscale Simulations Have Been Applied to a Number of Complex Microfluidic Systems and Biological Applications, But Existing Methods Are Limited in the Scale and Scope of Problems That Are Addressable. Thermodynamically Constrained Averaging Theory (TCAT) Is an Established Approach That Can Be Used to Formulate Customized Macroscale Models That Are Consistent With Microscale Physics and Thermodynamics. Tcat Modeling Frameworks Have Been Developed, Evaluated, and Validated for a Wide Range of Applications Involving Fluid and Solid Phases, and in Phase I of This Project, Redbud Labs’ Actuatable Post Technology Enabling Rapid Target Isolation and Concentration Was Successfully Modeled by the Griffith and Miller Labs at the University of North Carolina at Chapel Hill at Both the Micro and Macroscale. This Will Enable Future in Silico Optimization of These Microfluidic Systems for Use in Point of Care Diagnostic (poc DX) in This Phase Ii Study, We Will Expand Upon the Models Developed in Phase I to Include Scenarios Relevant to a Broad Group of Molecular Diagnostics, Including Those Where Off Target Species Are Plentiful and Target Species Are Exceedingly Rare. in Addition, Phase Ii Models Will Include Relevant Biological Matrices Such as Whole Blood, Plasma, and Saliva. the Developed Computational Model Will Then Be Used to Optimize High-impact Purification/diagnostic Assays for Hiv, SARS-COV-2, Cancer Detection (liquid Biopsy), and Sepsis. Finally, the Optimized Components Will Be Ported to Redbud Labs’ Existing Sample Prep Platform, Naxtract, and Made Available for Research Use Only Applications.
Committed
$2.0 Million
Paid out
$1.9M
98%
Committed, not yet paid
$42.0K
2%
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