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.