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中文摘要
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摘要 微尺度模拟已经被应用于许多复杂的微流体系统和生物系统。 虽然现有的方法在可解决的问题的规模和范围上是有限的。 热力学约束平均理论(TCAT)是一种已建立的方法,可用于 制定与微观物理学和热力学一致的定制宏观模型。 TCAT建模框架已经开发、评估和验证,用于广泛的应用 涉及流体和固相,在该项目的第一阶段,Redbud Labs的可致动后技术 格里菲斯和米勒实验室在 位于查佩尔山的北卡罗来纳州大学在微观和宏观尺度上的研究。这将使未来在 这些微流控系统用于床旁诊断(POC Dx)的计算机优化 在第二阶段研究中,我们将扩展第一阶段开发的模型,以包括相关的情景。 广泛的分子诊断,包括那些脱靶物种丰富和目标 物种非常罕见。此外,第二阶段模型将包括相关的生物基质,如全 血液血浆和唾液开发的计算模型将用于优化高影响力 用于HIV、SARS-CoV-2、癌症检测(液体活检)和败血症的纯化/诊断测定。最后 优化的组件将被移植到Redbud Labs现有的样品制备平台NAextract, 仅用于研究应用。
英文摘要
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.
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Enhanced MDx: a computational model to optimize pre-analytical pathogen isolation from whole blood
  • 批准号:
    10484641
  • 项目类别:
  • 资助金额:
    $99.97万
  • 财政年份:
    2020
  • 负责人:
    Cass T Miller
  • 依托单位:
Enhanced MDx: a computational model to optimize pre-analytical pathogen isolation from whole blood.
  • 批准号:
    9909760
  • 项目类别:
  • 资助金额:
    $29.7万
  • 财政年份:
    2020
  • 负责人:
    Cass T Miller
  • 依托单位:
Core--Mathematical and Statistical Analysis
Enhanced Remediation of Heterogeneous Subsurface Systems
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