Synthetic microfluidic microvasculature networks
Inventors
Prabhakarpandian, Balabhaskar • Sundaram, Shivshankar • Pant, Kapil
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Assignees
MemberSynVivoSynVivoSynVivo is a pioneering provider of cell-based microfluidic organ-on-chip platforms, delivering biologically realistic microenvironments for real-time study of cellular behavior, drug delivery, and drug discovery. Their proprietary technology bridges microfluidics and bioengineering, enabling advanced research in life sciences, disease modeling, and personalized medicine. SynVivo's chips support microvascular networks that closely mimic in vivo tissue conditions, validated by scientific research to more accurately reflect human biology than conventional culture methods. The platform is especially impactful for personalized cancer therapy, allowing patient-derived cells to be used for drug efficacy testing in a simulated tumor environment. SynVivo also distributes a wide range of high-quality primary cells and cell lines from various species, supporting research in immunology, cardiovascular, and cancer biology.
SynVivo is a pioneering provider of cell-based microfluidic organ-on-chip platforms, delivering biologically realistic microenvironments for real-time study of cellular behavior, drug delivery, and drug discovery. Their proprietary technology bridges microfluidics and bioengineering, enabling advanced research in life sciences, disease modeling, and personalized medicine. SynVivo's chips support microvascular networks that closely mimic in vivo tissue conditions, validated by scientific research to more accurately reflect human biology than conventional culture methods. The platform is especially impactful for personalized cancer therapy, allowing patient-derived cells to be used for drug efficacy testing in a simulated tumor environment. SynVivo also distributes a wide range of high-quality primary cells and cell lines from various species, supporting research in immunology, cardiovascular, and cancer biology.
Publication Number
US-8589083-B2
Publication Date
2013-11-19
Expiration Date
Abstract
A synthetic microfluidic microvasculature network and associated methods mimic the structure, fluid flow characteristics, and physiological behavior of physiological microvasculature networks. Computational methods for simulating flow and particle adherence in synthetic and physiological microvascular systems and methods for determining parameters influencing particle adhesion and drug delivery are described with applications in the optimization of drug delivery and microvascular treatments and in describing disease mechanisms that affect the microvasculature.
Core Innovation
The invention provides synthetic microfluidic microvasculature networks (SMNs) and associated methods that mimic the structure, fluid flow characteristics, and physiological behavior of physiological microvasculature networks. Computational methods for simulating flow and particle adherence in synthetic and physiological microvascular systems and methods for determining parameters influencing particle adhesion and drug delivery are described.
The invention addresses the lack of an in-vitro flow chamber that accurately simulates the anatomical and hemodynamic properties of physiological microvascular networks. Existing in-vitro flow chambers are described as having linear channels with constant cross sections and dimensions larger than physiological microvessels and lacking the geometric variations, interconnectedness, and flow patterns found in in-vivo microcirculation, and the invention provides apparatus and methods to reproduce and predict adhesion patterns and numbers of adhered particles in microvascular networks.
Claims Coverage
The patent includes one independent claim. The independent claim recites a computer-implemented method that (a) creates a computational mesh representing geometric features and connectivity of a microvascular network, (b) specifies fluid flow/pressure conditions at inlets and outlets, and (c) solves for flow velocities and pressures using one or more mathematical models.
Computational simulation implemented on a computer-readable medium
A method for computationally simulating fluid flow through a microvascular network implemented on a computer having a physical computer-readable medium having computer-executable instructions thereon that when executed by the computer implement the steps of the method.
Computational mesh representing geometric features and connectivity
Creating a computational mesh representing the geometric features and connectivity of the microvascular network to generate a computational microvascular network, the computational microvascular network being selected from a physiological microvascular network, a synthetic microvascular network, and an averaged microvascular network.
Specification of inlet and outlet fluid flow/pressure conditions
Specifying fluid flow/pressure conditions at the one or more inlets and one or more outlets.
Solving for flow velocities and pressures using mathematical models
Solving for flow velocities and pressures using one or more mathematical models.
The independent claim covers a computer-implemented CFD workflow for microvascular networks that includes generating a geometric computational mesh for physiological, synthetic, or averaged networks, applying inlet/outlet flow or pressure conditions, and computing flow velocities and pressures via mathematical models.
Stated Advantages
Mimics the structure, fluid flow characteristics, and physiological behavior of physiological microvasculature networks.
Enables optimization of drug delivery and microvascular treatments.
Describes and predicts behavior of particles and cells in microvascular networks, including particle adhesion patterns and numbers of adhered particles.
Provides an anatomically realistic in-vitro/in-silico toolkit to study microvascular processes such as leukocyte adhesion, platelet adhesion, inflammation, chemotaxis, thrombosis, vascular activation, and effects of shear rate on vascular endothelial cells.
Allows extraction of predictive relationships between parameters such as flow rate, particle size, receptor density, and network geometry.
Documented Applications
Optimization of drug delivery and microvascular treatments.
Describing disease mechanisms that affect the microvasculature such as inflammation, diabetes and hypertension.
Studying microvascular processes including leukocyte adhesion, platelet adhesion, inflammation, chemotaxis, thrombosis, vascular activation, and the effects of shear rate on vascular endothelial cells.
Using SMNs and computational models to reproduce and predict fluid flow, dye perfusion, particle transport, and particle adhesion in microvascular networks for experimental validation and analysis.
Screening materials and methods for optimal drug delivery to healthy and diseased microvasculature and screening targeting molecules using SMNs coated with target cells.
Generating averaged or nominal microvascular networks derived from combinations of physiological networks for use in simulation and study.
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