Design Software for Application-Specific Microfluidic Devices

Bedekar, A.S.; Wang, Yi; Siddhaye, Sachin S.; Krishnamoorthy, S.; Malin, Stephen F.

doi:10.1373/clinchem.2007.090498

Cited by 4 publications

(2 citation statements)

References 10 publications

(1 reference statement)

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“…Similarly, chip geometry constitutes a major factor in providing a physiologically-relevant environment amenable to sampling. While most Organs-on-Chips currently published feature rather simple flow circuits serving mostly perfusion and gas exchange, more sophisticated scenarios containing in-flow sensors and drug dispensers could be designed with the help of design and simulation software, as is routinely done for microfluidics applications [275]. However, introducing complex fluidic microchannel networks may increase bubble formation which could in turn damage cultures through shear forces and cells drying out when bubbles block medium perfusion.…”

Section: Hardware/materialsmentioning

confidence: 99%

Stem cell-based Lung-on-Chips: The best of both worlds?

Nawroth

Barrile

Conegliano

et al. 2019

Advanced Drug Delivery Reviews

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Pathologies of the respiratory system such as lung infections, chronic inflammatory lung diseases, and lung cancer are among the leading causes of morbidity and mortality, killing one in six people worldwide. Development of more effective treatments is hindered by the lack of preclinical models of the human lung that can capture the disease complexity, highly heterogeneous disease phenotypes, and pharmacokinetics and pharmacodynamics observed in patients. The merger of two novel technologies, Organs-on-Chips and human stem cell engineering, has the potential to deliver such urgently needed models. Organs-on-Chips, which are microengineered bioinspired tissue systems, recapitulate the mechanochemical environment and physiological functions of human organs while concurrent advances in generating and differentiating human stem cells promise a renewable supply of patient-specific cells for personalized and precision medicine. Here, we discuss the challenges of modeling human lung pathophysiology in vitro, evaluate past and current models including Organs-on-Chips, review the current status of lung tissue modeling using human pluripotent stem cells, explore in depth how stem-cell based Lung-on-Chips may advance disease modeling and drug testing, and summarize practical consideration for the design of Lung-on-Chips for academic and industry applications.

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Section: Hardware/materialsmentioning

confidence: 99%

Stem cell-based Lung-on-Chips: The best of both worlds?

Nawroth

Barrile

Conegliano

et al. 2019

Advanced Drug Delivery Reviews

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“…Future efforts to improve the existing simulation capability will focus on two aspects: model extension to account for dynamics of the isolated gas phase ͑such as air bubble trapping and propagation͒ and integration of the model with our systemlevel microfluidic design tool-Pharos. 24 …”

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confidence: 99%

System-level simulation of liquid filling in microfluidic chips

2011

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Liquid filling in microfluidic channels is a complex process that depends on a variety of geometric, operating, and material parameters such as microchannel geometry, flow velocity/pressure, liquid surface tension, and contact angle of channel surface. Accurate analysis of the filling process can provide key insights into the filling time, air bubble trapping, and dead zone formation, and help evaluate tradeoffs among the various design parameters and lead to optimal chip design. However, efficient modeling of liquid filling in complex microfluidic networks continues to be a significant challenge. High-fidelity computational methods, such as the volume of fluid method, are prohibitively expensive from a computational standpoint. Analytical models, on the other hand, are primarily applicable to idealized geometries and, hence, are unable to accurately capture chip level behavior of complex microfluidic systems. This paper presents a parametrized dynamic model for the system-level analysis of liquid filling in three-dimensional ͑3D͒ microfluidic networks. In our approach, a complex microfluidic network is deconstructed into a set of commonly used components, such as reservoirs, microchannels, and junctions. The components are then assembled according to their spatial layout and operating rationale to achieve a rapid system-level model. A dynamic model based on the transient momentum equation is developed to track the liquid front in the microchannels. The principle of mass conservation at the junction is used to link the fluidic parameters in the microchannels emanating from the junction. Assembly of these component models yields a set of differential and algebraic equations, which upon integration provides temporal information of the liquid filling process, particularly liquid front propagation ͑i.e., the arrival time͒. The models are used to simulate the transient liquid filling process in a variety of microfluidic constructs and in a multiplexer, representing a complex microfluidic network. The accuracy ͑relative error less than 7%͒ and orders-of-magnitude speedup ͑30 000X-4 000 000X͒ of our system-level models are verified by comparison against 3D high-fidelity numerical studies. Our findings clearly establish the utility of our models and simulation methodology for fast, reliable analysis of liquid filling to guide the design optimization of complex microfluidic networks.

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Review on macromodels of MEMS sensors and actuators

Chen

2017

Microsyst Technol

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Design Software for Application-Specific Microfluidic Devices

Cited by 4 publications

References 10 publications

Stem cell-based Lung-on-Chips: The best of both worlds?

Stem cell-based Lung-on-Chips: The best of both worlds?

System-level simulation of liquid filling in microfluidic chips

Review on macromodels of MEMS sensors and actuators

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