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Integrated Multilayer Microfluidic Platforms with Silicon Architectures for Next-Generation Health Diagnostic Systems

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Abstract

Majority of research on lab-on-chip devices was on single layer devices. Stacking a combination of microfluidic layers to silicon architecture gives substantial advantage to integrate precise sensors, actuators, and control systems. Advantages of multilayer stack are: (i) multiple functions can be incorporated into single chip and (ii) simultaneous analysis of both macroscopic and microscopic properties, for example, characterizing blood as a bulk fluid and at the individual component level at the same time. Such integrated systems enable the applications that lead to development of comprehensive diagnostics system. Challenges for developing such devices are integrating multiple layers – a combination of biocompatible microfluidics and silicon architectures; individual automated systems that incorporate sensors, actuators, and control systems; development of rapid data analysis and management; and development of diagnostic metrics to manipulate the actuators based on the responses (feedback control). This chapter reviews existing literature and techniques to address the above challenges through the prospect of a state-of-the-art silicon integrated lab-on-chip device with advanced automation coupled with novel data analysis tools to address critical applications in healthcare.

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References

  1. Casadevall i Solvas X, deMello A (2011) Droplet microfluidics: recent developments and future applications. Chem Commun 47:1936–1942

    Article  CAS  Google Scholar 

  2. Chou W-L, Lee P-Y, Yang C-L et al (2015) Recent advances in applications of droplet microfluidics. Micromachines 6:1249–1271

    Article  Google Scholar 

  3. Teh S-Y, Lin R, Hung L-H, Lee AP (2008) Droplet microfluidics. Lab Chip 8:198

    Article  CAS  Google Scholar 

  4. Paguirigan AL, Beebe DJ (2008) Microfluidics meet cell biology: bridging the gap by validation and application of microscale techniques for cell biological assays. BioEssays 30:811–821

    Article  CAS  Google Scholar 

  5. Song H, Chen DL, Ismagilov RF (2006) Reactions in droplets in microfluidic channels. Angew Chem Int Ed Engl 45:7336–7356

    Article  CAS  Google Scholar 

  6. Jamal S, Agrawal YK (2013) Advances in microfluidics: lab-on-a-chip to point of care diagnostic devices. Adv Sci, Eng Med 5:385–394

    Article  CAS  Google Scholar 

  7. Zilberman-Rudenko J, Sylman JL, Lakshmanan HHS et al (2016) Dynamics of blood flow and thrombus formation in a multi-bypass microfluidic ladder network. Cell Mol Bioeng 10:16–29

    Article  CAS  Google Scholar 

  8. Zilberman-Rudenko J, White RM, Zilberman DA et al (2018) Design and utility of a point-of-care microfluidic platform to assess hematocrit and blood coagulation. Cell Mol Bioeng 11:519–529

    Article  CAS  Google Scholar 

  9. Maddala J, Rengaswamy R (2013) Droplet digital signal generation in microfluidic networks using model predictive control. J Process Control 23:132–139

    Article  CAS  Google Scholar 

  10. Kuswandi B, Nuriman, Huskens J, Verboom W (2007) Optical sensing systems for microfluidic devices: a review. Anal Chim Acta 601:141–155

    Article  CAS  Google Scholar 

  11. Ahn K, Kerbage C, Hunt TP et al (2006) Dielectrophoretic manipulation of drops for high-speed microfluidic sorting devices. Appl Phys Lett 88:024104

    Article  CAS  Google Scholar 

  12. Dittrich PS, Schwille P (2003) An integrated microfluidic system for reaction, high-sensitivity detection, and sorting of fluorescent cells and particles. Anal Chem 75:5767–5774

    Article  CAS  Google Scholar 

  13. Chen CH, Cho SH, Tsai F et al (2009) Microfluidic cell sorter with integrated piezoelectric actuator. Biomed Microdevices 11:1223–1231

    Article  CAS  Google Scholar 

  14. Han Z, Li W, Huang Y, Zheng B (2009) Measuring rapid enzymatic kinetics by electrochemical method in droplet-based microfluidic devices with pneumatic valves. Anal Chem 81:5840–5845

    Article  CAS  Google Scholar 

  15. Suea-Ngam A, Rattanarat P, Chailapakul O, Srisa-Art M (2015) Electrochemical droplet-based microfluidics using chip-based carbon paste electrodes for high-throughput analysis in pharmaceutical applications. Anal Chim Acta 883:45–54

    Article  CAS  Google Scholar 

  16. Pollack MG, Shenderov AD, Fair RB (2002) Electrowetting-based actuation of droplets for integrated microfluidics. Lab Chip 2:96–101

    Article  CAS  Google Scholar 

  17. Link DR, Grasland-Mongrain E, Duri A et al (2006) Electric control of droplets in microfluidic devices. Angew Chem Int Ed Engl 45:2556–2560

    Article  CAS  Google Scholar 

  18. Bransky A, Korin N, Khoury M, Levenberg S (2009) A microfluidic droplet generator based on a piezoelectric actuator. Lab Chip 9:516–520

    Article  CAS  Google Scholar 

  19. Cao Z, Chen F, Bao N et al (2013) Droplet sorting based on the number of encapsulated particles using a solenoid valve. Lab Chip 13:171–178

    Article  CAS  Google Scholar 

  20. Cho SH, Chen CH, Tsai FS et al (2010) Human mammalian cell sorting using a highly integrated micro-fabricated fluorescence-activated cell sorter (μFACS). Lab Chip 10:1567

    Article  CAS  Google Scholar 

  21. Wang MM, Tu E, Raymond DE et al (2005) Microfluidic sorting of mammalian cells by optical force switching. Nat Biotechnol 23:83–87

    Article  CAS  Google Scholar 

  22. Lignos I, Protesescu L, Stavrakis S et al (2014) Facile droplet-based microfluidic synthesis of monodisperse IV–VI semiconductor nanocrystals with coupled in-line NIR fluorescence detection. Chem Mater 26:2975–2982

    Article  CAS  Google Scholar 

  23. Krishnadasan S, Brown RJC, deMello AJ, deMello JC (2007) Intelligent routes to the controlled synthesis of nanoparticles. Lab Chip 7:1434–1441

    Article  CAS  Google Scholar 

  24. Maceiczyk RM, deMello AJ (2014) Fast and reliable metamodeling of complex reaction spaces using universal kriging. J Phys Chem C 118:20026–20033

    Article  CAS  Google Scholar 

  25. Maceiczyk RM, Lignos IG, deMello AJ (2015) Online detection and automation methods in microfluidic nanomaterial synthesis. Curr Opin Chem Eng 8:29–35

    Article  Google Scholar 

  26. Fu AY, Chou H-P, Spence C et al (2002) An integrated microfabricated cell sorter. Anal Chem 74:2451–2457

    Article  CAS  Google Scholar 

  27. Abate AR, Weitz DA (2008) Single-layer membrane valves for elastomeric microfluidic devices. Appl Phys Lett 92:243509

    Article  CAS  Google Scholar 

  28. Zeng S, Li B, X’ou S et al (2009) Microvalve-actuated precise control of individual droplets in microfluidic devices. Lab Chip 9:1340–1343

    Article  CAS  Google Scholar 

  29. Lee H, Lee H, Liu Y et al (2005) An IC/microfluidic hybrid microsystem for 2D magnetic manipulation of individual biological cells. In: ISSCC. 2005 IEEE international digest of technical papers. Solid-state circuits conference

    Google Scholar 

  30. Zhang K, Liang Q, Ai X et al (2011) On-demand microfluidic droplet manipulation using hydrophobic ferrofluid as a continuous-phase. Lab Chip 11:1271–1275

    Article  CAS  Google Scholar 

  31. Duffy DC, McDonald JC, Schueller OJ, Whitesides GM (1998) Rapid prototyping of microfluidic systems in poly(dimethylsiloxane). Anal Chem 70:4974–4984

    Article  CAS  Google Scholar 

  32. Unger MA, Chou HP, Thorsen T et al (2000) Monolithic microfabricated valves and pumps by multilayer soft lithography. Science 288:113–116

    Article  CAS  Google Scholar 

  33. Guo Z-X, Zeng Q, Zhang M et al (2011) Valve-based microfluidic droplet micromixer and mercury (II) ion detection. Sens Actuators A Phys 172:546–551

    Article  CAS  Google Scholar 

  34. Schindler M, Ajdari A (2008) Droplet traffic in microfluidic networks: a simple model for understanding and designing. Phys Rev Lett 100:044501

    Article  CAS  Google Scholar 

  35. An F, Qu Y, Liu X et al (2015) Organ-on-a-chip: new platform for biological analysis. Anal Chem Insights 10:39–45

    Article  CAS  Google Scholar 

  36. Stieger B (2016) Faculty of 1000 evaluation for organ-on-a-chip: new platform for biological analysis. F1000 – Post-publication peer review of the biomedical literature

    Google Scholar 

  37. Glick C, Schwartz A, Srimongkol M et al (2018) Rapid assembly of multilayer microfluidic structures. In: 2018 IEEE micro electro mechanical systems (MEMS)

    Google Scholar 

  38. Glick CC, Srimongkol MT, Schwartz AJ et al (2016) Rapid assembly of multilayer microfluidic structures via 3D-printed transfer molding and bonding. Microsyst Nanoeng 2:16063. https://doi.org/10.1038/micronano.2016.63

    Article  CAS  Google Scholar 

  39. Saharil F, Carlborg CF, Haraldsson T, van der Wijngaart W (2012) Biocompatible “click” wafer bonding for microfluidic devices. Lab Chip 12:3032

    Article  CAS  Google Scholar 

  40. Chen X, Zhang L, Li H et al (2013) Development of a multilayer microfluidic device integrated with a PDMS-cellulose composite film for sample pre-treatment and immunoassay. Sens Actuators A Phys 193:54–58

    Article  CAS  Google Scholar 

  41. Tsai L-F (2011) Bonding of polydimethylsiloxane microfluidics to silicon-based sensors. J Micro/Nanolithogr MEMS MOEMS 10:043009

    Article  CAS  Google Scholar 

  42. Iliescu C, Taylor H, Avram M et al (2012) A practical guide for the fabrication of microfluidic devices using glass and silicon. Biomicrofluidics 6:016505

    Article  CAS  Google Scholar 

  43. Tsybeskov L, Hirschman KD, Duttagupta SP, Fauchet PM. An LED for silicon-based integrated optoelectronics. In: 1996 54th annual device research conference digest

    Google Scholar 

  44. Su Y (2012) All-optical signal processing using integrated silicon photonic devices. In: 2012 11th international conference on information science, signal processing and their applications (ISSPA)

    Google Scholar 

  45. Gong J, Kim C-JCJ (2008) All-electronic droplet generation on-chip with real-time feedback control for EWOD digital microfluidics. Lab Chip 8:898–906

    Article  CAS  Google Scholar 

  46. Fair RB, Pollack MG, Woo R et al. A micro-watt metal-insulator-solution-transport (MIST) device for scalable digital bio-microfluidic systems. In: International electron devices meeting. Technical digest (Cat. No.01CH37224)

    Google Scholar 

  47. Maddala J, Vanapalli SA, Rengaswamy R (2011) Sort-synchronization control in microfluidic loop devices with experimental uncertainties using a model predictive control (MPC) framework. IFAC Proc Vol 44:4886–4891

    Article  Google Scholar 

  48. Abe Y, Takemura K, Sato K et al (2013) Droplet μTAS using electro-conjugate fluid – feedback position control of multiple droplets in flow channel matrix. Sens Actuators A Phys 198:1–7

    Article  CAS  Google Scholar 

  49. Chung Y-C, Wen B-J, Lin Y-C (2007) Optimal fuzzy sliding-mode control for bio-microfluidic manipulation. Control Eng Pract 15:1093–1105

    Article  Google Scholar 

  50. Lin C-J, Lin C-J, Chen Y-Y, Hang F-R. Fuzzy processing on GPS data to improve the position accuracy. In: Soft computing in intelligent systems and information processing. Proceedings of the 1996 Asian fuzzy systems symposium

    Google Scholar 

  51. Zhang G, Lu J, Gao Y (2015) Fuzzy bi-level decision making. In: Multi-Level Decision Making. Intelligent systems reference library, vol 82. Springer, Berlin, Heidelberg, pp 175–205

    Google Scholar 

  52. Maddala J, Rengaswamy R (2014) Design of multi-functional microfluidic ladder networks to passively control droplet spacing using genetic algorithms. Comput Chem Eng 60:413–425

    Article  CAS  Google Scholar 

  53. Maddala J, Wang WS, Vanapalli SA, Rengaswamy R (2012) Traffic of pairs of drops in microfluidic ladder networks with fore-aft structural asymmetry. Microfluid Nanofluidics 14:337–344

    Article  Google Scholar 

  54. Kasule JS, Maddala J, Mobed P, Rengaswamy R (2016) Very large scale droplet microfluidic integration (VLDMI) using genetic algorithm. Comput Chem Eng 85:94–104

    Article  CAS  Google Scholar 

  55. Mohammed M-I, Desmulliez MPY (2011) Lab-on-a-chip based immunosensor principles and technologies for the detection of cardiac biomarkers: a review. Lab Chip 11:569–595

    Article  CAS  Google Scholar 

  56. Alix-Panabières C, Pantel K (2014) Technologies for detection of circulating tumor cells: facts and vision. Lab Chip 14:57–62

    Article  Google Scholar 

  57. Uttley L, Whiteman BL, Woods HB et al (2016) Building the evidence base of blood-based biomarkers for early detection of cancer: a rapid systematic mapping review. EBioMedicine 10:164–173

    Article  Google Scholar 

  58. Mazumder R (2015) Blood-based companion diagnostics. The journal of precision medicine

    Google Scholar 

  59. Kasukurti A, Eggleton CD, Desai SA, Marr DWM (2015) FACS-style detection for real-time cell viscoelastic cytometry. RSC Adv 5:105636–105642

    Article  CAS  Google Scholar 

  60. Yaghobian F, Weimann T, Güttler B, Stosch R (2011) On-chip approach for traceable quantification of biomarkers based on isotope-dilution surface-enhanced Raman scattering (IDSERS). Lab Chip 11:2955

    Article  CAS  Google Scholar 

  61. Wu J, Gu M (2011) Microfluidic sensing: state of the art fabrication and detection techniques. J Biomed Opt 16:080901

    Article  Google Scholar 

  62. Zhu Y, Fang Q (2013) Analytical detection techniques for droplet microfluidics – a review. Anal Chim Acta 787:24–35

    Article  CAS  Google Scholar 

  63. Cole MC, Kenis PJA (2009) Multiplexed electrical sensor arrays in microfluidic networks. Sens Actuators B Chem 136:350–358

    Article  CAS  Google Scholar 

  64. Petchakup C, Li K, Hou H (2017) Advances in single cell impedance cytometry for biomedical applications. Micromachines 8:87

    Article  Google Scholar 

  65. Holmes D, Morgan H (2010) Single cell impedance cytometry for identification and counting of CD4 T-cells in human blood using impedance labels. Anal Chem 82:1455–1461

    Article  CAS  Google Scholar 

  66. Claudel J, Nadi M, El Mazria O, Kourtiche D (2017) High reliability microfluidic biosensor for single cell impedance cytometry. In: 2017 eleventh international conference on sensing technology (ICST)

    Google Scholar 

  67. Morgan H, Spencer D (2015) Microfluidic impedance cytometry for blood cell analysis. RSC Nanoscience and Nanotechnology. pp 213–241

    Google Scholar 

  68. Simini F, Bertemes-Filho P (2018) Bioimpedance in biomedical applications and research. Springer, Cham

    Book  Google Scholar 

  69. Chen J, Xue C, Zhao Y et al (2015) Microfluidic impedance flow cytometry enabling high-throughput single-cell electrical property characterization. Int J Mol Sci 16:9804–9830

    Article  CAS  Google Scholar 

  70. Iacovacci V, Lucarini G, Ricotti L, Menciassi A (2016) Magnetic field-based technologies for lab-on-a-chip applications. In: Lab-on-a-chip fabrication and application, IntechOpen. https://doi.org/10.5772/62865

    Google Scholar 

  71. Yang S, Ündar A, Zahn J (2005) Biological fluid separation in microfluidic channels using flow rate control. American society of mechanical engineers, fluids engineering division (Publication) FED. 261. https://doi.org/10.1115/IMECE2005-80501

  72. Stoecklein D, Wu C-Y, Owsley K et al (2014) Micropillar sequence designs for fundamental inertial flow transformations. Lab Chip 14:4197–4204

    Article  CAS  Google Scholar 

  73. Dutta D (2013) Enhanced microfluidic separation by pressure-driven flow. Encyclopedia of microfluidics and nanofluidics, pp 1–13. https://doi.org/10.1007/978-3-642-27758-0_1747-1

    Google Scholar 

  74. Raj A, Suthanthiraraj PPA, Sen AK (2018) Pressure-driven flow through PDMS-based flexible microchannels and their applications in microfluidics. Microfluid Nanofluidics 22. https://doi.org/10.1007/s10404-018-2150-5

  75. Lewpiriyawong N, Yang C (2014) Dielectrophoresis field-flow fractionation for continuous-flow separation of particles and cells in microfluidic devices. In: Wang L. (ed) Advances in transport phenomena 2011. Advances in transport phenomena, vol 3. Springer, Cham. pp 29–62

    Google Scholar 

  76. Modak N, Datta A, Ganguly R (2008) Cell separation in a microfluidic channel using magnetic microspheres. Microfluid Nanofluidics 6:647–660

    Article  CAS  Google Scholar 

  77. Shields CW 4th, Ohiri KA, Szott LM, López GP (2017) Translating microfluidics: cell separation technologies and their barriers to commercialization. Cytometry B Clin Cytom 92:115–125

    Article  Google Scholar 

  78. Buican TN (1991) Automated cell separation techniques based on optical trapping. In: ACS symposium series. pp 59–72

    Google Scholar 

  79. Grover SC, Skirtach AG, Gauthier RC, Grover CP (2001) Automated single-cell sorting system based on optical trapping. J Biomed Opt 6:14–22

    Article  CAS  Google Scholar 

  80. Applegate RW Jr, Squier J, Vestad T et al (2006) Microfluidic sorting system based on optical waveguide integration and diode laser bar trapping. Lab Chip 6:422–426

    Article  CAS  Google Scholar 

  81. Applegate R Jr, Squier J, Vestad T et al (2004) Optical trapping, manipulation, and sorting of cells and colloids in microfluidic systems with diode laser bars. Opt Express 12:4390–4398

    Article  Google Scholar 

  82. Kasukurti A, Potcoava M, Desai SA et al (2011) Single-cell isolation using a DVD optical pickup. Opt Express 19:10377

    Article  CAS  Google Scholar 

  83. Dholakia K, MacDonald MP, Zemánek P, Cizmár T (2007) Cellular and colloidal separation using optical forces. Methods Cell Biol 82:467–495

    Article  CAS  Google Scholar 

  84. Sun Y, Haglund TA, Rogers AJ et al (2018) Review: microfluidics technologies for blood-based cancer liquid biopsies. Anal Chim Acta 1012:10–29

    Article  CAS  Google Scholar 

  85. Bogue R (2016) Lab-on-a-chip and other miniaturised analytical instruments. Sens Rev 36:109–114

    Article  Google Scholar 

  86. Chen L, Bode AM, Dong Z (2017) Circulating tumor cells: moving biological insights into detection. Theranostics 7:2606–2619

    Article  CAS  Google Scholar 

  87. Liu J, Qiang Y, Alvarez O, Du E (2018) Electrical impedance microflow cytometry with oxygen control for detection of sickle cells. Sens Actuators B Chem 255:2392–2398

    Article  CAS  Google Scholar 

  88. Swensen JS, Xiao Y, Ferguson BS et al (2009) Continuous, real-time monitoring of cocaine in undiluted blood serum via a microfluidic, electrochemical aptamer-based sensor. J Am Chem Soc 131:4262–4266

    Article  CAS  Google Scholar 

  89. Song H, Li H-W, Munson MS et al (2006) On-chip titration of an anticoagulant argatroban and determination of the clotting time within whole blood or plasma using a plug-based microfluidic system. Anal Chem 78:4839–4849

    Article  CAS  Google Scholar 

  90. Wolff A, Perch-Nielsen IR, Larsen UD et al (2003) Integrating advanced functionality in a microfabricated high-throughput fluorescent-activated cell sorter. Lab Chip 3:22

    Article  CAS  Google Scholar 

  91. Chen Y, Wu T-H, Chung A et al (2014) Pulsed laser activated cell sorter (PLACS) for high-throughput fluorescent mammalian cell sorting. Proceedings of SPIE – The international society for optical engineering. 9164. https://doi.org/10.1117/12.2060914

  92. Chandrasekaran A, Packirisamy M (2010) Integrated microfluidic biophotonic chip for laser induced fluorescence detection. Biomed Microdevices 12:923–933

    Article  Google Scholar 

  93. Lee H, Xu L, Koh D et al (2014) Various on-chip sensors with microfluidics for biological applications. Sensors 14:17008–17036

    Article  CAS  Google Scholar 

  94. Tokel O, Yildiz UH, Inci F et al (2015) Portable microfluidic integrated plasmonic platform for pathogen detection. Sci Rep 5:9152

    Article  CAS  Google Scholar 

  95. Berchtold C, Bosilkovska M, Daali Y et al (2013) Real-time monitoring of exhaled drugs by mass spectrometry. Mass Spectrom Rev 33:394–413

    Article  CAS  Google Scholar 

  96. Freire S, Wheeler A (2008) Interfaces between microfluidics and mass spectrometry. In: Li D (ed) Encyclopedia of microfluidics and nanofluidics. Springer, Boston, pp 1–9

    Google Scholar 

  97. Ma X, Li M, He J-J (2013) CMOS-compatible integrated spectrometer based on echelle diffraction grating and MSM photodetector array. IEEE Photonics J 5:6600807

    Article  Google Scholar 

  98. Bates KE, Lu H (2016) Optics-integrated microfluidic platforms for biomolecular analyses. Biophys J 110:1684–1697

    Article  CAS  Google Scholar 

  99. Kinsey JL (1977) Laser-induced fluorescence. Annu Rev Phys Chem 28(1):349–372

    Article  CAS  Google Scholar 

  100. Peroz C, Dhuey S, Goltsov A et al (2011) Digital spectrometer-on-chip fabricated by step and repeat nanoimprint lithography on pre-spin coated films. Microelectron Eng 88:2092–2095

    Article  CAS  Google Scholar 

  101. Liu R, Wang N, Kamili F, Fatih Sarioglu A (2016) Microfluidic CODES: a scalable multiplexed electronic sensor for orthogonal detection of particles in microfluidic channels. Lab Chip 16:1350–1357

    Article  CAS  Google Scholar 

  102. Ashiba H, Fujimaki M, Awazu K et al (2016) Microfluidic chips for forward blood typing performed with a multichannel waveguide-mode sensor. Sens Bio-Sens Res 7:121–126

    Article  Google Scholar 

  103. Wilhelm E, Neumann C, Duttenhofer T et al (2013) Connecting microfluidic chips using a chemically inert, reversible, multichannel chip-to-world-interface. Lab Chip 13:4343

    Article  CAS  Google Scholar 

  104. Chen X, Cui D, Chen J (2012) Integrated microfluidic chips for whole blood pretreatment. On-chip pretreatment of whole blood by using MEMS technology. pp 110–116. https://doi.org/10.2174/978160805147211201010110

  105. Hou HW, Bhagat AAS, Lee WC et al (2011) Microfluidic devices for blood fractionation. Micromachines 2:319–343

    Article  Google Scholar 

  106. Alazzam A, Hilal-Alnaqbi A, Alnaimat F et al (2018) Dielectrophoresis-based microfluidic devices for field-flow fractionation. Med Devices Sens 1:e10007

    Article  Google Scholar 

  107. Alvankarian J, Majlis B (2015) Tunable microfluidic devices for hydrodynamic fractionation of cells and beads: a review. Sensors 15:29685–29701

    Article  Google Scholar 

  108. Sahore V, Sonker M, Nielsen AV et al (2018) Automated microfluidic devices integrating solid-phase extraction, fluorescent labeling, and microchip electrophoresis for preterm birth biomarker analysis. Anal Bioanal Chem 410:933–941

    Article  CAS  Google Scholar 

  109. Kasukurti A, Eggleton CD, Desai SA et al (2014) A simple microfluidic dispenser for single-microparticle and cell samples. Lab Chip 14:4673–4679

    Article  CAS  Google Scholar 

  110. Kasukurti A (2014) Combining optical and hydrodynamic forces for single cell characterization, isolation and delivery, PhD diss., Colorado School of Mines, Golden, CO. http://hdl.handle.net/11124/16984

  111. Vaidyanathan R, Yeo T, Lim CT (2018) Microfluidics for cell sorting and single cell analysis from whole blood. Methods Cell Biol 147:151–173

    Google Scholar 

  112. Majeed B, Liu C, Van Acker L et al (2014) Fabrication of silicon based microfluidics device for cell sorting application. In: 2014 IEEE 64th electronic components and technology conference (ECTC)

    Google Scholar 

  113. Girault M, Kim H, Arakawa H et al (2017) An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution. Sci Rep 7:40072

    Article  CAS  Google Scholar 

  114. Mazutis L, Gilbert J, Lloyd Ung W et al (2013) Single-cell analysis and sorting using droplet-based microfluidics. Nat Protocol 8:870–891

    Article  CAS  Google Scholar 

  115. Stoecklein D, Lore KG, Davies M et al (2017) Deep learning for flow sculpting: insights into efficient learning using scientific simulation data. Sci Rep 7:46368

    Article  CAS  Google Scholar 

  116. Samsel L, Dagur PK, Raghavachari N et al (2013) Imaging flow cytometry for morphologic and phenotypic characterization of rare circulating endothelial cells. Cytometry B Clin Cytom 84:379–389

    Article  CAS  Google Scholar 

  117. Heo YJ, Lee D, Kang J et al (2017) Real-time image processing for microscopy-based label-free imaging flow cytometry in a microfluidic chip. Sci Rep 7:11651. https://doi.org/10.1038/s41598-017-11534-0

    Article  CAS  Google Scholar 

  118. Su X, Xu Y, Zhao H et al (2019) Design and preparation of centrifugal microfluidic chip integrated with SERS detection for rapid diagnostics. Talanta 194:903–909

    Article  CAS  Google Scholar 

  119. Bhatia SN, Ingber DE (2014) Microfluidic organs-on-chips. Nat Biotechnol 32:760–772

    Article  CAS  Google Scholar 

  120. Wang Z, Roya S, Kyo-in K, Kim K (2015) Organ-on-a-chip platforms for drug delivery and cell characterization: a review. Sens Mater 27(6):487–506

    Google Scholar 

  121. Grosberg A, Nesmith AP, Goss JA et al (2012) Muscle on a chip: in vitro contractility assays for smooth and striated muscle. J Pharmacol Toxicol Methods 65:126–135

    Article  CAS  Google Scholar 

  122. van der Meer AD, Vermeul K, Poot AA et al (2010) A microfluidic wound-healing assay for quantifying endothelial cell migration. Am J Physiol Heart Circ Physiol 298:H719–H725

    Article  CAS  Google Scholar 

  123. Zheng W, Jiang B, Wang D et al (2012) A microfluidic flow-stretch chip for investigating blood vessel biomechanics. Lab Chip 12:3441–3450

    Article  CAS  Google Scholar 

  124. Neeves KB, Onasoga AA, Wufsus AR (2013) The use of microfluidics in hemostasis: clinical diagnostics and biomimetic models of vascular injury. Curr Opin Hematol 20:417–423

    Article  CAS  Google Scholar 

  125. Jain A, van der Meer AD, Papa A-L et al (2016) Assessment of whole blood thrombosis in a microfluidic device lined by fixed human endothelium. Biomed Microdevices 18:73. https://doi.org/10.1007/s10544-016-0095-6

    Article  Google Scholar 

  126. Huh D, Matthews BD, Mammoto A et al (2010) Reconstituting organ-level lung functions on a Chip. Science 328:1662–1668

    Article  CAS  Google Scholar 

  127. Grosberg A, Alford PW, McCain ML, Parker KK (2011) Ensembles of engineered cardiac tissues for physiological and pharmacological study: heart on a chip. Lab Chip 11:4165–4173

    Article  CAS  Google Scholar 

  128. Agarwal A, Goss JA, Cho A et al (2013) Microfluidic heart on a chip for higher throughput pharmacological studies. Lab Chip 13:3599

    Article  CAS  Google Scholar 

  129. Zhang YS, Aleman J, Shin SR et al (2017) Multisensor-integrated organs-on-chips platform for automated and continual in situ monitoring of organoid behaviors. Proc Natl Acad Sci U S A 114:E2293–E2302

    Article  CAS  Google Scholar 

  130. Valencia PM, Farokhzad OC, Karnik R, Langer R (2012) Microfluidic technologies for accelerating the clinical translation of nanoparticles. Nat Nanotechnol 7:623–629

    Article  CAS  Google Scholar 

  131. Ngamcherdtrakul W, Morry J, Gu S et al (2015) Cationic polymer modified mesoporous silica nanoparticles for targeted SiRNA delivery to HER2+ breast cancer. Adv Funct Mater 25:2646–2659

    Article  CAS  Google Scholar 

  132. Ngamcherdtrakul W, Morry J, Gu S et al (2015) Cancer nanomedicine: cationic polymer modified mesoporous silica nanoparticles for targeted siRNA delivery to HER2 breast cancer. Adv Funct Mater 25:2629–2629

    Article  Google Scholar 

  133. Urries I, Muñoz C, Gomez L et al (2014) Magneto-plasmonic nanoparticles as theranostic platforms for magnetic resonance imaging, drug delivery and NIR hyperthermia applications. Nanoscale 6:9230–9240

    Article  CAS  Google Scholar 

  134. Lim J-M, Bertrand N, Valencia PM et al (2014) Parallel microfluidic synthesis of size-tunable polymeric nanoparticles using 3D flow focusing towards in vivo study. Nanomedicine 10:401–409

    Article  CAS  Google Scholar 

  135. Leung AKK, Hafez IM, Baoukina S et al (2012) Lipid nanoparticles containing siRNA synthesized by microfluidic mixing exhibit an electron-dense nanostructured core. J Phys Chem C Nanomater Interfaces 116:18440–18450

    Article  CAS  Google Scholar 

  136. Prabhakarpandian B, Shen M-C, Nichols JB et al (2015) Synthetic tumor networks for screening drug delivery systems. J Control Release 201:49–55

    Article  CAS  Google Scholar 

  137. Cao C, Liu F, Tan H et al (2018) Deep learning and its applications in biomedicine. Genomics Proteomics Bioinformatics 16:17–32

    Article  Google Scholar 

  138. Ching T, Himmelstein DS, Beaulieu-Jones BK et al (2018) Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface 15:20170387. https://doi.org/10.1098/rsif.2017.0387

    Article  Google Scholar 

  139. Van Valen DA, Kudo T, Lane KM et al (2016) Deep learning automates the quantitative analysis of individual cells in live-cell imaging experiments. PLoS Comput Biol 12:e1005177

    Article  CAS  Google Scholar 

  140. Chen CL, Mahjoubfar A, Tai L-C et al (2016) Deep learning in label-free cell classification. Sci Rep 6:21471

    Article  CAS  Google Scholar 

  141. Li L (2010) Machine learning methods for computational biology, Open dissertation press. ISBN-10:1360962859. ISBN-13:978-1360962856

    Google Scholar 

  142. Riordon J, Sovilj D, Sanner S et al (2018) Deep learning with microfluidics for biotechnology. Trends Biotechnol 37:310. https://doi.org/10.1016/j.tibtech.2018.08.005

    Article  CAS  Google Scholar 

  143. Ionica MH, Gregg D (2015) The Movidius myriad architecture’s potential for scientific computing. IEEE Micro 35:6–14

    Article  Google Scholar 

  144. (2016) Google works with Movidius to deploy advanced machine intelligence on mobiles. Biometric Technol Today 2016:12

    Google Scholar 

  145. Othman NA, Aydin I (2018) A new deep learning application based on Movidius NCS for embedded object detection and recognition. In: 2018 2nd international symposium on multidisciplinary studies and innovative technologies (ISMSIT)

    Google Scholar 

  146. Ko J, Baldassano SN, Loh P-L et al (2018) Machine learning to detect signatures of disease in liquid biopsies – a user’s guide. Lab Chip 18:395–405

    Article  CAS  Google Scholar 

  147. Huang X, Jiang Y, Liu X et al (2016) Machine learning based single-frame super-resolution processing for lensless blood cell counting. Sensors 16. https://doi.org/10.3390/s16111836

    Article  CAS  Google Scholar 

  148. Ko J, Bhagwat N, Yee SS et al (2017) Combining machine learning and nanofluidic technology to diagnose pancreatic cancer using exosomes. ACS Nano 11:11182–11193

    Article  CAS  Google Scholar 

  149. Singh DK, Ahrens CC, Li W, Vanapalli SA (2017) Label-free, high-throughput holographic screening and enumeration of tumor cells in blood. Lab Chip 17:2920–2932

    Article  CAS  Google Scholar 

  150. Wang Z, Boddeda A, Parker B et al (2018) A high-resolution minimicroscope system for wireless real-time monitoring. IEEE Trans Biomed Eng 65:1524–1531

    Article  Google Scholar 

  151. Berthier J, Brakke KA, Berthier E (2016) Open microfluidics. Wiley, Beverly

    Book  Google Scholar 

  152. Delamarche E, Kaigala GV (2018) Open-space microfluidics: concepts, implementations, applications. Wiley, Weinheim

    Book  Google Scholar 

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Acknowledgments

This work was supported by West Virginia University startup funds awarded to J. Maddala.

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Correspondence to Aditya Kasukurti or Jeevan Maddala .

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Kasukurti, A., Lakshmanan, H.H.S., Tiwari, S., Maddala, J. (2019). Integrated Multilayer Microfluidic Platforms with Silicon Architectures for Next-Generation Health Diagnostic Systems. In: Kumar, C. (eds) Nanotechnology Characterization Tools for Tissue Engineering and Medical Therapy. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59596-1_9

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