Advancing Point-of-Care Applications with Droplet Microfluidics: From Single-Cell to Multicellular Analysis

Literature Cited

1. 1.

   Li Y, Fan H, Ding J, Xu J, Liu C, Wang H. 2022.. Microfluidic devices: the application in TME modeling and the potential in immunotherapy optimization. . Front. Genet. 13::969723
   [Crossref] [Google Scholar]
2. 2.

   Berger Fridman I, Ugolini GS, VanDelinder V, Cohen S, Konry T. 2021.. High throughput microfluidic system with multiple oxygen levels for the study of hypoxia in tumor spheroids. . Biofabrication 13::035037
   [Crossref] [Google Scholar]
3. 3.

   Macounova K, Cabrera CR, Holl MR, Yager P. 2000.. Generation of natural pH gradients in microfluidic channels for use in isoelectric focusing. . Anal. Chem. 72::3745–51
   [Crossref] [Google Scholar]
4. 4.

   Ayuso JM, Rehman S, Virumbrales-Munoz M, McMinn PH, Geiger P, et al. 2021.. Microfluidic tumor-on-a-chip model to evaluate the role of tumor environmental stress on NK cell exhaustion. . Sci. Adv. 7::eabc2331
   [Crossref] [Google Scholar]
5. 5.

   Pavesi A, Tan AT, Koh S, Chia A, Colombo M, et al. 2017.. A 3D microfluidic model for preclinical evaluation of TCR-engineered T cells against solid tumors. . JCI Insight 2::e89762
   [Crossref] [Google Scholar]
6. 6.

   Konry T, Dominguez-Villar M, Baecher-Allan C, Hafler DA, Yarmush ML. 2011.. Droplet-based microfluidic platforms for single T cell secretion analysis of IL-10 cytokine. . Biosens. Bioelectron. 26::2707–10
   [Crossref] [Google Scholar]
7. 7.

   Sabhachandani P, Motwani V, Cohen N, Sarkar S, Torchilin V, Konry T. 2016.. Generation and functional assessment of 3D multicellular spheroids in droplet based microfluidics platform. . Lab Chip 16::497–505
   [Crossref] [Google Scholar]
8. 8.

   Sarkar S, Motwani V, Sabhachandani P, Cohen N, Konry T. 2015.. T cell dynamic activation and functional analysis in nanoliter droplet microarray. . J. Clin. Cell. Immunol. 6::334
   [Crossref] [Google Scholar]
9. 9.

   Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, et al. 2015.. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. . Cell 161::1202–14
   [Crossref] [Google Scholar]
10. 10.

    Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, et al. 2015.. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. . Cell 161::1187–201
    [Crossref] [Google Scholar]
11. 11.

    Mazutis L, Gilbert J, Ung WL, Weitz DA, Griffiths AD, Heyman JA. 2013.. Single-cell analysis and sorting using droplet-based microfluidics. . Nat. Protoc. 8::870–91
    [Crossref] [Google Scholar]
12. 12.

    Agresti JJ, Antipov E, Abate AR, Ahn K, Rowat AC, et al. 2010.. Ultrahigh-throughput screening in drop-based microfluidics for directed evolution. . PNAS 107::4004–9
    [Crossref] [Google Scholar]
13. 13.

    Wu M, Ouyang Y, Wang Z, Zhang R, Huang PH, et al. 2017.. Isolation of exosomes from whole blood by integrating acoustics and microfluidics. . PNAS 114::10584–89
    [Crossref] [Google Scholar]
14. 14.

    Duncanson WJ, Lin T, Abate AR, Seiffert S, Shah RK, Weitz DA. 2012.. Microfluidic synthesis of advanced microparticles for encapsulation and controlled release. . Lab Chip 12::2135–45
    [Crossref] [Google Scholar]
15. 15.

    Lan F, Demaree B, Ahmed N, Abate AR. 2017.. Single-cell genome sequencing at ultra-high-throughput with microfluidic droplet barcoding. . Nat. Biotechnol. 35::640–46
    [Crossref] [Google Scholar]
16. 16.

    Sun C, Liu L, Perez L, Li X, Liu Y, et al. 2022.. Droplet-microfluidics-assisted sequencing of HIV proviruses and their integration sites in cells from people on antiretroviral therapy. . Nat. Biomed. Eng. 6::1004–12
    [Crossref] [Google Scholar]
17. 17.

    Konry T, Golberg A, Yarmush M. 2013.. Live single cell functional phenotyping in droplet nano-liter reactors. . Sci. Rep. 3::3179
    [Crossref] [Google Scholar]
18. 18.

    Agnihotri SN, Ugolini GS, Sullivan MR, Yang Y, De Ganzo A, et al. 2022.. Droplet microfluidics for functional temporal analysis and cell recovery on demand using microvalves: application in immunotherapies for cancer. . Lab Chip 22::3258–67
    [Crossref] [Google Scholar]
19. 19.

    Konry T, Sarkar S, Sabhachandani P, Cohen N. 2016.. Innovative tools and technology for analysis of single cells and cell-cell interaction. . Annu. Rev. Biomed. Eng. 18::259–84
    [Crossref] [Google Scholar]
20. 20.

    Ravi D, Sarkar S, Purvey S, Passero F, Beheshti A, et al. 2020.. Interaction kinetics with transcriptomic and secretory responses of CD19-CAR natural killer-cell therapy in CD20 resistant non-hodgkin lymphoma. . Leukemia 34::1291–304
    [Crossref] [Google Scholar]
21. 21.

    Paterson K, Zanivan S, Glasspool R, Coffelt SB, Zagnoni M. 2021.. Microfluidic technologies for immunotherapy studies on solid tumours. . Lab Chip 21::2306–29
    [Crossref] [Google Scholar]
22. 22.

    Esfahani K, Roudaia L, Buhlaiga N, Del Rincon SV, Papneja N, Miller WH Jr. 2020.. A review of cancer immunotherapy: from the past, to the present, to the future. . Curr. Oncol. 27::S87–97
    [Crossref] [Google Scholar]
23. 23.

    Kim J, Koo BK, Knoblich JA. 2020.. Human organoids: model systems for human biology and medicine. . Nat. Rev. Mol. Cell Biol. 21::571–84
    [Crossref] [Google Scholar]
24. 24.

    Matsui T, Shinozawa T. 2021.. Human organoids for predictive toxicology research and drug development. . Front. Genet. 12::767621
    [Crossref] [Google Scholar]
25. 25.

    Prabhakar P, Sen RK, Dwivedi N, Khan R, Solanki PR, et al. 2021.. 3D-printed microfluidics and potential biomedical applications. . Front. Nanotechnol. 3::609355
    [Crossref] [Google Scholar]
26. 26.

    Schuster B, Junkin M, Kashaf SS, Romero-Calvo I, Kirby K, et al. 2020.. Automated microfluidic platform for dynamic and combinatorial drug screening of tumor organoids. . Nat. Commun. 11::5271
    [Crossref] [Google Scholar]
27. 27.

    Tehranirokh M, Kouzani AZ, Francis PS, Kanwar JR. 2013.. Microfluidic devices for cell cultivation and proliferation. . Biomicrofluidics 7::51502
    [Crossref] [Google Scholar]
28. 28.

    Frey O, Misun PM, Fluri DA, Hengstler JG, Hierlemann A. 2014.. Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis. . Nat. Commun. 5::4250
    [Crossref] [Google Scholar]
29. 29.

    Agarwal P, Wang H, Sun M, Xu J, Zhao S, et al. 2017.. Microfluidics enabled bottom-up engineering of 3D vascularized tumor for drug discovery. . ACS Nano 11::6691–702
    [Crossref] [Google Scholar]
30. 30.

    Wang H, Liu H, Zhang X, Wang Y, Zhao M, et al. 2021.. One-step generation of aqueous-droplet-filled hydrogel fibers as organoid carriers using an all-in-water microfluidic system. . ACS Appl. Mater. Interfaces 13::3199–208
    [Crossref] [Google Scholar]
31. 31.

    Collins DJ, Neild A, deMello A, Liu AQ, Ai Y. 2015.. The Poisson distribution and beyond: methods for microfluidic droplet production and single cell encapsulation. . Lab Chip 15::3439–59
    [Crossref] [Google Scholar]
32. 32.

    Zhang P, Abate AR. 2020.. High-definition single-cell printing: cell-by-cell fabrication of biological structures. . Adv. Mater. 32::e2005346
    [Crossref] [Google Scholar]
33. 33.

    Belousov KI, Filatov NA, Kukhtevich IV, Kantsler V, Evstrapov AA, Bukatin AS. 2021.. An asymmetric flow-focusing droplet generator promotes rapid mixing of reagents. . Sci. Rep. 11::8797
    [Crossref] [Google Scholar]
34. 34.

    Gu H, Duits MH, Mugele F. 2010.. A hybrid microfluidic chip with electrowetting functionality using ultraviolet (UV)-curable polymer. . Lab Chip 10::1550–56
    [Crossref] [Google Scholar]
35. 35.

    Choi JH, Lee SK, Lim JM, Yang SM, Yi GR. 2010.. Designed pneumatic valve actuators for controlled droplet breakup and generation. . Lab Chip 10::456–61
    [Crossref] [Google Scholar]
36. 36.

    Li Y, Jain M, Ma Y, Nandakumar K. 2015.. Control of the breakup process of viscous droplets by an external electric field inside a microfluidic device. . Soft Matter 11::3884–99
    [Crossref] [Google Scholar]
37. 37.

    Salehi SS, Shamloo A, Hannani SK. 2020.. Microfluidic technologies to engineer mesenchymal stem cell aggregates—applications and benefits. . Biophys. Rev. 12::123–33
    [Crossref] [Google Scholar]
38. 38.

    Sonnen KF, Merten CA. 2019.. Microfluidics as an emerging precision tool in developmental biology. . Dev. Cell 48::293–311
    [Crossref] [Google Scholar]
39. 39.

    Ma Q, Ma H, Xu F, Wang X, Sun W. 2021.. Microfluidics in cardiovascular disease research: state of the art and future outlook. . Microsyst. Nanoeng. 7::19
    [Crossref] [Google Scholar]
40. 40.

    Liu W, Sun M, Han K, Wang J. 2019.. Large-scale antitumor screening based on heterotypic 3D tumors using an integrated microfluidic platform. . Anal. Chem. 91::13601–10
    [Crossref] [Google Scholar]
41. 41.

    Jeyhani M, Gnyawali V, Abbasi N, Hwang DK, Tsai SSH. 2019.. Microneedle-assisted microfluidic flow focusing for versatile and high throughput water-in-water droplet generation. . J. Colloid Interface Sci. 553::382–89
    [Crossref] [Google Scholar]
42. 42.

    Flont M, Jastrzebska E, Brzozka Z. 2020.. A multilayered cancer-on-a-chip model to analyze the effectiveness of new-generation photosensitizers. . Analyst 145::6937–47
    [Crossref] [Google Scholar]
43. 43.

    Jiang R, Huang J, Sun X, Chu X, Wang F, et al. 2022.. Construction of in vitro 3-D model for lung cancer-cell metastasis study. . BMC Cancer 22::438
    [Crossref] [Google Scholar]
44. 44.

    Kwak B, Lee Y, Lee J, Lee S, Lim J. 2018.. Mass fabrication of uniform sized 3D tumor spheroid using high-throughput microfluidic system. . J. Control. Release 275::201–7
    [Crossref] [Google Scholar]
45. 45.

    Khan AH, Zhou SP, Moe M, Ortega Quesada BA, Bajgiran KR, et al. 2022.. Generation of 3D spheroids using a thiol-acrylate hydrogel scaffold to study endocrine response in ER⁺ breast cancer. . ACS Biomater. Sci. Eng. 8::3977–85
    [Crossref] [Google Scholar]
46. 46.

    Truong DD, Kratz A, Park JG, Barrientos ES, Saini H, et al. 2019.. A human organotypic microfluidic tumor model permits investigation of the interplay between patient-derived fibroblasts and breast cancer cells. . Cancer Res. 79::3139–51
    [Crossref] [Google Scholar]
47. 47.

    Lombardo JA, Aliaghaei M, Nguyen QH, Kessenbrock K, Haun JB. 2021.. Microfluidic platform accelerates tissue processing into single cells for molecular analysis and primary culture models. . Nat. Commun. 12::2858
    [Crossref] [Google Scholar]
48. 48.

    Li Y, Zhang T, Pang Y, Li L, Chen ZN, Sun W. 2019.. 3D bioprinting of hepatoma cells and application with microfluidics for pharmacodynamic test of metuzumab. . Biofabrication 11::034102
    [Crossref] [Google Scholar]
49. 49.

    Tricinci O, De Pasquale D, Marino A, Battaglini M, Pucci C, Ciofani G. 2020.. A 3D biohybrid real-scale model of the brain cancer microenvironment for advanced in vitro testing. . Adv. Mater Technol. 5::2000540
    [Crossref] [Google Scholar]
50. 50.

    Liu X, Fang J, Huang S, Wu X, Xie X, et al. 2021.. Tumor-on-a-chip: from bioinspired design to biomedical application. . Microsyst. Nanoeng. 7::50
    [Crossref] [Google Scholar]
51. 51.

    Fontana F, Marzagalli M, Sommariva M, Gagliano N, Limonta P. 2021.. In vitro 3D cultures to model the tumor microenvironment. . Cancers 13::2970
    [Crossref] [Google Scholar]
52. 52.

    Krysko DV, Demuynck R, Efimova I, Naessens F, Krysko O, Catanzaro E. 2022.. In vitro veritas: from 2D cultures to organ-on-a-chip models to study immunogenic cell death in the tumor microenvironment. . Cells 11::3705
    [Crossref] [Google Scholar]
53. 53.

    Brassart-Pasco S, Brezillon S, Brassart B, Ramont L, Oudart JB, Monboisse JC. 2020.. Tumor microenvironment: extracellular matrix alterations influence tumor progression. . Front. Oncol. 10::397
    [Crossref] [Google Scholar]
54. 54.

    Micek HM, Visetsouk MR, Masters KS, Kreeger PK. 2020.. Engineering the extracellular matrix to model the evolving tumor microenvironment. . iScience 23::101742
    [Crossref] [Google Scholar]
55. 55.

    Khalaf K, Hana D, Chou JT, Singh C, Mackiewicz A, Kaczmarek M. 2021.. Aspects of the tumor microenvironment involved in immune resistance and drug resistance. . Front. Immunol. 12::656364
    [Crossref] [Google Scholar]
56. 56.

    Eslami Amirabadi H, SahebAli S, Frimat JP, Luttge R, den Toonder JMJ. 2017.. A novel method to understand tumor cell invasion: integrating extracellular matrix mimicking layers in microfluidic chips by “selective curing. .” Biomed. Microdevices 19::92
    [Crossref] [Google Scholar]
57. 57.

    Frisk T, Rydholm S, Liebmann T, Svahn HA, Stemme G, Brismar H. 2007.. A microfluidic device for parallel 3-D cell cultures in asymmetric environments. . Electrophoresis 28::4705–12
    [Crossref] [Google Scholar]
58. 58.

    Akther F, Little P, Li Z, Nguyen NT, Ta HT. 2020.. Hydrogels as artificial matrices for cell seeding in microfluidic devices. . RSC Adv. 10::43682–703
    [Crossref] [Google Scholar]
59. 59.

    Ma J, Li N, Wang Y, Wang L, Wei W, et al. 2018.. Engineered 3D tumour model for study of glioblastoma aggressiveness and drug evaluation on a detachably assembled microfluidic device. . Biomed. Microdevices 20::80
    [Crossref] [Google Scholar]
60. 60.

    Liu C, Lewin Mejia D, Chiang B, Luker KE, Luker GD. 2018.. Hybrid collagen alginate hydrogel as a platform for 3D tumor spheroid invasion. . Acta Biomater. 75::213–25
    [Crossref] [Google Scholar]
61. 61.

    Lee KY, Mooney DJ. 2012.. Alginate: properties and biomedical applications. . Prog. Polym. Sci. 37::106–26
    [Crossref] [Google Scholar]
62. 62.

    Sabhachandani P, Sarkar S, McKenney S, Ravi D, Evens AM, Konry T. 2019.. Microfluidic assembly of hydrogel-based immunogenic tumor spheroids for evaluation of anticancer therapies and biomarker release. . J. Control. Release 295::21–30
    [Crossref] [Google Scholar]
63. 63.

    Liu P, Tian Z, Yang K, Naquin TD, Hao N, et al. 2022.. Acoustofluidic black holes for multifunctional in-droplet particle manipulation. . Sci. Adv. 8::eabm2592
    [Crossref] [Google Scholar]
64. 64.

    Zhou Y, Yu Z, Wu M, Lan Y, Jia C, Zhao J. 2023.. Single-cell sorting using integrated pneumatic valve droplet microfluidic chip. . Talanta 253::124044
    [Crossref] [Google Scholar]
65. 65.

    Girault M, Kim H, Arakawa H, Matsuura K, Odaka M, 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
    [Crossref] [Google Scholar]
66. 66.

    Dugger SA, Platt A, Goldstein DB. 2018.. Drug development in the era of precision medicine. . Nat. Rev. Drug Discov. 17::183–96
    [Crossref] [Google Scholar]
67. 67.

    Seyhan AA, Carini C. 2019.. Are innovation and new technologies in precision medicine paving a new era in patients centric care?. J. Transl. Med. 17::114
    [Crossref] [Google Scholar]
68. 68.

    Roth L, Bempong D, Babigumira JB, Banoo S, Cooke E, et al. 2018.. Expanding global access to essential medicines: investment priorities for sustainably strengthening medical product regulatory systems. . Global Health 14::102
    [Crossref] [Google Scholar]
69. 69.

    Yao B, Zhu L, Jiang Q, Xia HA. 2013.. Safety monitoring in clinical trials. . Pharmaceutics 5::94–106
    [Crossref] [Google Scholar]
70. 70.

    Pognan F, Beilmann M, Boonen HCM, Czich A, Dear G, et al. 2023.. The evolving role of investigative toxicology in the pharmaceutical industry. . Nat. Rev. Drug Discov. 22::317–35
    [Crossref] [Google Scholar]
71. 71.

    Hughes JP, Rees S, Kalindjian SB, Philpott KL. 2011.. Principles of early drug discovery. . Br. J. Pharmacol. 162::1239–49
    [Crossref] [Google Scholar]
72. 72.

    Cardoso BD, Castanheira EMS, Lanceros-Mendez S, Cardoso VF. 2023.. Recent advances on cell culture platforms for in vitro drug screening and cell therapies: from conventional to microfluidic strategies. . Adv. Healthc. Mater. 12::e2202936
    [Crossref] [Google Scholar]
73. 73.

    Ravi M, Paramesh V, Kaviya SR, Anuradha E, Solomon FD. 2015.. 3D cell culture systems: advantages and applications. . J. Cell. Physiol. 230::16–26
    [Crossref] [Google Scholar]
74. 74.

    Lage OM, Ramos MC, Calisto R, Almeida E, Vasconcelos V, Vicente F. 2018.. Current screening methodologies in drug discovery for selected human diseases. . Mar. Drugs 16::279
    [Crossref] [Google Scholar]
75. 75.

    Ugolini GS, Occhetta P, Saccani A, Re F, Krol S, et al. 2018.. Design and validation of a microfluidic device for blood–brain barrier monitoring and transport studies. . J. Micromech. Microeng. 24::044001
    [Crossref] [Google Scholar]
76. 76.

    Järvinen P, Bonabi A, Jokinen V, Sikanen T. 2020.. Simultaneous culturing of cell monolayers and spheroids on a single microfluidic device for bridging the gap between 2D and 3D cell assays in drug research. . Adv. Funct. Mater. 30::2000479
    [Crossref] [Google Scholar]
77. 77.

    Li S, Yang K, Chen X, Zhu X, Zhou H, et al. 2021.. Simultaneous 2D and 3D cell culture array for multicellular geometry, drug discovery and tumor microenvironment reconstruction. . Biofabrication 13::045013
    [Crossref] [Google Scholar]
78. 78.

    Holohan C, Van Schaeybroeck S, Longley DB, Johnston PG. 2013.. Cancer drug resistance: an evolving paradigm. . Nat. Rev. Cancer 13::714–26
    [Crossref] [Google Scholar]
79. 79.

    Xu Z, Gao Y, Hao Y, Li E, Wang Y, et al. 2013.. Application of a microfluidic chip-based 3D co-culture to test drug sensitivity for individualized treatment of lung cancer. . Biomaterials 34::4109–17
    [Crossref] [Google Scholar]
80. 80.

    Amoyav B, Goldstein Y, Steinberg E, Benny O. 2020.. 3D printed microfluidic devices for drug release assays. . Pharmaceutics 13::13
    [Crossref] [Google Scholar]
81. 81.

    Chen X, Chen H, Wu D, Chen Q, Zhou Z, et al. 2018.. 3D printed microfluidic chip for multiple anticancer drug combinations. . Sens. Actuators B Chem. 276::507–16
    [Crossref] [Google Scholar]
82. 82.

    Jeong SY, Lee JH, Shin Y, Chung S, Kuh HJ. 2016.. Co-culture of tumor spheroids and fibroblasts in a collagen matrix-incorporated microfluidic chip mimics reciprocal activation in solid tumor microenvironment. . PLOS ONE 11::e0159013
    [Crossref] [Google Scholar]
83. 83.

    Al-Samadi A, Poor B, Tuomainen K, Liu V, Hyytiainen A, et al. 2019.. In vitro humanized 3D microfluidic chip for testing personalized immunotherapeutics for head and neck cancer patients. . Exp. Cell Res. 383::111508
    [Crossref] [Google Scholar]
84. 84.

    Rahmanian M, Seyfoori A, Ghasemi M, Shamsi M, Kolahchi AR, et al. 2021.. In-vitro tumor microenvironment models containing physical and biological barriers for modelling multidrug resistance mechanisms and multidrug delivery strategies. . J. Control. Release 334::164–77
    [Crossref] [Google Scholar]
85. 85.

    Liu W, Sun M, Lu B, Yan M, Han K, Wang J. 2019.. A microfluidic platform for multi-size 3D tumor culture, monitoring and drug resistance testing. . Sens. Actuators B Chem. 292::111–20
    [Crossref] [Google Scholar]
86. 86.

    Carvalho MR, Barata D, Teixeira LM, Giselbrecht S, Reis RL, et al. 2019.. Colorectal tumor-on-a-chip system: a 3D tool for precision onco-nanomedicine. . Sci. Adv. 5::eaaw1317
    [Crossref] [Google Scholar]
87. 87.

    Shembekar N, Chaipan C, Utharala R, Merten CA. 2016.. Droplet-based microfluidics in drug discovery, transcriptomics and high-throughput molecular genetics. . Lab Chip 16::1314–31
    [Crossref] [Google Scholar]
88. 88.

    Jiang Z, Shi H, Tang X, Qin J. 2023.. Recent advances in droplet microfluidics for single-cell analysis. . Trends Analyt. Chem. 159::116932
    [Crossref] [Google Scholar]
89. 89.

    Cui P, Wang S. 2019.. Application of microfluidic chip technology in pharmaceutical analysis: a review. . J. Pharm. Anal. 9::238–47
    [Crossref] [Google Scholar]
90. 90.

    De Stefano P, Bianchi E, Dubini G. 2022.. The impact of microfluidics in high-throughput drug-screening applications. . Biomicrofluidics 16::031501
    [Crossref] [Google Scholar]
91. 91.

    Ling SD, Geng Y, Chen A, Du Y, Xu J. 2020.. Enhanced single-cell encapsulation in microfluidic devices: from droplet generation to single-cell analysis. . Biomicrofluidics 14::061508
    [Crossref] [Google Scholar]
92. 92.

    Tavakoli H, Zhou W, Ma L, Perez S, Ibarra A, et al. 2019.. Recent advances in microfluidic platforms for single-cell analysis in cancer biology, diagnosis and therapy. . Trends Analyt. Chem. 117::13–26
    [Crossref] [Google Scholar]
93. 93.

    Li B, Ma X, Cheng J, Tian T, Guo J, et al. 2023.. Droplets microfluidics platform—a tool for single cell research. . Front. Bioeng. Biotechnol. 11::1121870
    [Crossref] [Google Scholar]
94. 94.

    Fan Y, Nguyen DT, Akay Y, Xu F, Akay M. 2016.. engineering a brain cancer chip for high-throughput drug screening. . Sci. Rep. 6::25062
    [Crossref] [Google Scholar]
95. 95.

    Hou HW, Li QS, Lee GY, Kumar AP, Ong CN, Lim CT. 2009.. Deformability study of breast cancer cells using microfluidics. . Biomed. Microdevices 11::557–64
    [Crossref] [Google Scholar]
96. 96.

    Eduati F, Utharala R, Madhavan D, Neumann UP, Longerich T, et al. 2018.. A microfluidics platform for combinatorial drug screening on cancer biopsies. . Nat. Commun. 9::2434
    [Crossref] [Google Scholar]
97. 97.

    An X, Zuo P, Ye BC. 2020.. A single cell droplet microfluidic system for quantitative determination of food-borne pathogens. . Talanta 209::120571
    [Crossref] [Google Scholar]
98. 98.

    Choi Y, Hyun E, Seo J, Blundell C, Kim HC, et al. 2015.. A microengineered pathophysiological model of early-stage breast cancer. . Lab Chip 15::3350–57
    [Crossref] [Google Scholar]
99. 99.

    Du GS, Pan JZ, Zhao SP, Zhu Y, den Toonder JM, Fang Q. 2013.. Cell-based drug combination screening with a microfluidic droplet array system. . Anal. Chem. 85::6740–47
    [Crossref] [Google Scholar]
100. 100.

     An D, Kim K, Kim J. 2014.. Microfluidic system based high throughput drug screening system for curcumin/TRAIL combinational chemotherapy in human prostate cancer PC3 cells. . Biomol. Ther. 22::355–62
     [Crossref] [Google Scholar]