An on-chip cell culturing and combinatorial drug screening system

  • Jiahui Sun
  • Wenjia Liu
  • Yulong Li
  • Azarmidokht Gholamipour-Shirazi
  • Aynur Abdulla
  • Xianting DingEmail author
Research Paper


A low-cost, convenient and precise drug combination screening microfluidic platform is developed, in which cell culture chambers designed with micropillars integrate with three laminar flow diffusion channels. This platform has several distinct features, including minimum shear stress on cells, biocompatibility, optimum concentration distribution and automatic combinatorial gradient generation, which can potentially speed up the discovery of an effective drug combination for cancer ablations. The presented device can generate two-drug combination gradients at the optimum flow rate of 90 μL/h and can be applied to identify the optimal combination of two clinically relevant chemotherapy drugs. For demonstration, paclitaxel at 0.77 × 10−3 mg/mL and cisplatin at 0.23 × 10−4 mg/mL were studied against lung cancer cells (A549). This microfluidic device has the potential to provide a precise and robust screening for anticancer combinational drugs practiced in clinics.


Drug combination Cisplatin Paclitaxel Microfluidics A549 cells Cancer 



This work was supported by National Natural Science Foundation of China (81301293) and National Science and Technology Major Projects for “Major New Drugs Innovation and Development” (2014ZX09507008).

Supplementary material

10404_2017_1959_MOESM1_ESM.docx (2 mb)
Supplementary material 1 (DOCX 2028 kb)


  1. Ahadian S, Ramón-Azcón J, Estili M, Obregón R, Shiku H, Matsue T (2014) Facile and rapid generation of 3D chemical gradients within hydrogels for high-throughput drug screening applications. Biosens Bioelectron 59:166–173CrossRefGoogle Scholar
  2. Al-Lazikani B, Banerji U, Workman P (2012) Combinatorial drug therapy for cancer in the post-genomic era. Nat Biotechnol 30:679–692CrossRefGoogle Scholar
  3. Atencia J, Morrow J, Locascio LE (2009) The microfluidic palette: a diffusive gradient generator with spatio-temporal control. Lab Chip 9:2707–2714. doi: 10.1039/b902113b CrossRefGoogle Scholar
  4. Beltran H et al (2011) New therapies for castration-resistant prostate cancer: efficacy and safety. Eur Urol 60:279–290CrossRefGoogle Scholar
  5. Bijl H, Carpenter MH, Vatsa VN, Kennedy CA (2002) Implicit time integration schemes for the unsteady compressible Navier–Stokes equations: laminar flow. J Comput Phys 179:313–329CrossRefzbMATHGoogle Scholar
  6. Bonadonna G et al (1976) Combination chemotherapy as an adjuvant treatment in operable breast cancer. N Engl J Med 294:405–410CrossRefGoogle Scholar
  7. Ding X, Sanchez DJ, Shahangian A, Al-Shyoukh I, Cheng G, Ho C-M (2012) Cascade search for HSV-1 combinatorial drugs with high antiviral efficacy and low toxicity. Int J 7:2281–2292Google Scholar
  8. Ding X, Xu H, Hopper C, Yang J, Ho CM (2013) Use of fractional factorial designs in antiviral drug studies. Qual Reliab Eng Int 29:299–304CrossRefGoogle Scholar
  9. Ding Y et al (2015) Microfluidic-enabled print-to-screen platform for high-throughput screening of combinatorial chemotherapy. Anal Chem 87:10166–10171CrossRefGoogle Scholar
  10. El-Ali J, Sorger PK, Jensen KF (2006) Cells on chips. Nature 442:403–411CrossRefGoogle Scholar
  11. Espinal MA et al (2000) Standard short-course chemotherapy for drug-resistant tuberculosis: treatment outcomes in 6 countries. JAMA 283:2537–2545CrossRefGoogle Scholar
  12. Frank T, Tay S (2013) Flow-switching allows independently programmable, extremely stable, high-throughput diffusion-based gradients. Lab Chip 13:1273–1281CrossRefGoogle Scholar
  13. Honda Y, Ding X, Mussano F, Wiberg A, C-m Ho, Nishimura I (2013) Guiding the osteogenic fate of mouse and human mesenchymal stem cells through feedback system control. Sci Rep 3:3420CrossRefGoogle Scholar
  14. Jang Y-H, Hancock MJ, Kim SB, Selimović Š, Sim WY, Bae H, Khademhosseini A (2011) An integrated microfluidic device for two-dimensional combinatorial dilution. Lab Chip 11:3277–3286CrossRefGoogle Scholar
  15. Kalchman J et al (2013) A three-dimensional microfluidic tumor cell migration assay to screen the effect of anti-migratory drugs and interstitial flow. Microfluid Nanofluid 14:969–981. doi: 10.1007/s10404-012-1104-6 CrossRefGoogle Scholar
  16. Khoo BL et al (2016) Liquid biopsy and therapeutic response: circulating tumor cell cultures for evaluation of anticancer treatment. Sci Adv. doi: 10.1126/sciadv.1600274 Google Scholar
  17. Kim J, Hegde M, Jayaraman A (2010) Co-culture of epithelial cells and bacteria for investigating host–pathogen interactions. Lab Chip 10:43–50CrossRefGoogle Scholar
  18. Kim J et al (2012) A programmable microfluidic cell array for combinatorial drug screening. Lab Chip 12:1813–1822CrossRefGoogle Scholar
  19. Lam KS (1997) Mini-review. Application of combinatorial library methods in cancer research and drug discovery. Anti-cancer Drug Des 12:145–167Google Scholar
  20. Lee K, Kim C, Jung G, Kim TS, Kang JY, Oh KW (2010) Microfluidic network-based combinatorial dilution device for high throughput screening and optimization. Microfluid Nanofluid 8:677–685. doi: 10.1007/s10404-009-0500-z CrossRefGoogle Scholar
  21. Li C-W, Chen R, Yang M (2007) Generation of linear and non-linear concentration gradients along microfluidic channel by microtunnel controlled stepwise addition of sample solution. Lab Chip 7:1371–1373CrossRefGoogle Scholar
  22. Liebmann JE, Fisher J, Teague D, Cook JA (1993) Sequence dependence of paclitaxel (Taxol) combined with cisplatin or alkylators in human cancer cells. Oncol Res 6:25–31Google Scholar
  23. Luo C, Zhu X, Yu T, Luo X, Ouyang Q, Ji H, Chen Y (2008) A fast cell loading and high-throughput microfluidic system for long-term cell culture in zero-flow environments. Biotechnol Bioeng 101:190–195CrossRefGoogle Scholar
  24. Malo S, Geuna A (2000) Science–technology linkages in an emerging research platform: the case of combinatorial chemistry and biology. Scientometrics 47:303–321CrossRefGoogle Scholar
  25. Merkel T, Bondar V, Nagai K, Freeman B, Pinnau I (2000) Gas sorption, diffusion, and permeation in poly (dimethylsiloxane). J Polym Sci Part B Polym Phys 38:415–434CrossRefGoogle Scholar
  26. Neils C, Tyree Z, Finlayson B, Folch A (2004) Combinatorial mixing of microfluidic streams. Lab Chip 4:342–350CrossRefGoogle Scholar
  27. Shamloo A, Ma N, Poo M-M, Sohn LL, Heilshorn SC (2008) Endothelial cell polarization and chemotaxis in a microfluidic device. Lab Chip 8:1292–1299CrossRefGoogle Scholar
  28. Shi Y, Gao XH, Chen LQ, Zhang M, Ma JY, Zhang XX, Qin JH (2013) High throughput generation and trapping of individual agarose microgel using microfluidic approach. Microfluid Nanofluid 15:467–474. doi: 10.1007/s10404-013-1160-6 CrossRefGoogle Scholar
  29. Silva A, Lee B-Y, Clemens DL, Kee T, Ding X, Ho C-M, Horwitz MA (2016) Output-driven feedback system control platform optimizes combinatorial therapy of tuberculosis using a macrophage cell culture model. In: Proceedings of the national academy of sciences, 201600812Google Scholar
  30. Singh A, Freeman B, Pinnau I (1998) Pure and mixed gas acetone/nitrogen permeation properties of polydimethylsiloxane [PDMS]. J Polym Sci Part B Polym Phys 36:289–301CrossRefGoogle Scholar
  31. Somaweera H, Haputhanthri SO, Ibraguimov A, Pappas D (2015) On-chip gradient generation in 256 microfluidic cell cultures: simulation and experimental validation. Analyst 140:5029–5038CrossRefGoogle Scholar
  32. Theodossiou C, Cook J, Fisher J, Teague D, Liebmann J, Russo A, Mitchell J (1998) Interaction of gemcitabine with paclitaxel and cisplatin in human tumor cell lines. Int J Oncol 12:825–832Google Scholar
  33. Tran TB, Cho S, Min J (2013) Hydrogel-based diffusion chip with Electric Cell-substrate Impedance Sensing (ECIS) integration for cell viability assay and drug toxicity screening. Biosens Bioelectron 50:453–459CrossRefGoogle Scholar
  34. Unger MA, Chou H-P, Thorsen T, Scherer A, Quake SR (2000) Monolithic microfabricated valves and pumps by multilayer soft lithography. Science 288:113–116CrossRefGoogle Scholar
  35. Wellhausen M, Rinke G, Wackerbarth H (2012) Combined measurement of concentration distribution and velocity field of two components in a micromixing process. Microfluid Nanofluid 12:917–926. doi: 10.1007/s10404-011-0926-y CrossRefGoogle Scholar
  36. Wu S et al (2016) Quantification of cell viability and rapid screening anti-cancer drug utilizing nanomechanical fluctuation. Biosens Bioelectron 77:164–173CrossRefGoogle Scholar
  37. Xu Y, Lv Y, Wang L, Xing W, Cheng J (2012) A microfluidic device with passive air-bubble valves for real-time measurement of dose-dependent drug cytotoxicity through impedance sensing. Biosens Bioelectron 32:300–304CrossRefGoogle Scholar
  38. Xu Z et al (2013) Application of a microfluidic chip-based 3D co-culture to test drug sensitivity for individualized treatment of lung cancer. Biomaterials 34:4109–4117. doi: 10.1016/j.biomaterials.2013.02.045 CrossRefGoogle Scholar
  39. Zhou Y, Lin Q (2014) Microfluidic flow-free generation of chemical concentration gradients. Sens Actuators B Chem 190:334–341CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Jiahui Sun
    • 1
  • Wenjia Liu
    • 1
  • Yulong Li
    • 1
  • Azarmidokht Gholamipour-Shirazi
    • 1
  • Aynur Abdulla
    • 1
  • Xianting Ding
    • 1
    Email author
  1. 1.State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina

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