Scalable Multiplexed Drug-Combination Screening Platforms Using 3D Microtumor Model for Precision Medicine

Zhixiong Zhang, Yu Chih Chen, Sumithra Urs, Lili Chen, Diane M. Simeone, Euisik Yoon

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


Cancer heterogeneity is a notorious hallmark of this disease, and it is desirable to tailor effective treatments for each individual patient. Drug combinations have been widely accepted in cancer treatment for better therapeutic efficacy as compared to a single compound. However, experimental complexity and cost grow exponentially with more target compounds under investigation. The primary challenge remains to efficiently perform a large-scale drug combination screening using a small number of patient primary samples for testing. Here, a scalable, easy-to-use, high-throughput drug combination screening scheme is reported, which has the potential of screening all possible pairwise drug combinations for arbitrary number of drugs with multiple logarithmic mixing ratios. A “Christmas tree mixer” structure is introduced to generate a logarithmic concentration mixing ratio between drug pairs, providing a large drug concentration range for screening. A three-layer structure design and special inlets arrangement facilitate simple drug loading process. As a proof of concept, an 8-drug combination chip is implemented, which is capable of screening 172 different treatment conditions over 1032 3D cancer spheroids on a single chip. Using both cancer cell lines and patient-derived cancer cells, effective drug combination screening is demonstrated for precision medicine.

Original languageEnglish
Article number1703617
Issue number42
Publication statusPublished - 2018 Oct 18

Bibliographical note

Publisher Copyright:
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

All Science Journal Classification (ASJC) codes

  • Engineering (miscellaneous)
  • Chemistry(all)
  • Materials Science(all)
  • Biotechnology
  • Biomaterials


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