Issue 24, 2021

Cancer drug screening with an on-chip multi-drug dispenser in digital microfluidics

Abstract

Microfluidics has been the most promising platform for drug screening with a limited number of cells. However, convenient on-chip preparation of a wide range of drug concentrations remains a large challenge and has restricted wide acceptance of microfluidics in precision medicine. In this paper, we report a digital microfluidic system with an innovative control structure and chip design for on-chip drug dispensing to generate concentrations that span three to four orders of magnitude, enabling single drug or combinatorial multi-drug screening with simple electronic control. Specifically, we utilize droplet ejection from a drug drop sitting on a special electrode, named a drug dispenser, under high-voltage pulse actuation to deliver the desired amount of drugs to be picked up by a cell suspension drop driven by low-voltage sine wave actuation. Our proof-of-principle validation for this technique as a convenient single and multi-drug screening involved testing of the drug toxicity of two chemotherapeutics, cisplatin (Cis) and epirubicin (EP), towards MDA-MB-231 breast cancer cells and MCF-10A normal breast cells. The results are consistent with those screened based on traditional 96-well plates. These findings demonstrate the reliability of the drug screening system with an on-chip drug dispenser. This system with fewer cancer cells, less drug consumption, a small footprint, and high scalability with regard to concentration could pave the way for drug screening on biopsied primary tumor cells for precision medicine or any concentration-related research.

Graphical abstract: Cancer drug screening with an on-chip multi-drug dispenser in digital microfluidics

Supplementary files

Article information

Article type
Paper
Submitted
05 Oct 2021
Accepted
02 Nov 2021
First published
02 Nov 2021

Lab Chip, 2021,21, 4749-4759

Cancer drug screening with an on-chip multi-drug dispenser in digital microfluidics

J. Zhai, C. Li, H. Li, S. Yi, N. Yang, K. Miao, C. Deng, Y. Jia, P. Mak and R. P. Martins, Lab Chip, 2021, 21, 4749 DOI: 10.1039/D1LC00895A

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