A novel design of microfluidic platform for metronomic combinatorial chemotherapy drug screening based on 3D tumor spheroid model

Sankar, S. and Sharma, C. and Rath, S.et al. (2021) A novel design of microfluidic platform for metronomic combinatorial chemotherapy drug screening based on 3D tumor spheroid model. Biomedical Microdevices, 23 (50). ISSN 13872176

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Abstract

For treating cancer at various stages, chemotherapy drugs administered in combination provide better treatment results with lower side effects compared to single-drug therapy. However, finding the potential drug combinations has been challenging due to the large numbers of possible combinations from approved drugs and the failure of in vitro 2D well plate-based cancer models. 3D spheroid-based high-throughput microfluidic platforms recapitulate some of the important features of native tumor tissue and offer a promising alternative to evaluate the combinatory effects of the drugs. This study develops a novel polydimethylsiloxane (PDMS) based microfluidic design with a dynamic environment and strategically placed U-shaped wells for testing all seven possible combinations (three single-drug treatments, three pairwise combinations, treatment with all three drugs) of three chemotherapy drugs (Paclitaxel, Vinorelbine, and Etoposide) on lung tumor spheroids. The design of U-shaped wells has been validated with computational results. Firstly, we test all combinations of drugs on the conventional well plate in static conditions with 3D tumor spheroids. Based on static drug testing results, we show a proof-of-concept by testing the most effective drug combination on the microfluidic device in a dynamic environment. The concentration of the drugs used in combination falls below the maximum tolerated dose (MTD) of the individual drugs, towards low dose metronomic (LDM) chemotherapy. LDM combinatorial chemotherapy identified in this study can potentially lower toxicity and provide better treatment results in cancer patients. The device can be further used to culture patient-specific tumor spheroids and identify synergistic drug combinations for personalized medicine.

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