Personalized Drug Efficacy Monitoring Chip

Cancer drug resistance mechanisms such as tumor heterogeneity and adaptable feedback loops are prevalent issues facing cancer therapy development. Drug resistance can be unique to a cancer type and, most importantly, to each individual cancer patient. Consequently, testing different dosages and therapeutics directly on each individual patient sample (i.e., tumor and cancer cells) has compelling advantages compared to large scale in vitro drug testing and is a step toward personalized drug selection and effective treatment development. Recently, microfluidic-based chemo-sensitivity assays on patient biopsies have been proposed. Despite their novelty, these platforms usually rely on optical labels, optical equipment, or complex microfabricated channel geometries and structures. In this work, we proposed a novel lab on a chip platform capable of real-time and continuous screening of drug efficacy on (cancer) cell subpopulations without the need of labels or bulky readout optical equipment. In this platform, several label-free and rapid techniques have been implemented for the precise capturing of cells of interest in parallel with the real-time measurement and characterization of the effectiveness of candidate therapeutic agents. To demonstrate the utility of the platform, the effect of an apoptotic inducer, topoisomerase I inhibitor, 7-ethyl-10-hydrocamptothecin (SN38) on human colorectal carcinoma cancer cells (HCT 116) was used as a study model. Additionally, electrical results were optically verified to examine the continuous measurements of the biological mechanisms, specifically, apoptosis and necrosis, during therapeutic agent characterizations. The proposed device is a versatile platform which can also be easily redesigned for the automated and arrayed analysis of cell-drug interaction down to the single cell level. Our platform is another step toward enabling the personalized screening of drug efficacy on individual patients' samples that potentially leads to a better understanding of drug resistance and the optimization of patients' treatments.