Issue 19, 2018

Multi-parametric cell profiling with a CMOS quad-modality cellular interfacing array for label-free fully automated drug screening

Abstract

Cells are complex systems with concurrent multi-physical responses, and cell physiological signals are often encoded with spatiotemporal dynamics and further coupled with multiple cellular activities. However, most existing electronic sensors are only single-modality and cannot capture multi-parametric cellular responses. In this paper, a 1024-pixel CMOS quad-modality cellular interfacing array that enables multi-parametric cell profiling for drug development is presented. The quad-modality CMOS array features cellular impedance characterization, optical detection, extracellular potential recording, and biphasic current stimulation. The fibroblast transparency and surface adhesion are jointly monitored by cellular impedance and optical sensing modalities for comprehensive cell growth evaluation. Simultaneous current stimulation and opto-mechanical monitoring based on cardiomyocytes are demonstrated without any stimulation/sensing dead-zone. Furthermore, drug dose-dependent multi-parametric feature extractions in cardiomyocytes from their extracellular potentials and opto-mechanical signals are presented. The CMOS array demonstrates great potential for fully automated drug screening and drug safety assessments, which may substantially reduce the drug screening time and cost in future new drug development.

Graphical abstract: Multi-parametric cell profiling with a CMOS quad-modality cellular interfacing array for label-free fully automated drug screening

Article information

Article type
Paper
Submitted
08 Feb 2018
Accepted
06 Jun 2018
First published
31 Aug 2018
This article is Open Access
Creative Commons BY license

Lab Chip, 2018,18, 3037-3050

Multi-parametric cell profiling with a CMOS quad-modality cellular interfacing array for label-free fully automated drug screening

J. S. Park, S. I. Grijalva, M. K. Aziz, T. Chi, S. Li, M. N. Sayegh, A. Wang, H. C. Cho and H. Wang, Lab Chip, 2018, 18, 3037 DOI: 10.1039/C8LC00156A

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