Affiliation:
1. Department of Chemistry, University of Connecticut, Storrs, CT 06269-3060, USA
2. Institute of Materials Science, University of Connecticut, Storrs, CT 06269-3136, USA
3. Department of Surgery and Neag Cancer Center, Uconn Health, Farmington, CT 06030-0001, USA
4. School of Chemistry, National University of Ireland at Galway, H91 TK33 Galway, Ireland
Abstract
Microfluidic technology has revolutionized device fabrication by merging principles of fluid dynamics with technologies from chemistry, physics, biology, material science, and microelectronics. Microfluidic systems manipulate small volumes of fluids to perform automated tasks with applications ranging from chemical syntheses to biomedical diagnostics. The advent of low-cost 3D printers has revolutionized the development of microfluidic systems. For measuring molecules, 3D printing offers cost-effective, time, and ease-of-designing benefits. In this paper, we present a comprehensive tutorial for design, optimization, and validation for creating a 3D-printed microfluidic immunoarray for ultrasensitive detection of multiple protein biomarkers. The target is the development of a point of care array to determine five protein biomarkers for aggressive cancers. The design phase involves defining dimensions of microchannels, reagent chambers, detection wells, and optimizing parameters and detection methods. In this study, the physical design of the array underwent multiple iterations to optimize key features, such as developing open detection wells for uniform signal distribution and a flap for covering wells during the assay. Then, full signal optimization for sensitivity and limit of detection (LOD) was performed, and calibration plots were generated to assess linear dynamic ranges and LODs. Varying characteristics among biomarkers highlighted the need for tailored assay conditions. Spike-recovery studies confirmed the assay’s accuracy. Overall, this paper showcases the methodology, rigor, and innovation involved in designing a 3D-printed microfluidic immunoarray. Optimized parameters, calibration equations, and sensitivity and accuracy data contribute valuable metrics for future applications in biomarker analyses.
Funder
University of Connecticut College of Liberal arts and Sciences the Paul Krenicki Professorship fund
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering
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