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Active STANDARD GRANT National Science Foundation (US)

CISE-MSI: RCBP: SCH: Global Access to Lab-On-Chip Through Additive Manufacturing

$4M USD

Funder National Science Foundation (US)
Recipient Organization California State University-Long Beach Foundation
Country United States
Start Date Sep 01, 2024
End Date Aug 31, 2026
Duration 729 days
Number of Grantees 3
Roles Principal Investigator; Co-Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2431589
Grant Description

The global aging population presents significant healthcare challenges, especially in low and middle-income countries with limited biomedical infrastructure and access to healthcare. This project aims to address these challenges by developing a portable and cost-effective biomedical diagnostic system minimizing human interaction in the form an integrated Lab-on-a-Chip diagnostic platform produced using additive manufacturing.

This project aims not only to advance biomedical engineering by integrating cutting-edge technologies but also to directly address global health disparities. As proposed Lab-on-a-Chip platform is to be tailored for resource-limited environments, the project aims to enhance healthcare accessibility and affordability worldwide. Further broader-impact aspects of the work include an interdisciplinary research effort fostering collaboration between biomedical engineering, materials science, and computer science in order to contribute to broader educational and research initiatives in global health equity and technology innovation.

Specifically, this project outlines the development of an integrated Lab-on-a-Chip diagnostic platform using Additive Manufacturing techniques. The technical activities comprise 1) advancing 3D manufacturing techniques, particularly in electrode printing, and establishing design rules to enhance fabrication precision and performance; 2) addressing the miniaturization of actuation, sensors, and readout systems using CMOS technology, aiming for seamless integration for bio-sample characterization without optical components; 3) defining design rules for implementing two independent tests with 3D-printed electrodes in the form of label-free cell characterization and dielectrophoresis-impedance methods for protein detection; and 4) leveraging artificial intelligence to optimize the fabrication process of 3D-printed conductive electrodes.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

All Grantees

California State University-Long Beach Foundation

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