Year: 2024
Type: article
Abstract: Microfluidic lab-on-a-chip technologies enable the analysis and manipulation of small fluid volumes and particles at small scales and the control of fluid flow and transport processes at the microscale, leading to the development of new methods to address a broad range of scientific and medical challenges. Microfluidic and lab-on-a-chip technologies have made a noteworthy impact in basic, preclinical, and clinical research, especially in hematology and vascular biology due to the inherent ability of microfluidics to mimic physiologic flow conditions in blood vessels and capillaries. With the potential to significantly impact translational research and clinical diagnostics, technical issues and incentive mismatches have stymied microfluidics from fulfilling this promise. We describe how accessibility, usability, and manufacturability of microfluidic technologies should be improved and how a shift in mindset and incentives within the field is also needed to address these issues. In this report, we discuss the state of the microfluidic field regarding current limitations and propose future directions and new approaches for the field to advance microfluidic technologies closer to translation and clinical use. While our report focuses on using blood as the prototypical biofluid sample, the proposed ideas and research directions can be extrapolated to other areas of hematology, oncology, biology, and medicine.
Source: Lab on a Chip
DOI: 10.1039/d3lc00796k
Institutions: Case Western Reserve University, University of Minnesota, United States Food and Drug Administration, University of Pennsylvania, Florida Atlantic University, Washington University in St. Louis, Wayne State University, University of Illinois Chicago, University of Houston, University of Washington, Baebies (United States), Medical College of Wisconsin, National Heart, Lung, and Blood Institute, Emory University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4392455145
