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Sensor Technologies for Quality Control in Engineered Tissue Manufacturing

Published

Author(s)

Mary Clare McCorry, Marcie Black, Chrysanthi Williams, Greta Babakhanova, Sumona Sarkar, Nathan Swami, Katherine A. Mirica, Sarah Boermeester, Abbie Underhill

Abstract

The use of engineered cells, tissues, and organs has the opportunity to change the way injuries and diseases are treated. Commercialization of these groundbreaking technologies has been limited in part by the complex and costly nature of their manufacture. Process-related variability and even small changes in the manufacturing process of a living product will impact its quality. Without real-time integrated detection, the magnitude and mechanism of that impact are largely unknown. Real-time and non-destructive sensor technologies are key for in-process insight and ensuring a consistent product throughout commercial scale-up and/or scale-out. The application of a measurement technology into a manufacturing process requires cell and tissue developers to understand the best way to apply a sensor to their process, and for sensor manufacturers to understand the design requirements and end-user needs. Furthermore, sensors to monitor component cells' health and phenotype need to be compatible with novel integrated and automated manufacturing equipment. This review summarizes commercially relevant sensor technologies that can detect meaningful quality attributes during the manufacturing of regenerative medicine products, the gaps within each technology, and sensor considerations for manufacturing.
Citation
Biofabrication

Keywords

Tissue Engineering, Regenerative Medicine, Process Analytic Technology (PAT), Organoid, Cell Therapy, Measurement, Tissue Engineered Medical Product, Organoid, Lab on Chip

Citation

McCorry, M. , Black, M. , Williams, C. , Babakhanova, G. , Sarkar, S. , Swami, N. , Mirica, K. , Boermeester, S. and Underhill, A. (2022), Sensor Technologies for Quality Control in Engineered Tissue Manufacturing, Biofabrication, [online], https://doi.org/10.1088/1758-5090/ac94a1, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934648 (Accessed April 14, 2024)
Created October 27, 2022, Updated February 8, 2023