Evidence map›Paper›PMID 36150372›Full record

ReviewBiofabrication2022

Sensor technologies for quality control in engineered tissue manufacturing.

Mary Clare McCorry, Kenneth F Reardon, Marcie Black, Chrysanthi Williams, Greta Babakhanova, Jeffrey M Halpern, Sumona Sarkar, Nathan S Swami, Katherine A Mirica, Sarah Boermeester and 1 more

Abstract readReview
In one paragraph

Review in Biofabrication, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Mary Clare McCorryAdvanced Regenerative Manufacturing Institute, Manchester, NH 03101, United States of America.ORCID 0000-0001-9490-3523
Kenneth F ReardonChemical and Biological Engineering and Biomedical Engineering, Colorado State University, Fort Collins, CO 80521, United States of America.ORCID 0000-0002-7753-4049
Marcie BlackAdvanced Silicon Group, Lowell, MA 01854, United States of America.
Chrysanthi WilliamsAccess Biomedical Solutions, Trinity, Florida 34655, United States of America.
Greta BabakhanovaNational Institute of Standards and Technology, Gaithersburg, MD 20899, United States of America.ORCID 0000-0002-5027-5673
Jeffrey M HalpernDepartment of Chemical Engineering, University of New Hampshire, Durham, NH 03824, United States of America.ORCID 0000-0003-0814-1986
Sumona SarkarNational Institute of Standards and Technology, Gaithersburg, MD 20899, United States of America.
Nathan S SwamiElectrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, United States of America.ORCID 0000-0002-0492-1160
Katherine A MiricaDepartment of Chemistry, Dartmouth College, Hanover, NH 03755, United States of America.
Sarah BoermeesterAdvanced Regenerative Manufacturing Institute, Manchester, NH 03101, United States of America.
Abbie UnderhillScientific Bioprocessing Inc., Pittsburgh, PA 15238, United States of America.

Funding

Chemically Precise Framework Materials as a Modular Platform Technology for ElectroanalysisR35GM138318 · NIGMS · DARTMOUTH COLLEGE · PI MIRICA, KATHERINE ANDREA · 2020 to 2024
$2.0M
NIGMS NIH HHS R35 GM138318
6 · The paper itself

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.

Indexed as

Technology, PharmaceuticalTissue EngineeringQuality ControlRegenerative Medicinebiosensormeasurementorganoidprocess analytic technology (PAT)regenerative medicinetissue engineered medical producttissue engineering

Identifiers

PMID36150372
PMCPMC10283157

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.