Evidence map›Paper›PMID 32500349›Full record

ArticleCytotechnology2020

Automated in-process characterization and selection of cell-clones for quality and efficient cell manufacturing.

Venkata P Mantripragada, Viviane Luangphakdy, Bradley Hittle, Kimerly Powell, George F Muschler

Abstract read
In one paragraph

Article in Cytotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. 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

5 authors.

Venkata P MantripragadaDepartment of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA. mantriv@ccf.org.ORCID http://orcid.org/0000-0003-3144-079X
Viviane LuangphakdyDepartment of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.
Bradley HittleDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA.
Kimerly PowellDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA.
George F MuschlerDepartment of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.

Funding

Early Identification and Characterization of Connective Tissue ProgenitorsR21AR067357 · NIAMS · CLEVELAND CLINIC LERNER COM-CWRU · PI MUSCHLER, GEORGE F · 2014 to 2015
$365k
Foundation for the National Institutes of Health NCAI-17-7-APP-CCF-MuschlerFoundation for the National Institutes of Health R21AR067357NIAMS NIH HHS R21 AR067357
6 · The paper itself

Abstract

Delivery of safe, effective and reliable cellular therapies, whether based on mesenchymal stromal cells (MSCs) or induced pluripotent stem cells (iPSCs), demand standardization of cell culture protocols. There is a need to develop automation platform that enables the users to generate culture expanded human cell populations that improves the quality and reduces batch-to-batch variation with respect to biological potential. Cell X™ robot was designed to address these current challenges in the cell fabrication industry. It utilizes non-invasive large field of view quantitative image analysis to guide an automated process of targeted "biopsy" (cells or media), "picking" (selection) of desired cells or colonies, or "weeding" (removal) of undesired cells, thus providing an unprecedented ability to acquire quantitative measurement in a complex heterogeneous cell environment "in process" and then to act on those measurements to define highly reproducible methods for cell and colony "management" based on application specific critical quality attributes to improve the quality of the manufactured cell lines and cell products.

Indexed as

AutomationCell-pickingImagingPerformance-based cell selectionStem-cell manufacturingStem cells

Identifiers

PMID32500349
PMCPMC7547927

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.