ArticleJournal of translational medicine2022
Point-of-care cell therapy manufacturing; it's not for everyone.
Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Harnessing immunity against breast cancer: from checkpoints to cell therapies.Journal of translational medicine · 2026Review
- From production to bedside: A tiered QC framework for regulatory alignment and analytical comparability in decentralized CGT.Regenerative therapy · 2026Review
- Point-of-care CAR T-cell therapy: toward broader access.Blood advances · 2025Article
- Treatment of non-Hodgkin lymphoma with point-of-care manufactured CAR T cells: a dual institution, phase 1 trial.EClinicalMedicine · 2025Article
- Emerging Ethical Challenges in Manufacturing of Cell-Based Medicines.Advances in experimental medicine and biology · 2025Review
- Chimeric Antigen Receptor Immunotherapy for Solid Tumors: Choosing the Right Ingredients for the Perfect Recipe.Cancers · 2022Review
- Editorial: Mesenchymal Stromal Cells: Preclinical and Clinical Challenges.Frontiers in cell and developmental biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of cellular therapies to treat cancer, inherited immune deficiencies, hemoglobinopathies and viral infections is growing rapidly. The increased interest in cellular therapies has led to the development of reagents and closed-system automated instruments for the production of these therapies. For cellular therapy clinical trials involving multiple sites some people are advocating a decentralized model of manufacturing where patients are treated with cells produced using automated instruments at each participating center using a single, centrally held Investigational New Drug Application (IND). Many academic centers are purchasing these automated instruments for point-of-care manufacturing and participation in decentralized multiple center clinical trials. However, multiple site manufacturing requires harmonization of product testing and manufacturing in order to interpret the clinical trial results. Decentralized manufacturing is quite challenging since all centers should use the same manufacturing protocol, the same or comparable in-process and lot release assays and the quality programs from each center must work closely together. Consequently, manufacturing cellular therapies using a decentralized model is in many ways more difficult than manufacturing cells in a single centralized facility. Before an academic center decides to establish a point-of-care cell processing laboratory, they should consider all costs associated with such a program. For many academic cell processing centers, point-of-care manufacturing may not be a good investment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.