ReviewCurrent hematologic malignancy reports2019
Towards Automated Manufacturing for Cell Therapies.
Review in Current hematologic malignancy reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 25 citations in OpenAlex.
- Performance of a modular robotic cluster matches skilled human operators for complex cell therapy manufacturing tasks.International journal of pharmaceutics: X · 2026Article
- A decade of innovation in healthcare: Automation, bio-printing and digital twin technologies for personalized therapies.International journal of pharmaceutics: X · 2026Review
- Immunomodulatory strategies for ex vivo immune cell expansion in adoptive cell therapy: translational and regulatory considerations for clinical manufacturing.Frontiers in immunology · 2026Review
- Challenges and opportunities of human iPSC-derived NK as "Off-the-shelf" cellular therapies.Journal of experimental & clinical cancer research : CR · 2025Review
- Cell-based immunotherapies for solid tumors: advances, challenges, and future directions.Frontiers in oncology · 2025Review
- Advances in manufacturing chimeric antigen receptor immune cell therapies.Seminars in immunopathology · 2024Review
- Translation of cell therapies to treat autoimmune disorders.Advanced drug delivery reviews · 2024Review
- The GibcoGene therapy · 2023Review
- Approach of resource expenditure estimation toward mechanization in the manufacturing of cell-based products.Regenerative therapy · 2022Article
- Use of Multi-Site Radiation Therapy for Systemic Disease Control.International journal of radiation oncology, biology, physics · 2021Review
- Production and Application of CAR T Cells: Current and Future Role of Europe.Frontiers in medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewMany cell therapy products are beginning to reach the commercial finish line and a rapidly escalating pipeline of products are in clinical development. The need to develop manufacturing capability that will support a successful commercial business model has become a top priority as many cell therapy developers look to secure long-term visions to enable both funding and treatment success. RECENT
findingsManufacturing automation is both highly compelling and very challenging at the same time as a key tactic to address quality, cost of goods, scale, and sustainability that are fundamental drivers for commercially viable manufacturing. This paper presents an overview and strategic drivers for application of automation to cell therapy manufacturing. It also explores unique automation considerations for patient-specific cell therapy (PSCT) where each full-scale lot is for one patient vs off-the-shelf cell therapy (OTSCT) where a full-scale lot will treat many patients, and finally some practical considerations for implementing automation.
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.