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Record W4417329705 · doi:10.18609/cgti.2025.034

CAR-T manufacturing intensification: the next wave of CAR-T commercialization

2025· article· en· W4417329705 on OpenAlexaff
Alexey Bersenev, Emilie Kleiren, John Knighton, Paul Bowles

Bibliographic record

VenueCell and Gene Therapy Insights · 2025
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsOntario Medical Association
Fundersnot available
KeywordsCommercializationManufacturingManufacturing sectorAdvanced manufacturingIntersection (aeronautics)Health care

Abstract

fetched live from OpenAlex

Since the commercialization of the first CAR-T therapies, these revolutionary treatments have reshaped the landscape of cancer therapy, offering unprecedented hope to patients with hematologic malignancies. Here, a panel of industry and healthcare sector experts to discuss the critical intersection of commercialization strategies and manufacturing technology in advancing the next wave of CAR-T therapies to market. They explore the current industry status and the latest innovations that have the potential to optimize manufacturing processes for scale-up or scale-out, impacting cost of goods (CoGs) and manufacturing success to meet the growing demand and ensure broader patient access.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.299
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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