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Record W3016844795 · doi:10.3747/co.27.5283

Chimeric Antigen Receptor T Cell Therapy Comes to Clinical Practice

2020· review· en· W3016844795 on OpenAlexafffundvenueabout
Donna A. Wall, Joerg Krueger

Bibliographic record

VenueCurrent Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersHospital for Sick Children
KeywordsChimeric antigen receptorMedicineImmunotherapyCell therapyCancerLeukemiaT cellCancer immunotherapyImmunologyCancer researchImmune systemCellInternal medicineBiology

Abstract

fetched live from OpenAlex

Adoptive cellular therapy with chimeric antigen receptor T cells (car-ts) has recently received approval from Health Canada and the U.S. Food and Drug Administration after remarkable and durable remissions were seen in children with recurrent or refractory leukemia and adults with non-Hodgkin lymphoma-responses that were so impressive that a shift in the paradigm of care has now occurred for children with acute lymphoblastic leukemia. The concept behind car-t immunotherapy is that modification of a patient's own T cells to facilitate their localization to the cancer cell, with subsequent activation of the T cell effector mechanism and proliferation, will result in targeted killing of cancer cells. The car-ts are a novel drug in that the starting material for the manufacture of the car-t product comes from the patient, whose viable T cells are then genetically modified. Thus, collaboration is needed between the pharmaceutical companies, which must meet good manufacturing standards for each patient's unique product, and the treating sites. For regulators and health authorities, this new class of drugs requires new paradigms for assessment and approval. Treatments with car-ts require that institutions address unique logistics requirements and management of novel toxicities. The Hospital for Sick Children has had early experience with both the licensing of clinical trials and the introduction of the first commercial product. Here, we provide an overview of basic concepts and treatment, with caveats drawn from what we have learned thus far in bringing this new therapy to the clinical front line.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.006

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 head0.465
GPT teacher head0.614
Teacher spread0.149 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations37
Published2020
Admission routes4
Has abstractyes

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