Industry’s Giant Leap Into Cellular Therapy: Catalyzing Chimeric Antigen Receptor T Cell (CAR-T) Immunotherapy
Bibliographic record
Abstract
PURPOSE OF REVIEW: We describe the significant technological leap from bench to bedside that was achieved through a strong academic-industry collaboration between dedicated clinicians and researchers at the University of Pennsylvania, the Children's Hospital of Philadelphia, and Novartis to commercialize the chimeric antigen receptor T cell (CAR-T) therapy tisagenlecleucel (CTL019; Kymriah®; Novartis Pharma AG, Basel, Switzerland). RECENT FINDINGS: Tisagenlecleucel was the first CAR-T therapy and the first gene therapy to receive US Food and Drug Administration approval in 2017, with an initial indication for pediatric and young adult patients with relapsed or refractory (r/r) acute lymphoblastic leukemia, followed by approval in May 2018 for a second indication in adult patients with r/r diffuse large B cell lymphoma. Subsequent approvals in the European Union, Switzerland, and Canada soon followed. The tisagenlecleucel success story represents the development and commercialization of a first-of-its-kind personalized cellular therapy with a manufacturing process that supports commercial production and ongoing global clinical trials in a growing number of countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".