Efficacy of CPX‐351, (cytarabine:daunorubicin) liposome injection, against acute lymphoblastic leukemia (ALL) xenograft models of the Pediatric Preclinical Testing Program
Bibliographic record
Abstract
BACKGROUND: CPX-351, a liposomal formulation of cytarabine and daunorubicin co-encapsulated at an optimized synergistic 5:1 molar ratio, has demonstrated improved clinical outcomes over conventional cytarabine/daunorubicin treatment in a randomized phase 2 trial in patients with AML as well as superior efficacy against preclinical leukemia models when compared to the free drugs in combination. PROCEDURES: Given the promising phase 2 data, limited toxicities observed, and the known clinical activities of cytarabine/daunorubicin, we assessed the efficacy of CPX-351 against a panel of childhood ALL xenograft models. Plasma pharmacokinetics of cytarabine and daunorubicin following CPX-351 treatment were determined by HPLC in order to correlate efficacy with drug exposure. RESULTS: CPX-351, at a dose of 5 units/kg (corresponding to 5 mg/kg cytarabine and 2.2 mg/kg daunorubicin), was highly efficacious against all xenografts tested, inducing complete responses in four B-lineage xenografts and partial response in one T-lineage xenograft. These therapeutic responses were achieved with CPX-351 doses that provided drug exposures (based on Cmax and AUC) comparable to those observed in patients with AML. CONCLUSIONS: These results suggest that CPX-351 may be a promising chemotherapeutic to be utilized in the treatment of ALL and support its testing in pediatric patients with leukemia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".