A Multi-Arm Phase I Study of the PI3K/mTOR Inhibitors PF-04691502 and Gedatolisib (PF-05212384) plus Irinotecan or the MEK Inhibitor PD-0325901 in Advanced Cancer
Bibliographic record
Abstract
BACKGROUND: This phase I, four-arm, open-label study (NCT01347866) evaluated the PI3K/mTOR inhibitors PF-04691502 (arms A, B) and gedatolisib (PF-05212384; arms C, D) in combination with the MEK inhibitor PD-0325901 (arm A, D) or irinotecan (arm B, C) in patients with advanced solid tumors. OBJECTIVES: Primary endpoint was dose-limiting toxicity with each combination. Secondary endpoints included safety, pharmacokinetics and preliminary antitumor activity. PATIENTS AND METHODS: Dose escalation followed a 3 + 3 design in arm C and a zone-based design in arm D. RESULTS: was estimated to be 110 mg weekly and for the combination with PD-0325901 was not reached at the highest dose evaluated (gedatolisib 154 mg weekly). Plasma concentrations of gedatolisib were generally similar across dose groups in arm C (with irinotecan) and arm D (with PD-0325901). Frequent dose delays or dose reductions were required for both combinations, potentially preventing sustained therapeutic drug concentrations. Gedatolisib plus irinotecan produced a response rate of ~5% and clinical benefit in 16% of patients with advanced colorectal cancer (progression-free survival, 2.8 months). Preliminary evidence of clinical activity was observed with gedatolisib plus PD-0325901 in patients with ovarian cancer (three partial responses, n = 5) or endometrial cancer (one partial response, n = 1) and KRAS mutations. CONCLUSIONS: Further evaluations of gedatolisib are warranted in patients with advanced solid malignancies.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".