Phase I Pharmacologic and Pharmacodynamic Study of the Gamma Secretase (Notch) Inhibitor MK-0752 in Adult Patients With Advanced Solid Tumors
Bibliographic record
Abstract
PURPOSE: Aberrant Notch signaling has been implicated in the pathogenesis of many human cancers. MK-0752 is a potent, oral inhibitor of γ-secretase, an enzyme required for Notch pathway activation. Safety, maximum-tolerated dose, pharmacokinetics (PKs), pharmacodynamics, and preliminary antitumor efficacy were assessed in a phase I study of MK-0752. PATIENTS AND METHODS: MK-0752 was administered in three different schedules to patients with advanced solid tumors. Hair follicles were collected at higher dose levels to assess a gene signature of Notch inhibition. RESULTS: Of 103 patients who received MK-0752, 21 patients received a continuous once-daily dosing at 450 and 600 mg; 17 were dosed on an intermittent schedule of 3 of 7 days at 450 and 600 mg; and 65 were dosed once per week at 600, 900, 1,200, 1,500, 1,800, 2,400, 3,200, and 4,200 mg. The most common drug-related toxicities were diarrhea, nausea, vomiting, and fatigue. PKs (area under the concentration-time curve and maximum measured plasma concentration) increased in a less than dose proportional manner, with a half-life of approximately 15 hours. Significant inhibition of Notch signaling was observed with the 1,800- to 4,200-mg weekly dose levels, confirming target engagement at those doses. One objective complete response and an additional 10 patients with stable disease longer than 4 months were observed among patients with high-grade gliomas. CONCLUSION: MK-0752 toxicity was schedule dependent. Weekly dosing was generally well tolerated and resulted in strong modulation of a Notch gene signature. Clinical benefit was observed, and rational combination trials are currently ongoing to maximize clinical benefit with this novel agent.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".