Neuropharmacological Study of Posaconazole for Glioblastoma: A Phase 0 Clinical Trial Protocol
Bibliographic record
Abstract
BACKGROUND: Glioblastoma (GBM) is the most common malignant primary brain tumor with a universally poor prognosis. GBMs express elevated levels of hexokinase 2 (HK2), catalyzing the critical step in glycolysis and influencing several oncogenic pathways. Previous preclinical work has suggested a role for repurposed posaconazole (PCZ) in downregulating HK2 activity, reducing lactate and pyruvate production, interfering with tumor cell metabolism, and increasing mouse survival. OBJECTIVE: To establish brain tumor penetrance, neuropharmacokinetic profile, and mechanistic effect on tumor cell metabolism of PCZ in adults with GBM. METHODS: This is an open label, nonrandomized, parallel arm trial involving patients with GBM. Cohorts will receive PCZ (intervention, n = 5) or will not receive PCZ (control, n = 5), followed by tumor resection and microdialysis catheter placement. Dialysate, plasma, and tumor samples will be analyzed for lactate and pyruvate concentrations. Tumor samples will also be assessed for PCZ concentration, HK2 expression, angiogenesis, and apoptosis. PCZ's neuropharmacokinetics will be determined based on the concentration vs time profile and area under the curve 0 to 24 hours of PCZ concentration in the brain interstitium. EXPECTED OUTCOMES: (1) Increased PCZ concentration in contrast-enhancing brain regions compared with nonenhancing regions; (2) inverse correlation between lactate/pyruvate and PCZ concentrations in dialysate samples from treated patients, over time; and (3) decreased HK2 activity in PCZ-treated tumor samples. DISCUSSION: A successful trial will support the decision to proceed to advanced phase trials. Any tumor penetration by PCZ, with concomitant effect on glycolysis, warrants further in-depth analysis, as therapeutic options for these deadly tumors are currently limited.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".