48 Phase 2 studies of dianhydrogalactitol (VAL-083) in patients with glioblastoma, MGMT-unmethylated
Bibliographic record
Abstract
Current standard-of-care for glioblastoma (GBM) includes surgery, radiation and temozolomide. Most tumors recur within a year from diagnosis and median survival for recurrent GBM (rGBM) is 3-9 months. Unmethylated promoter status for O6-methylguanine-DNA-methyltransferase (MGMT) is a validated biomarker for temozolomide-resistance, exhibited by most GBM patients. VAL-083 is a DNA-targeting agent with a mechanism-of-action that is independent of MGMT. VAL-083 overcomes temozolomide-resistance in GBM cell-lines, cancer stem cells, and in vivo models. VAL-083 readily crosses the blood-brain barrier and accumulates in brain-tumor tissue. We recently completed a VAL-083 dose-escalation trial in temozolomide- and bevacizumab-refractory rGBM and determined that 40mg/m2/day given intravenously on days 1,2,3 of a 21-day cycle is generally well-tolerated. This dosing regimen was selected for subsequent GBM trials, including an ongoing single-arm, biomarker-driven Phase 2 trial (N=48) in temolozomide-refractory, bevacizumab-naïve rGBM , MGMT-unmethylated (Clinicaltrials.gov:NCT02717962). The primary objective of this study is to determine if VAL-083 improves OS compared to a historical control of 7.15 months for MGMT-unmethylated rGBM patients treated with lomustine (EORTC26101). In addition, another single-arm, biomarker-driven, Phase 2 study (N=25) of VAL-083 in combination with radiotherapy in newly diagnosed GBM, MGMT-unmethylated is ongoing (Clinicaltrials.gov:NCT03050736). This trial aims to determine a dose for further study of VAL-083 in combination with radiotherapy and explore if VAL-083 improves PFS and OS compared to historical results in newly diagnosed GBM. Enrollment and safety data updates will be provided at the meeting. The results of these studies, if successful, may support VAL-083 as part of a new chemotherapeutic treatment paradigm for GBM.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".