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Record W4213298430 · doi:10.1093/neuonc/nox036.312

P09.57 Clinical trials of VAL-083 in patients with chemoresistant glioblastoma

2017· article· en· W4213298430 on OpenAlexaff
Jeffrey Bacha, Anne Steinø, Rachel Schwartz, John Langlands, Sarath Kanekal, L. Madero López, Destiny Brown

Bibliographic record

VenueNeuro-Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsDelmar (Canada)
Fundersnot available
KeywordsTemozolomideMedicineBevacizumabClinical trialOncologyInternal medicineGliomaPhases of clinical researchChemotherapyCancer research

Abstract

fetched live from OpenAlex

Glioblastoma (GBM) is the most common CNS tumor. Patients with recurrent GBM have few treatment options and dismal prognosis. O6-methylguanine-DNA-methyltransferase (MGMT) is correlated with resistance to standard of care treatment with temozolomide and poor patient outcomes. Dianhydrogalactitol (VAL-083) is a bi-functional alkylating agent with a distinct mechanism-of-action differentiating it from other alkylating agents used in the treatment of GBM and other CNS tumors. VAL-083 readily crosses the blood-brain barrier and accumulates in brain tumor tissue. VAL-083 has demonstrated MGMT-independent cytotoxicity in multiple GBM cell-lines and cancer stem cells and is able to overcome TMZ-resistance in vitro demonstrating a different mechanism of action. In multiple prior NCI-sponsored clinical trials VAL-083 showed promise against CNS tumors. We recently concluded a phase I/II clinical trial studying VAL-083 in recurrent GBM patients failing temozolomide and bevacizumab, and data suggests a potential for VAL-083 to offer clinically meaningful survival benefits in patients who have failed or are unlikely to respond to currently available chemotherapeutic regimens. In the phase I portion of the trial, VAL-083, 40 mg/m2/day x 3 every 21 days was well-tolerated and this dose was selected for study in the phase II expansion phase. We are initiating multiple clinical trials targeting adult patients with chemoresistant GBM due to MGMT expression. Enrollment is anticipated to be initiated in early 2017. These trials include i) a pivotal, randomized Phase 3 study measuring survival outcome compared to “physician’s choice” control, which, if successful, would serve as the basis for a New Drug Application (NDA) submission for VAL-083. The control arm will consist of a limited number of salvage chemotherapies currently utilized in bevacizumab-failed GBM. ii) A single-arm, biomarker-driven, Phase 2 study to determine if treatment of MGMT-unmethylated recurrent GBM with VAL-083 improves overall survival at 9 months, compared to historical control in bevacizumab-naïve patients (clinicaltrials.gov identifier: NCT02717962). iii) A single arm Phase 2 study to confirm the tolerability of DelMar’s dosing regimen in combination with radiotherapy and to explore the activity of VAL-083 in newly diagnosed MGMT-unmethylated GBM patients whose tumors are known to express high MGMT levels. The results of these studies may support a new treatment paradigm in chemotherapeutic regimens for the treatment of GBM. Enrollment updates and study design details will be presented at the meeting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.071
GPT teacher head0.407
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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