P3‐036: REPURPOSING OF MONTELUKAST FOR THE TREATMENT OF ALZHEIMER'S DISEASE: INTELGENX INITIATES PHASE 2A MONTELUKAST VERSAFILM™ CLINICAL TRIAL IN ALZHEIMER'S PATIENTS
Bibliographic record
Abstract
As life expectancy increases effective treatments for age related neurodegenerative diseases have become a primary research focus for the pharmaceutical industry. It was recently demonstrated that montelukast, a leukotriene receptor antagonist, improves cognitive performance in animal models. A second group found that patients prescribed montelukast during their lives experienced statistically lowered instances of neurodegenerative diseases. These studies indicate a need to further evaluate how montelukast may be improving cognitive impairment related to neurodegenerative diseases in a larger population setting. IntelGenx is working to repurpose Montelukast as a therapeutic to treat neurodegenerative diseases by re-formulating the drug into an oral film-based product. In a recent Phase 1 study, IntelGenx demonstrated that an oral film formulation of Montelukast is safe and tolerable in healthy subjects, reduces the first-pass-effect and has a 52% higher bioavailability compared to the regular Montelukast tablet. 1-Marschallinger J., Aigner L., Nat. Comm 2015, 6, 8466, 2- Grinde B., Engdahl B., Immunity & Ageing, 2017, 14:20. Based on this pre-clinical data IntelGenx Corp. has initiated a Phase 2a proof of concept (“POC”) Montelukast VersaFilm™ clinical trial in Alzheimer's patients, following clearance of the Clinical Trial Application by Health Canada. The Phase 2a Montelukast Versafilm™ clinical trial is a randomized, double-blind, placebo controlled POC study that will enroll approximately 70 subjects with mild to moderate Alzheimer's Disease across eight Canadian research sites. The primary study objectives will be to evaluate the safety, feasibility, tolerability, and efficacy of Montelukast buccal film following daily dosing for 26 weeks. This study will begin by focussing on the development of tools for quantifying improvement using cognitive assays combined with functional assessment. This poster will outline our plans for performing the Phase II clinical study as well as discuss our methods of evaluation.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".