Emerging Drugs for Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract

 Horizon scan reports provide brief summaries of information regarding new and emerging health technologies. These technologies are identified through the CADTH Horizon Scanning Service as topics of potential interest to health care decision-makers in Canada. This Horizon Scan summarizes the available information regarding emerging drug therapies for the treatment of patients with amyotrophic lateral sclerosis.
 Amyotrophic lateral sclerosis (ALS) is a progressive fatal neurodegenerative disorder characterized by muscle weakness and wasting. ALS can be classified as sporadic (sALS), which accounts for 85% to 90% of the cases, or familial (fALS), which includes 10% to 15% of the cases.
 At present, 2 drugs are available in Canada for the treatment of patients with ALS, riluzole and edaravone. These 2 drugs provide modest benefits in terms of survival and function.
 Many treatments are currently in various stages of clinical development. Fasudil, ibudilast, inosine, and masitinib are drugs of interest as they have completed phase II, and some have initiated phase III, of their respective clinical development. Several other drugs are in clinical development and are briefly described in this report: AT-1501, CNM-Au8, Engensis, Pridopidine, Verdiperstat, and Zilucoplan.
 Emerging drugs for ALS pertain to different drug classes. Despite different mechanisms of action, these drugs all aim at providing a neuroprotective effect that will result in slowing of disease progression, maintenance of patient functional status, and improvement in patient survival.
 Of the 4 ALS drugs of interest in late-stage development, Fasudil, Ibudilast, and Inosine have completed phase II of clinical development.
 The estimated completion date for phase III of clinical development for Masitinib is December 2022.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".