The Safety Profile of Pridopidine, a Novel Sigma-1 Receptor Agonist for the Treatment of Huntington’s Disease
Bibliographic record
Abstract
BACKGROUND: Huntington's disease (HD) is a rare, fatal, chronic progressive neurodegenerative disorder with a significant unmet medical need for effective treatments. Pridopidine is a novel, first-in-class, highly selective and potent sigma-1 receptor (S1R) agonist in development for HD. Pridopidine has been extensively studied in adult HD across the full spectrum of disease severity and age ranges, and its safety profile has been characterized in approximately 1600 participants across multiple studies and a broad range of doses. The specific objective of this study was to gain an in-depth understanding of pridopidine's safety profile at the recommended human dose of 45 mg twice daily (bid) in patients with HD. METHODS: An integrated safety analysis of pooled data from 1067 patients with HD enrolled in four double-blind, placebo-controlled studies was performed. The safety profile of pridopidine was compared with placebo. RESULTS: Pridopidine was found to be generally safe and well tolerated with an adverse event (AE) profile comparable to that of placebo. Moreover, there were no significant differences observed in the safety profile of pridopidine compared with placebo when analyzed by age, sex, baseline total functional capacity (TFC), cytosine-adenine-guanine (CAG) repeat length, use of antidopaminergic medications (ADMs), and region. CONCLUSIONS: The integrated analysis replicated and corroborated the good safety profile observed in the individual studies. Despite the larger sample size, no new safety signals emerged. Long-term exposure to pridopidine, up to 6.5 years in open-label extension studies, revealed no new safety concerns, supporting its potential for long-term use in patients with HD.
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 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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".