Effects of the Acetylcholine Release Agent ST101 with Donepezil in Alzheimer’s Disease: A Randomized Phase 2 Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: ST101, an acetylcholine release agent with efficacy in rodent memory and cognition models, was assessed for clinical safety and efficacy. METHODS: A phase 2 double blind, placebo-controlled study enrolled 210 AD patients (MMSE 10-20) on 10 mg donepezil QD. Patients received ST101 (10, 60, or 120 mg QD) or placebo for 12 weeks. The primary endpoint was change in cognitive function measured by ADAS-cog in the modified Intent To Treat (MITT) population and the Per Protocol (PP) population. RESULTS: Mean ADAS-cog change favored ST101 over placebo in the MITT population (p = 0.0957, one-sided) and in the PP population (p = 0.0434, one-sided, ∼1.5 point drug-placebo difference) comparing all ST101 dose groups combined to placebo. Among secondary and exploratory outcome measures the ADCS-CGIC also showed a beneficial trend (p = 0.0294, one-sided). In a post-hoc analysis, the subgroup with more severe disease (MMSE 10-17) showed a dose response in the ADAS-cog with the greatest efficacy at 120 mg (p = 0.0067, one sided). No significant ST101-related safety concerns were identified. CONCLUSION: The study supports the possibility that ST101, in patients receiving a stable dose of donepezil, may provide additional symptomatic benefit in moderate AD.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".