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Record W2271210490 · doi:10.3233/jad-150414

Effects of the Acetylcholine Release Agent ST101 with Donepezil in Alzheimer’s Disease: A Randomized Phase 2 Study

2015· article· en· W2271210490 on OpenAlexaff
Serge Gauthier, Susan Rountree, Bárbara C Finn, Barbra LaPlante, Eckard Weber, Tilman Oltersdorf

Bibliographic record

VenueJournal of Alzheimer s Disease · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsMcGill University
Fundersnot available
KeywordsPlaceboDonepezilPopulationClinical endpointMedicineInternal medicinePharmacologyClinical trialDementiaDisease

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.067
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.303
Teacher spread0.285 · 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 teacher head, 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

Citations26
Published2015
Admission routes1
Has abstractyes

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