The path forward in Alzheimer's disease therapeutics: Reevaluating the amyloid cascade hypothesis
Bibliographic record
Abstract
Development of disease-modifying treatments for Alzheimer's disease (AD) has been challenging, with no drugs approved to date. The failures of several amyloid-targeted programs have led many to dismiss the amyloid beta (Aβ) hypothesis of AD. An antiamyloid antibody aducanumab recently showed modest but significant efficacy in a phase 3 trial, providing important validation of amyloid as a therapeutic target. However, the inconsistent results observed with aducanumab may be explained by the limited brain penetration and lack of selectivity for the soluble Aβ oligomers, which are implicated as upstream drivers of neurodegeneration by multiple studies. Development of agents that can effectively inhibit Aβ oligomer formation or block their toxicity is therefore warranted. An ideal drug would cross the blood-brain barrier efficiently and achieve sustained brain levels that can continuously prevent oligomer formation or inhibit their toxicity. A late-stage candidate with these attributes is ALZ-801, an oral drug with a favorable safety profile and high brain penetration that can robustly inhibit Aβ oligomer formation. An upcoming phase 3 trial with ALZ-801 in APOE4/4 homozygous patients with early AD will effectively test this amyloid oligomer hypothesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".