Can we do better in developing new drugs for Alzheimer's disease?
Bibliographic record
Abstract
The past 30 years have seen multiple attempts at demonstrating the safety and efficacy of drugs for Alzheimer's disease (AD), predominantly to improve symptoms. Only five drugs (tacrine, donepezil, rivastigmine, galantamine, memantine) have obtained regulatory approval in most countries. Their cost-effectiveness from a societal perspective has not been universally recognized, and anybody who thinks these drugs are useful for individual patients will have to agree that the improvement above the starting point of treatment is moderate. Most of the benefit has been in slowing down progression of symptoms rather than a readily detectable improvement above baseline. There have also been attempts at arresting progression of AD, but all have failed until now. Should we change our approach to developing new drugs for AD so as to move forward? This review will highlight some options to consider in the development of future drugs for AD, with emphasis on strategies to prevent AD or arrest its progression.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".