Advancements in Pharmacological Treatment of Alzheimer’s Disease: The Advent of Disease-Modifying Therapies (DMTs)
Bibliographic record
Abstract
The landscape of pharmacological treatment for Alzheimer's disease (AD) has undergone significant transformations with the advent of disease-modifying therapies (DMTs) targeting β-Amyloid (Aβ) accumulation, one of the hallmark pathologies of AD. The approval and market introduction of monoclonal antibodies mark the dawn of a new era in AD therapeutics as well. Furthermore, considerable progress has also been made in the development of new drugs targeting non-Aβ and non-Tau protein pathways. These advancements are key in tackling the root causes of AD, offering hope for treatments that both relieve symptoms and slow disease progression, improving patient outcomes and quality of life. This review aims to provide a comprehensive update on the advances in drug development and application for AD, including those currently in clinical trials and those already approved for the market to treat patients.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".