Overview of dominantly inherited AD and top‐line DIAN‐TU results of solanezumab and gantenerumab
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease (AD) prevention trials aim to intervene prior to significant neuronal loss, brain damage, and symptom onset to delay or slow cognitive decline. In dominantly inherited AD (DIAD), mutation carriers develop symptomatic AD at predictable ages with near 100% penetrance. In 2012, the Dominantly Inherited Alzheimer Network Trials Unit Adaptive Prevention Trial (DIAN‐TU APT) platform launched a double‐blind, randomized, placebo‐controlled, parallel group trial of two anti‐amyloid‐beta monoclonal antibodies with two different antigenic targets, gantenerumab and solanezumab (NCT01760005). The DIAN‐TU scientific development, implementation of the first AD prevention trial, trial challenges and opportunities, including dose escalation, and top‐line results will be presented. Method DIAN was established in 2008 in response to a call from the National Institute of Aging to establish a network to study DIAD and enable future clinical trials. Successive breakthroughs in understanding disease processes enabled the launch of the DIAN‐TU adaptive prevention trial, a global adaptive platform trial supporting testing multiple drugs in parallel. The DIAN‐TU partners include patients and families at risk for DIAD, global academic researchers, the NIH, Alzheimer’s Association, philanthropic supporters, the DIAN‐TU Pharma Consortium, and pharmaceutical companies with drugs being tested. Important milestones include developing a platform to enable a comprehensive efficient treatment trial for this rare population, adding tau PET as part of AMP AD, adapting dosing mid‐trial and extending the original biomarker trial to continue randomized dosing to test a cognitive endpoint until the last patient reaches 4 years, developing a disease progression statistical model and inclusion of DIAN observational data to increase the power to determine drug effects. Result The primary and key secondary outcomes of the DIAN‐TU trial will be presented for each therapy in the context of targeting amyloid‐beta at pre‐clinical and clinically symptomatic stages of disease. Conclusion These results inform about AD hypotheses, timing of treatment and the prospect of slowing, or preventing AD in DIAD and sporadic 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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".