August 7, 2025
AAIC 2025 showcased an Alzheimer’s research community entering a new era. Sponsors are advancing earlier-phase trials, exploring a wider range of treatment modalities, and embracing biomarker-driven strategies for more targeted intervention. Yet while the science is accelerating, trial infrastructure is struggling to keep pace. Across sessions, speakers emphasized the need for better tools—like simulation and synthetic data—to support earlier decisions, optimize subgroup analyses, and adapt designs with greater confidence.
What Stood Out at AAIC 2025
1. Biomarker Momentum: Promise, Accessibility, and Open Questions
Multiple sessions focused on emerging biomarkers such as p-tau217, plasma GFAP, and digital measures, that make earlier and less invasive detection of dementia possible. Many of these biomarkers can now be measured in the blood, rather than through PET scans or lumbar punctures. Amyloid and tau positivity can precede symptoms by 15-20 years, reinforcing the urgent need for earlier interventions. However, researchers are still actively examining which biomarkers are most predictive of future cognitive and functional changes, including when those changes might occur and how severe they might be.
2. Early Treatment Requires Early Confidence
Speakers emphasized that anti-amyloid therapies such as lecanemab and donanemab work best at the earliest disease stages—possibly even pre-MCI. Yet, selecting the right patients remains a challenge due to the lack of sensitive cognitive diagnostics in early-stage disease. Early-phase trial strategies now require robust, evidence-based ways to assess whether a treatment signal is real—before advancing to pivotal studies.
3. Trial Design Needs a Modern Upgrade
Several presenters shared statistical strategies for improving trial efficiency, but even with more innovative designs, one key challenge looms large: enrolling enough patients, especially in early stages. As sponsors begin targeting patients in the earliest stages of disease, many of whom may not yet show symptoms, recruitment becomes exponentially harder. Sessions also highlighted the need for more flexible trial infrastructure and design strategies that can accommodate evolving biomarkers, eligibility criteria, and endpoints.
Our Take: Making Every Data Point Count in Alzheimer’s Trials
This year, we shared new research on how digital twins—AI-generated forecasts of individual patient outcomes—can optimize composite scores for greater sensitivity in early Alzheimer’s trials. Composite scores frequently serve as primary or secondary endpoints in early-phase studies but can be noisy or incomplete, sometimes capturing only a subset of relevant clinical change, such as cognition but not function. This allows sponsors to identify and reweight the most informative assessment items, tailoring composite scores to better detect true treatment effects.
Key Takeaways
- Digital twins forecast outcomes at the patient level, enabling reweighting of score components for stronger signal.
- Optimized scores improve power without requiring additional patients or changes to trial design.
- Simulation results showed power gains from 25–50% to 65% in moderately powered studies, and from 44–80% to 92% in better-powered studies.
- Composite scores tailored to the study population can better reflect meaningful clinical change, especially in early-phase populations..
- More sensitive endpoints mean clearer insights, faster interpretation of treatment effects, and greater confidence in trial outcomes.
The Path Ahead
We left AAIC energized by the momentum in the Alzheimer’s space and encouraged by the conversations we had with biopharma teams, regulators, and researchers who share our urgency.
There’s never been a more critical time to invest in smarter trial tools—and no better way to do so than by partnering with experts who’ve already built them.
