ArticleNPJ systems biology and applications2025
Data-driven modeling of amyloid-β targeted antibodies for Alzheimer's disease.
Article in NPJ systems biology and applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Amyloid-beta fibrils as active contributors to synaptic dysfunction in Alzheimer's disease.Acta pharmacologica Sinica · 2026Article
- How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions.Bulletin of mathematical biology · 2026Review
- Data-driven modeling of spatiotemporal dynamics using multimodal imaging data.PLoS computational biology · 2026Article
- Learning patient-specific spatial biomarker dynamics via operator learning for Alzheimer's disease progression.NPJ systems biology and applications · 2026Article
- Article
- Utilizing fractional-order operator to Alzheimer's disease dynamics.Scientific reports · 2026Article
- Article
- Optimal control of monomers and oligomers degradation in an Alzheimer's disease model.Journal of mathematical biology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Alzheimer's disease (AD) is characterized by the accumulation of amyloid beta, which is strongly associated with disease progression and cognitive decline. Despite the approval of monoclonal antibodies targeting Aβ, optimizing treatment strategies while minimizing side effects remains a challenge. This study develops a mathematical framework to model Aβ aggregation dynamics, capturing the transition from monomers to higher-order aggregates, including protofibrils, toxic oligomers, and fibrils, using mass-action kinetics and coarse-grained modeling. Parameter estimation, sensitivity analysis, and data-driven calibration ensure model robustness. An optimal control framework is introduced to identify the optimal dose of the drug as a control function that reduces toxic oligomers and fibrils while minimizing adverse effects, such as amyloid-related imaging abnormalities (ARIA). The results indicate that Donanemab achieves the most significant reduction in fibrils. These findings provide a quantitative basis for optimizing AD treatments, providing valuable insight into the balance between therapeutic efficacy and safety.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.