ArticleCPT: pharmacometrics & systems pharmacology2023
Quantitative systems pharmacology model of the amyloid pathway in Alzheimer's disease: Insights into the therapeutic mechanisms of clinical candidates.
Article in CPT: pharmacometrics & systems pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Quantitative Systems Pharmacology Models of Anti-Amyloid Treatments for Alzheimer's Disease: A Systematic Review.CPT: pharmacometrics & systems pharmacology · 2026Pooled it
- CSF α-synuclein seed amplification assay positivity identifies a distinct soluble amyloid-β profile linked to fibrillar amyloid burden and structural neurodegeneration.Research square · 2026Article
- Neuro-Dynamic Quantitative Systems Pharmacology (QSP) model describing Alzheimer's disease pathophysiology and treatment effects.NPJ systems biology and applications · 2026Article
- Model-Informed Drug Development: Addressing the Critical Need for Training in the Promising New Field.Delaware journal of public health · 2026Article
- Mechanistic modeling of amyloid dynamics relating to Alzheimer's disease progression.Frontiers in aging neuroscience · 2026Article
- Mining the gaps: Deciphering Alzheimer's biology through AI-driven reconciliation.The journal of prevention of Alzheimer's disease · 2025Article
- A Step-by-Step Workflow for Performing In Silico Clinical Trials With Nonlinear Mixed Effects Models.CPT: pharmacometrics & systems pharmacology · 2025Article
- APOE4 genotypes and the trajectory of biomarkers, neuroimaging, and cognitive measures in Alzheimer's Disease: A mixed-effects disease progression model.Journal of pharmacokinetics and pharmacodynamics · 2025Article
- A mechanistic model of pure and lipidic α-synuclein aggregation for advancing Parkinson's therapies.Communications chemistry · 2025Article
- Virtual patients inspired by multiomics predict the efficacy of an anti-IFNα mAb in cutaneous lupus.iScience · 2025Article
- Application of model-informed drug development (MIDD) for dose selection in regulatory submissions for drug approval in Japan.Journal of pharmacokinetics and pharmacodynamics · 2025Article
- Quantitative Systems Pharmacology Development and Application in Neuroscience.Handbook of experimental pharmacology · 2025Review
- On the Therapeutic Use of Monoclonal Antibodies Against Amyloid Plaques in Older Adults with Down Syndrome: A Narrative Review and Perspective.Brain sciences · 2024Review
- Fourteenth American Conference on Pharmacometrics (ACoP14) - Innovation and Diversity: Redefining Pharmacometrics.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Analysis of clinical failure of anti-tau and anti-synuclein antibodies in neurodegeneration using a quantitative systems pharmacology model.Scientific reports · 2023Article
- A combined physiologically-based pharmacokinetic and quantitative systems pharmacology model for modeling amyloid aggregation in Alzheimer's disease.CPT: pharmacometrics & systems pharmacology · 2023Article
- Quantitative systems pharmacology model of the amyloid pathway in Alzheimer's disease: Insights into the therapeutic mechanisms of clinical candidates.CPT: pharmacometrics & systems pharmacology · 2023Article
Corrections and comments
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Authors and funding
16 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite considerable investment into potential therapeutic approaches for Alzheimer's disease (AD), currently approved treatment options are limited. Predictive modeling using quantitative systems pharmacology (QSP) can be used to guide the design of clinical trials in AD. This study developed a QSP model representing amyloid beta (Aβ) pathophysiology in AD. The model included mechanisms of Aβ monomer production and aggregation to form insoluble fibrils and plaques; the transport of soluble species between the compartments of brain, cerebrospinal fluid (CSF), and plasma; and the pharmacokinetics, transport, and binding of monoclonal antibodies to targets in the three compartments. Ordinary differential equations were used to describe these processes quantitatively. The model components were calibrated to data from the literature and internal studies, including quantitative data supporting the underlying AD biology and clinical data from clinical trials for anti-Aβ monoclonal antibodies (mAbs) aducanumab, crenezumab, gantenerumab, and solanezumab. The model was developed for an apolipoprotein E (APOE) ɛ4 allele carrier and tested for an APOE ɛ4 noncarrier. Results indicate that the model is consistent with data on clinical Aβ accumulation in untreated individuals and those treated with monoclonal antibodies, capturing increases in Aβ load accurately. This model may be used to investigate additional AD mechanisms and their impact on biomarkers, as well as predict Aβ load at different dose levels for mAbs with known targets and binding affinities. This model may facilitate the design of scientifically enriched and efficient clinical trials by enabling a priori prediction of biomarker dynamics in the brain and CSF.
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