Systematic in silico analysis of clinically tested drugs for reducing amyloid‐beta plaque accumulation in Alzheimer's disease. Issue 9 (2nd May 2021)

• Record Type: Journal Article
• Authors: Madrasi, Kumpal; Das, Raibatak; Mohmmadabdul, Hafiz; Lin, Lin; Hyman, Bradley T.; Lauffenburger, Douglas A.; Albers, Mark W.; Rissman, Robert A.; Burke, John M.; Apgar, Joshua F.; Wille, Lucia; Gruenbaum, Lore; Hua, Fei
• Is Part Of: Alzheimer's & dementia. Volume 17:Issue 9(2021)
• Page Start: 1487
• Page End: 1498
• Publication Date: 2021-05-02
• Subjects: aducanumab -- amyloid beta pathway -- amyloid plaque reduction -- bapineuzumab -- crenezumab -- elenbecestat -- model‐informed drug development -- quantitative systems pharmacology model -- semagacestat -- solanezumab -- verubecestat; Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.12312
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Introduction: Despite strong evidence linking amyloid beta (Aβ) to Alzheimer's disease, most clinical trials have shown no clinical efficacy for reasons that remain unclear. To understand why, we developed a quantitative systems pharmacology (QSP) model for seven therapeutics: aducanumab, crenezumab, solanezumab, bapineuzumab, elenbecestat, verubecestat, and semagacestat. Methods: Ordinary differential equations were used to model the production, transport, and aggregation of Aβ; pharmacology of the drugs; and their impact on plaque. Results: The calibrated model predicts that endogenous plaque turnover is slow, with an estimated half‐life of 2.75 years. This is likely why beta‐secretase inhibitors have a smaller effect on plaque reduction. Of the mechanisms tested, the model predicts binding to plaque and inducing antibody‐dependent cellular phagocytosis is the best approach for plaque reduction. Discussion: A QSP model can provide novel insights to clinical results. Our model explains the results of clinical trials and provides guidance for future therapeutic development.