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We describe a quantitative systems pharmacology (QSP) approach of the dynamics of A\u03b2 monomers, oligomers, protofibrils, and plaque using a detailed microscopic model of A\u03b2<jats:sub>40<\/jats:sub> and A\u03b2<jats:sub>42<\/jats:sub> aggregation and clearance of aggregated A\u03b2 by activated microglia cells, which is enhanced by the interaction of antibody\u2010bound A\u03b2. The model allows for the prediction of A\u03b2 positron emission tomography (PET) imaging load as measured by a standardized uptake value ratio. A physiology\u2010based pharmacokinetic model is seamlessly integrated to describe target exposure of monoclonal antibodies and simulate dynamics of cerebrospinal fluid (CSF) and plasma biomarkers, including CSF A\u03b2<jats:sub>42<\/jats:sub> and plasma A\u03b2<jats:sub>42<\/jats:sub>\/A\u03b2<jats:sub>40<\/jats:sub> ratio biomarkers. <jats:italic>Apolipoprotein E<\/jats:italic> genotype is implemented as a difference in microglia clearance. By incorporating antibody\u2010bound, plaque\u2010mediated macrophage activation in the perivascular compartment, the model also predicts the incidence of amyloid\u2010related imaging abnormalities with edema (ARIA\u2010E). The QSP platform is calibrated with pharmacological and clinical information on aducanumab, bapineuzumab, crenezumab, gantenerumab, lecanemab, and solanezumab, predicting adequately the change in PET imaging measured amyloid load and the changes in the plasma A\u03b2<jats:sub>42<\/jats:sub>\/A\u03b2<jats:sub>40<\/jats:sub> ratio while slightly overestimating the change in CSF A\u03b2<jats:sub>42<\/jats:sub>. ARIA\u2010E is well predicted for all antibodies except bapineuzumab. This QSP model could support the clinical trial design of different amyloid\u2010modulating interventions, define optimal titration and maintenance schedules, and provide a first step to understand the variability of biomarker response in clinical practice.<\/jats:p>","DOI":"10.1002\/psp4.12912","type":"journal-article","created":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T07:54:55Z","timestamp":1673510095000},"page":"444-461","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A combined physiologically\u2010based pharmacokinetic and quantitative systems pharmacology model for modeling amyloid aggregation in Alzheimer's disease"],"prefix":"10.1002","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9736-1800","authenticated-orcid":false,"given":"Hugo","family":"Geerts","sequence":"first","affiliation":[{"name":"Certara QSP\u2013UK  Canterbury UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mike","family":"Walker","sequence":"additional","affiliation":[{"name":"Certara QSP\u2013UK  Canterbury UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel","family":"Rose","sequence":"additional","affiliation":[{"name":"Certara QSP\u2013UK  Canterbury UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0696-9125","authenticated-orcid":false,"given":"Silke","family":"Bergeler","sequence":"additional","affiliation":[{"name":"Certara QSP\u2013UK  Canterbury UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Piet H.","family":"van der Graaf","sequence":"additional","affiliation":[{"name":"Certara QSP\u2013UK  Canterbury UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edgar","family":"Schuck","sequence":"additional","affiliation":[{"name":"Schrodinger Inc.  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