Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's Disease

ABSTRACT To inform an efficient development of new investigational anti‐amyloid beta (anti‐Aβ) monoclonal antibodies (mAbs), a modeling‐and‐simulation‐based strategy was proposed. A general modeling framework that links drug exposures to the time course of amyloid plaque removal and amyloid‐related...

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Main Authors: Sagar S. Bachhav, Ana Victoria Ponce‐Bobadilla, Diana Clausznitzer, Sven Stodtmann, Hao Xiong
Format: Article
Language:English
Published: Wiley 2025-07-01
Series:CPT: Pharmacometrics & Systems Pharmacology
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Online Access:https://doi.org/10.1002/psp4.70038
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author Sagar S. Bachhav
Ana Victoria Ponce‐Bobadilla
Diana Clausznitzer
Sven Stodtmann
Hao Xiong
author_facet Sagar S. Bachhav
Ana Victoria Ponce‐Bobadilla
Diana Clausznitzer
Sven Stodtmann
Hao Xiong
author_sort Sagar S. Bachhav
collection DOAJ
description ABSTRACT To inform an efficient development of new investigational anti‐amyloid beta (anti‐Aβ) monoclonal antibodies (mAbs), a modeling‐and‐simulation‐based strategy was proposed. A general modeling framework that links drug exposures to the time course of amyloid plaque removal and amyloid‐related imaging abnormalities characterized by edema and effusion (ARIA‐E) was developed based on publicly available data on aducanumab, lecanemab, and donanemab. A non‐linear mixed effect model with shared model parameters described the dose response data from aducanumab, lecanemab, and donanemab studies after adjusting for different potency for different antibodies, which allowed the rate of amyloid plaque removal to vary by drug. A time‐to‐event model was developed to describe ARIA‐E incidence. The model assumes that ARIA‐E incidence rate is dependent on the rate of amyloid plaque removal with a drug‐dependent scaling factor linking amyloid plaque removal rate and treatment‐dependent hazard. Simulations of amyloid plaque removal and ARIA‐E for a hypothetical anti‐Aβ mAb based on certain assumptions and scenarios provided insights into possible outcomes. Overall, the meta‐analysis of published data on existing anti‐Aβ mAbs could be utilized to model exposure‐response relationships and the time course of amyloid plaque removal and ARIA‐E incidence of new anti‐Aβ mAbs and to inform the design of early clinical trials for them.
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spelling doaj-art-e6c6a8d1e1944997864ca3048cfeb5f22025-08-20T03:12:24ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062025-07-011471191120010.1002/psp4.70038Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's DiseaseSagar S. Bachhav0Ana Victoria Ponce‐Bobadilla1Diana Clausznitzer2Sven Stodtmann3Hao Xiong4Clinical Pharmacology AbbVie Inc North Chicago Illinois USAClinical Pharmacology AbbVie Deutschland GmbH Co. KG Ludwigshafen am Rhein GermanyClinical Pharmacology AbbVie Deutschland GmbH Co. KG Ludwigshafen am Rhein GermanyClinical Pharmacology AbbVie Deutschland GmbH Co. KG Ludwigshafen am Rhein GermanyClinical Pharmacology AbbVie Inc North Chicago Illinois USAABSTRACT To inform an efficient development of new investigational anti‐amyloid beta (anti‐Aβ) monoclonal antibodies (mAbs), a modeling‐and‐simulation‐based strategy was proposed. A general modeling framework that links drug exposures to the time course of amyloid plaque removal and amyloid‐related imaging abnormalities characterized by edema and effusion (ARIA‐E) was developed based on publicly available data on aducanumab, lecanemab, and donanemab. A non‐linear mixed effect model with shared model parameters described the dose response data from aducanumab, lecanemab, and donanemab studies after adjusting for different potency for different antibodies, which allowed the rate of amyloid plaque removal to vary by drug. A time‐to‐event model was developed to describe ARIA‐E incidence. The model assumes that ARIA‐E incidence rate is dependent on the rate of amyloid plaque removal with a drug‐dependent scaling factor linking amyloid plaque removal rate and treatment‐dependent hazard. Simulations of amyloid plaque removal and ARIA‐E for a hypothetical anti‐Aβ mAb based on certain assumptions and scenarios provided insights into possible outcomes. Overall, the meta‐analysis of published data on existing anti‐Aβ mAbs could be utilized to model exposure‐response relationships and the time course of amyloid plaque removal and ARIA‐E incidence of new anti‐Aβ mAbs and to inform the design of early clinical trials for them.https://doi.org/10.1002/psp4.70038amyloid betamodel informed drug developmentmodel‐based meta‐analysis
spellingShingle Sagar S. Bachhav
Ana Victoria Ponce‐Bobadilla
Diana Clausznitzer
Sven Stodtmann
Hao Xiong
Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's Disease
CPT: Pharmacometrics & Systems Pharmacology
amyloid beta
model informed drug development
model‐based meta‐analysis
title Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's Disease
title_full Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's Disease
title_fullStr Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's Disease
title_full_unstemmed Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's Disease
title_short Use of Model‐Based Meta‐Analysis to Inform the Design of Early Clinical Trials of Anti‐Amyloid Beta Therapies in Alzheimer's Disease
title_sort use of model based meta analysis to inform the design of early clinical trials of anti amyloid beta therapies in alzheimer s disease
topic amyloid beta
model informed drug development
model‐based meta‐analysis
url https://doi.org/10.1002/psp4.70038
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