Gueorguieva I, Willis BA, Chua L, Chow K, Ernest CS, Wang J, Shcherbinin S, Sims JR, Chigutsa E. Donanemab exposure and efficacy relationship using modeling in Alzheimer's disease.
Alzheimers Dement (N Y) 2023;
9:e12404. [PMID:
37388759 PMCID:
PMC10301702 DOI:
10.1002/trc2.12404]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/19/2023] [Accepted: 05/31/2023] [Indexed: 07/01/2023]
Abstract
INTRODUCTION
Donanemab is an amyloid-targeting therapy that specifically targets brain amyloid plaques. The objective of these analyses was to characterize the relationship of donanemab exposure with plasma biomarkers and clinical efficacy through modeling.
METHODS
Data for the analyses were from participants with Alzheimer's disease from the phase 1 and TRAILBLAZER-ALZ studies. Indirect-response models were used to fit plasma phosphorylated tau 217 (p-tau217) and plasma glial fibrillated acidic protein (GFAP) data over time. Disease-progression models were developed using pharmacokinetic/pharmacodynamic modeling.
RESULTS
The plasma p-tau217 and plasma GFAP models adequately predicted the change over time, with donanemab resulting in decreased plasma p-tau217 and plasma GFAP concentrations. The disease-progression models confirmed that donanemab significantly reduced the rate of clinical decline. Simulations revealed that donanemab slowed disease progression irrespective of baseline tau positron emission tomography (PET) level within the evaluated population.
DISCUSSION
The disease-progression models show a clear treatment effect of donanemab on clinical efficacy regardless of baseline disease severity.
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