Disease Modeling and Model‐Based Meta‐Analyses to Define a New Direction for a Phase III Program of Gantenerumab in Alzheimer’s Disease

Abstract

Selecting the right dose is a significant challenge in designing clinical development programs, especially for slowly progressing diseases lacking predictive biomarkers of efficacy that may require long‐term treatment to assess clinical benefit. Gantenerumab, a fully human monoclonal antibody (mAb) that binds to aggregated amyloid‐beta, was tested in two 24‐month phase III studies (NCT01224106, NCT02051608) in participants with prodromal and mild Alzheimer’s disease (AD), respectively. Dosing in the first phase III study was suspended after a preplanned interim futility analysis in 2014. Subsequently, a dose–response relationship was observed in a subgroup of fast AD progressors that, together with contemporary aducanumab (another anti–amyloid‐beta mAb) data, indicated higher doses may be needed for clinical efficacy. The gantenerumab phase III studies were therefore transformed into dose‐finding, open‐label extension (OLE) trials. Two exposure–response models were developed to support dose selection via simulations for the OLEs: a pharmacokinetics (PK)/PET (positron emission tomography) model describing amyloid removal using PET data from low‐dose gantenerumab and high‐dose aducanumab, and a PK/ARIA‐E (amyloid‐related imaging abnormalities‐edema) model describing the occurrence of ARIA‐E events leveraging an existing bapineuzumab model. Multiple regimens were designed to gradually up‐titrate participants to the target dose of 1,200 mg gantenerumab every 4 weeks to mitigate the increased risk of ARIA‐E events that may be associated with higher doses of anti–amyloid‐beta antibodies. Favorable OLE data that matched well with model predictions supported the decision to continue the gantenerumab clinical development program and further apply model‐based analytical techniques to optimize the design of new phase III studies.