Our objective was to develop a beta regression (BR) model to describe the longitudinal progression of the 11 item Alzheimer's disease (AD) assessment scale cognitive subscale (ADAS-cog) in AD patients in both natural history and randomized clinical trial settings, utilizing both individual patient and summary level literature data. Patient data from the coalition against major diseases database (3,223 patients), the Alzheimer's disease neruroimaging initiative study database (186 patients), and summary data from 73 literature references (representing 17,235 patients) were fit to a BR drug-disease-trial model. Treatment effects for currently available acetyl cholinesterase inhibitors, longitudinal changes in disease severity, dropout rate, placebo effect, and factors influencing these parameters were estimated in the model. Based on predictive checks and external validation, an adequate BR meta-analysis model for ADAS-cog using both summary-level and patient-level data was developed. Baseline ADAS-cog was estimated from baseline MMSE score. Disease progression was dependent on time, ApoE4 status, age, and gender. Study drop out was a function of time, baseline age, and baseline MMSE. The use of the BR constrained simulations to the 0-70 range of the ADAS-cog, even when residuals were incorporated. The model allows for simultaneous fitting of summary and patient level data, allowing for integration of all information available. A further advantage of the BR model is that it constrains values to the range of the original instrument for simulation purposes, in contrast to methodologies that provide appropriate constraints only for conditional expectations.

Failures in trials for Alzheimer's disease (AD) may be attributable to inadequate dosing, population selection, drug inefficacy, or insufficient design optimization. The Coalition Against Major Diseases (CAMD) was formed in 2008 to develop drug development tools (DDT) to expedite drug development for AD and Parkinson's disease. CAMD led a process that successfully advanced a clinical trial simulation (CTS) tool for AD through the formal regulatory review process at the US Food and Drug Administration (FDA) and European Medicines Agency (EMA).

Exposure-response relationships for efficacy were inconsistent across exposure metrics; model-predicted cycle 1 C showed the strongest exposure-response trend. The Q1 subgroup based on model-predicted cycle 1 C had numerically similar or better OS and PFS versus control following covariate adjustment. The approved T-DM1 dose (3.6 mg/kg every 3 weeks) has a positive benefit-risk ratio versus control, even for the T-DM1 Q1 subgroup.

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Exposure-response relationships for efficacy were inconsistent across exposure metrics. HRs for survival in patients in the lowest T-DM1 exposure quartile vs. matched TPC-treated patients suggest that, compared with TCP, the approved T-DM1 dose is unlikely to be detrimental to patients with low exposure.