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Center for Global Research Data

Identification of heterogeneity in Alzheimer’s disease clinical trials using computational modelling

Lead Investigator: Neil Oxtoby, University College London
Title of Proposal Research: Identification of heterogeneity in Alzheimer’s disease clinical trials using computational modelling
Vivli Data Request: 7232
Funding Source: UK Research and Innovation (UKRI) Medical Research Council grant number MR/S03546X/1
Potential Conflicts of Interest: None

Summary of the Proposed Research:

Alzheimer’s disease is the leading cause of dementia, which is becoming a global pandemic for the world’s ageing population, and currently affects 55 million people worldwide and will nearly triple by 2050. Alzheimer’s disease is devastating for patients, their families and carers, and the economy. Decades of experimental research into novel treatments have produced many new very promising drugs but none have been unequivocally proven to work in clinical trials.

Our computational research has revealed previously hidden subtypes and stages of Alzheimer’s disease progression. We believe that clinical trials should take this information into account when recruiting patients because it is likely that any given drug won’t work on all subtypes, nor at all stages of the disease. Here we propose to test this idea in data from a completed clinical trial known as TOMMORROW. If our idea works, we can then contribute to the success of future clinical trials to finding treatments for this devastating disease.

Requested Studies:

A Double Blind, Randomized, Placebo Controlled, Parallel Group Study to Simultaneously Qualify a Biomarker Algorithm for Prognosis of Risk of Developing Mild Cognitive Impairment Due to Alzheimer’s Disease (MCI Due to AD) and to Test the Safety and Efficacy of Pioglitazone (AD-4833 SR 0.8 mg QD) to Delay the Onset of MCI Due to AD in Cognitively Normal Subjects
Data Contributor: Takeda
Study ID: NCT01931566
Sponsor ID: AD-4833/TOMM40_301