Approved research

The development of an Alzheimer's disease (AD) clinical trial simulator, parameter estimation from international patient cohorts and standardising epidemiological measurement platforms for cohort stud

Lay summary

AD is a progressive neurodegenerative disease, with no effective treatments or cure. The gold standard therapy would be preventative treatments, however, knowledge of the early stages of AD is limited. Over 98 percent of clinical trials of AD drug candidates have failed and the failure rate of AD clinical trials is far higher than that of trials in other therapy areas. The high variance in the measurement of cognition and diagnostic markers may be one of the most important reasons for the high failure rate of clinical trials of potential treatments against AD. In addition, treatments that are in fact efficacious may not be detected owing to the lack of accurate identification of measurable markers to detect earlier stages of AD. Mathematical, computational and statistical tools can be employed to investigate why AD clinical trials fail, to improve the design of trials of potential treatments and to enhance the chances of success. The development of a clinical trial simulator (CTS) over the following 12 months will enable the prediction of results in an actual AD clinical trial. We will use the requested data to determine the variance in the clinical outcome and aid the detection of potential sources of variance, to obtain better estimates for the CTS. A CTS could improve the accuracy of costly and timely clinical trials before they have begun which may help to understand the time course of the disease in more detail and ultimately benefit an aging society as a whole.