A0474
Title: Innovative precision medicine methods in subgroup identification for Alzheimers disease
Authors: Lei Liu - Washington University in St. Louis (United States) [presenting]
Abstract: Alzheimer's disease (AD) is a progressive, degenerative disorder of the brain and is the most common form of dementia of ageing. Developing new and more effective medications to treat Alzheimer's disease remains a high priority. However, considerable heterogeneity exists among people with Alzheimer's disease, which might affect their reactions to medications differently. To improve the safety, efficacy, and efficiency of Alzheimer's treatment medications, it is important to identify and treat patients who are likely to respond best to a particular medication. Precision medicine, which uses individual features to diagnose and treat disease, is of growing interest in Alzheimer's treatment. The aim is to develop new machine-learning methods to select predictive biomarkers and identify subgroups of patients who showed an enhanced treatment effect in a recently completed AD trial. The predictive biomarkers can identify patients more likely to benefit from treatment. Subgroups will be found by defining a combination of multiple predictive biomarkers through their interactions with treatment.
