WIDESPREAD BRAIN DISTRIBUTION AND ROBUST BACE1 INHIBITION FOLLOWING INTRACEREBROVENTRICULAR INFUSION OF ANTI-BACE1 IN NON-HUMAN PRIMATES

Abstract

Background: The Alzheimer’s Disease Cooperative Study was founded in 1991 in response to an NIA RFA. The primary aim of the ADCS is to ‘advance research in the development of interventions that might be useful for treating, delaying, or preventing AD’. Toward that goal the ADCS has designed, managed, and analyzed over 20 large, multi-site AD clinical trials. The psychometric, clinical, neuroimaging, and biological data from these trials have been collected using a web-based electronic data capture (EDC) system developed by the ADCS Informatics Core. This system serves as a central hub used to coordinate the data management, quality assurance, and monitoring activities of thousands of affiliates across several continents. Methods: As the volume, complexity, and sources of data collected in the conduct of a clinical trial have increased, traditional data transfer and processing methods and tools have struggled to keep up. The use of data-intensive approaches to study enrollment, randomization, and monitoring, which require just-in-time data, have only exacerbated these challenges. One-time, end-of-study data transfers with cursory quality controls have been supplanted by the need for near real-time data flows that are subjected to a comprehensive battery of quality checks and must be rapidly integrated into the main study database. In response to these challenges, the ADCS has developed a web-based data exchange and processing platform that allows data managers to configure, manage, and monitor each data flow for a given study. Results: This poster has the following aims:1. Describe the ADCS EDC’s data exchange and processing capabilities.2. Discuss how these capabilities were used to support real-time, periodic and sporadic data flows to facilitate the conduct of recent ADCS clinical trials.3. Outline opportunities for future improvement. Conclusions: The ADCS EDC system provides a sophisticated data exchange and processing framework that accelerates data management and analysis activities at every stage of a clinical study’s lifecycle.