Modern Data Architecture in Clinical Trials

Trial Better: A Clinical Trials Podcast

Drew Bustos, Senior Director of Business Intelligence Products, is joined by Dr. Santikary, Vice President and Global Chief Data Officer at ERT, for a discussion of the role of modern data architecture. Clinical trial sponsors and CROs are facing increasing numbers of complex data integration and quality challenges. Are you struggling to keep up with this exponential data growth? The solution may lie in modern data platform, cloud, and artificial intelligence technologies.

Data Architecture Challenges in Clinical Trials & Healthcare
Data architecture challenges can be significant, and often include data security; data privacy and protection at scale; data integration at scale; real time reporting and analytics at scale; and data governance and master data management at scale. A modern data platform can be built to handle these challenges.

Common Data Integration Problems
Integrating data and serving it to the end user in one, centralized location is easier said than done. Different vendors and technologies, using disparate platforms, make the integration process even more difficult. In addition to a lack of standardization, unstructured data and binary data further compound the data integration and architecture challenges.

Emerging Trends in Data Architecture and Technologies in the Clinical Trial and Healthcare Industries
The rate of change in clinical research and healthcare technology is unprecedented. In particular, artificial intelligence and blockchain technology are making a huge impact in clinical research.

The State of Artificial Intelligence and its Clinical Trial Application
Sponsors and CROs can expect to see a major shift toward embracing AI in the pharma industry over the next few years. In fact, this trend has already begun with the use of predictive algorithms, chatbots, and voicebots in clinical trials. Artificial intelligence has the potential to accelerate drug discovery and increase trial efficiency.