Unlocking the Value of Clinical Trial Data for Improved Decision-making
Clinical trials data can be difficult to capture and effectively utilize for future decision-making activities, including finding the right patients, selecting appropriate sites, establishing cohorts, understanding valuable patterns and trends in the data (non-compliance, drop-out rates), and comparing data across different trials.
This talk will show how Accenture is using semantics to integrate clinical data around standards in order to provide advanced types of search and analytics of clinical trials data. We call this engine Intelligence Everywhere. Utilizing advanced AI-based connectors, we will show how to find complex salient patterns across heterogeneous data sources using only metadata captured in various ontology models. Data can be queried from transactional as well as historical sources, across different formats (FHIR, SDTM, etc.) and patterns that are returned can be sent to powerful analytics engines to produce complex answers to clients’ most challenging questions.
The engine comes pre-loaded with certain standard models and algorithms, all of which can be quickly and easily extended for a given client’s specific needs and use cases. We will briefly discuss how newly evolving generative-AI capabilities can be integrated as well, in order to provide a highly interactive system that can also manage data access, security, and limit current challenges around explainability of automated analysis.