Deriving Insights from Clinical Data Is as Simple as Asking a Question
In this contributed article for Applied Clinical Trials, Saama’s Srinivasan Anandakumar (VP, Product Management) explains how an AI-enabled virtual assistant can be a valuable part of a clinical research toolkit.
“Once established in a sponsor’s or CRO’s clinical research workflow, a virtual assistant can automatically extract insights from data across an entire study portfolio, while enabling end users to simply converse with data to get the answers they need,” Anandakumar writes.
After explaining how virtual assistants work by combining intents, entities, and actions, and how the machine-learning models get better over time, Anandakumar makes the case for the ultimate inevitability of tools that can instantly analyze data and create operational efficiencies.
Finally, to help leaders in Data Management, Clinical Programming, and Clinical Operations start investigating virtual assistants, Anandakumar offers a checklist of must-have features:
- A unified experience for all clinical analytics needs
- Natural language search
- Pre-defined intents for study-, site-, and patient-level analysis
- Training capabilities for new intents and organization-specific entities
- Continuous feedback loop for ongoing improvement
