Simplified Clinical rolls out AI text analytics addition to its platform

Clinical trial software provider Simplified Clinical has added AI-supported text analytics to its platform to improve data collection and insights.

The Portsmouth, New Hampshire-based company said users of its Clinical Discovery Platform will be able to access unstructured medical texts, allowing them to identify relevant keywords and phrases, make better connections, compile statistics and streamline data analysis.

Simplified also plans to add other new technologies to the platform, including Microsoft’s Power BI data visualization software and automated data capture via FHIR, the acronym for fast healthcare interoperability resources that is a standard for how healthcare information can be exchanged between different computer systems regardless of how it is stored.

“Technological advancements like AI and text analytics are making it faster, more accurate, and more effective to move clinical trial approvals forward,” Simplified's CEO John Schwope said in an Oct. 10 release. “Researchers can use this tool to quickly and accurately read doctors’ notes, minimize risk and avoid regulatory hurdles.”

The use of AI to crunch vast amounts of data in order to fine-tune clinical studies from design and recruitment to post-trial follow-up has been rapidly embraced by parts of the industry.

Earlier this month, Healthcare platform company H1 announced it was delving deeper into the use of machine learning by adding GenosAI to its clinical trials arm, Trial Landscape. The company said users will be able to pose questions that GenosAI can respond to with the aid of natural language processing, such as inquiring about the best-performing trial sites or suitable locations for a particular disease area. 

In August, computational imaging company Altis Labs said it was leading an international project that includes drug giants AstraZeneca and Bayer to advance the use of "digital twins" in clinical trials. Digital twins are AI simulations that help drug developers and clinicians understand how a patient or a therapy may perform in real-life situations.