eClinical Solutions LLC, a global provider of digital clinical software and services, today announced newly released product enhancements and AI-enabled functionality within the elluminate Clinical Data Cloud ®. Recent platform updates offer clinical teams increased oversight and efficiency amid trial complexity and advance the AI technology footprint of life sciences organizations.

A notable new addition, Protocol Deviations, enhances and adds efficiency to trial oversight, giving clients the ability to ingest, standardize and manage protocol deviation data. With Protocol Deviations, users can configure their global and study Protocol Deviation Assessment Plan (PDAP) and view protocol deviation data directly within elluminate Data Central, utilizing the review workflow to support protocol deviation management. Bringing this data together from various incoming sources and systems into one interface helps stakeholders manage deviation records and enforce standards defined in the PDAP. With Protocol Deviations embedded in elluminate, teams can correct discrepancies and effectively prepare for eventual submission to regulatory authorities. 

“Successful clinical trials rely on protocols that ensure scientific validity, ethical conduct, and regulatory compliance – making processes to address protocol deviations critical for data integrity and patient safety,” says eClinical Solutions CEO and co-founder Raj Indupuri. “With Protocol Deviations, sponsors can streamline and improve oversight for that process. This capability, along with new AI advances across the platform, enable life sciences organizations to remove manual burdens and adopt risk-based approaches that are crucial for boosting operational efficiency in clinical trials.”

With this product release, the inclusion of AI-powered capabilities continues to expand throughout the elluminate platform. To further support oversight requirements, elluminate now includes the machine learning (ML) driven Audit Trail Review, which surfaces anomalies related to frequency and timing of data changes and deletions. To increase efficiency and reduce setup times in advance of data processing, newly added Data Classification uses ML and natural language processing (NLP) to identify incoming data that matches common concepts from the Clinical Data Acquisition Standards Harmonization (CDASH) Model and Study Data Tabulation Model (SDTM). Classification results are added to enhance traditional metadata, then made available while defining new visualizations in elluminate Data Central.

For more information on eClinical Solutions’ innovative elluminate Clinical Data Cloud and the related data products of the platform, please visit: www.eclinicalsol.com/platform.