Radiant Sage Announces Corelab-in-a-Box Version 3.1

Radiant Sage LLC, a provider of on-demand clinical trial imaging infrastructure solutions, today announced the newest version of its Corelab-in-a-Box™ (CLIB) Clinical Trial Imaging Management technology solution. This new version provides sponsors with the key functionality of an imaging corelab in a web-based solution bringing security, efficiency, speed, and transparency to what was considered a black box industry. CLIB Version 3.1 has expanded its features for specific clinical areas, such as oncology, dermatology and for echocardiography. It also offers enhanced workflow and increased flexibility and has eased the quality control and data clarification processes.

"Each clinical study has its own requirements. In this version of our Clinical Trial Imaging Management solution, we have made significant enhancements by adding features for oncology and other clinical areas that rely heavily on imaging data during their studies," said Ven Thangaraj, CEO of Radiant Sage. "We have listened to our clients and enhanced our product to help them to more easily facilitate study execution, regulatory compliance and exploratory research."

Some of the enhancements in CLIB Version 3.1 include:

• Oncology Read Criteria - RECIST 1.0, RECIST 1.1, mRECIST, Chesson, CHOI, IrRC, etc.
• Echocardiography Module providing numerous measurement capabilities for echo-related imaging
• Dermatology-specific Features masking components of images that share personally-identifiable features, such as eyes in facial images
• Endoscopy-specific Features to provide anonymization of personally-identifiable information and video editing for cropping and clipping videos to better fit the read criteria
• Enhanced Workflow enabling users to tailor workflow to the study (not define the study by a static workflow process)
• Increased Flexibility to meet processing steps of all clinical research studies, whether a classical study or a different paradigm
• Configurable QC Form that auto populates items to be checked effectively decreasing the time to complete these tasks. Also within this process, the ability to set data ranges and descriptive information to help normalize data and increase quality and, ultimately, decrease variability in the read analysis
• Additional Metrics to enable users to determine how well the sites and corelabs are working, identify bottlenecks, etc.
• Automated Data Clarification Form (DCF) Workflow providing reminders during the DCF process to ensure sites are responding in a timely manner