Explaining the ICH GCP E6 (R3) Guidelines: Updates, Changes, and Next Steps
Medidata Clinical Data Studio is a clinical data management, risk management and data quality solution that leverages AI and automation, and an intuitive user experience to simplify and accelerate data integration, data surveillance and data quality monitoring workflows, driving actionable insights to improve data quality and reduce study risks.
With Clinical Data Studio, clinical data management has access to review all clinical trial data in one place. Assisted by AI and automation, data managers can shorten review cycle times by up to 80% per review cycle.
Clinical Data Studio, with embedded AI and smart analytics, enables clinical operations teams to centrally monitor, manage, and mitigate data quality and patient safety risks.
With all the data in one place, sponsors, medical monitors, and sites can easily set up and visualize the patient journey with comprehensive patient narrative profiles.
Clinical Data Studio provides medical monitors with a full view of efficacy and safety trends across all aggregated patient data. This allows them to identify unexpected and emerging patterns and spot potential patient safety issues. They also gain access to oncology-specific analytics and dashboards to explore complex RECIST 1.1 data easily.
Clinical Data Studio is a solution delivered on the Medidata Platform and accesses Rave EDC data directly rather than adding another system and integration to maintain. It can be up and running in as little as three days, and its low/no-code environment means it doesn’t require expensive managed services to operate. Instead, it reduces reliance on technical resources by simplifying importing (from non-Medidata sources), integrating, and standardizing data.
Reduction in time generating listings
Reduction in data review cycle time
Reduction in KRI configuration time
As little as 3 days to get up and running
Clinical Data Studio positively impacts your data quality through features delivered in a single, high-quality user experience.
Clinical Data Studio enables self-service data import, validation, unit conversion, and derived dataset creation/transformation to integrate data from multiple sources (Medidata and non-Medidata). These capabilities make it easier and faster to make integrated data available to clinical data managers, central monitors, and medical monitors for review and analytics. Raw and derived datasets can also be easily exported in multiple standard formats to use in other systems.
With Clinical Data Studio’s data review and reconciliation capabilities, listings can be created without programming, Rave EDC queries can be posted in bulk, non-Medidata-sourced data can be queried with two-way communication with the data vendor, AI assists with data reconciliation, data can be easily visualized, and progress in data cleaning can be tracked at a glance.
Clinical Data Studio enables comprehensive patient profiles to be easily designed from scratch or from templates to provide complete patient narratives across all data sources. Ad-hoc visualizations can be quickly created to display data in multiple formats, and for oncology studies, RECIST 1.1 analytics are available, all without the need for programming.
Clinical Data Studio brings your risk-based strategies to all your clinical data in one place. Quickly configure and monitor KRIs (key risk indicators) and QTLs (quality tolerance limits). Uncover site performance and compliance risks, using AI to discover anomalies and unusual trends. Identify data quality and patient safety issues sooner.
Clinical Data Studio’s generative AI-powered audit trail review capability enables you to interrogate your audit trail data using natural language and generate subsets for further review and monitoring (e.g., in listings or KRIs). You can generate audit trail datasets quickly and easily without the need to ask your clinical programmers for help.
– Evan Hughes, Vice President, Clinical Data Science, ICON
– Shobha Dhadda, Ph.D., Chief Clinical Science & Operations Officer, Eisai
– Swathi Vasireddy, Associate Director, Clinical Data Management, Corcept Therapeutics
– Jin Dai, CEO, Everest Clinical Research
– Geneveve Nadeau, Director, UK Head, RBQM & Clinical Operations
Read our eBooks on:
This article outlines the evolution of clinical data management into clinical data science, with data managers now being the stewards of all data and overall data quality. It highlights the critical tenets of innovative strategies and cutting-edge technology while ensuring a proactive, efficient, and insightful data management ecosystem.
Read blog posts from Medidata’s clinical data quality and technology experts discussing topics including patient centricity and data centricity, why data platform architecture matters, RBQM, and AI.
A video series delivering insights on the future technology of clinical research – from the Medidata innovators who are shaping it. Real people, real solutions, real stories, real innovation…Hear from the Medidata team about the future of technology in clinical research and what is happening now that can drive your clinical trial outcomes.
This webinar introduces the concept of the ‘5Es of AI’ (Essential, Enjoyable, Explainable, Ethical, Efficient AI) and describes how each relates to a practical use case of AI applied to clinical data management tasks.