Quintiles has launched Data-driven Trial Execution, leveraging risk-based monitoring to improve clinical trial delivery.

While the industry's current approach to risk-based monitoring focuses solely on clinical trial monitoring, Data-driven Trial Execution combines study startup, project management, clinical monitoring, data management and analytics to optimize trial conduct while meeting regulatory demands and quality requirements for Good Clinical Practice (GCP).

"Our customers are seeking to manage clinical trials with greater efficiency, seamless execution and predictive insights that enable them to respond faster and make better-informed decisions," said Paula Brown Stafford, president of clinical development at Quintiles. "Data-driven Trial Execution is the first in a series of standardized offerings that Quintiles plans to bring to market, and is our answer to optimized trial execution that has the potential to improve quality while reducing overall trial costs by up to 25%."

Quintiles has delivered more than 80 projects involving risk-based monitoring principles and processes across more than 20,000 sites and 200,000 subjects. Quintiles Data-driven Trial Execution builds upon that experience and represents a true shift in clinical trial oversight, introducing a central data surveillance team that performs ongoing reviews of data to monitor risk and facilitate the right action at the right time.

Data-driven Trial Execution is powered by Quintiles Infosario platform, adding advanced analytics that provide biopharmaceutical customers with a real-time view of a study's status and progression for enhanced transparency and collaboration across stakeholder groups. Quintiles project teams can gather insights of critical data in a single, 360-degree view allowing for early identification of risks and potential issues with automated triggers and alerts that guide action plans. Project teams have real-time visibility to critical information across programs, including projected study visits, to enhance study execution, improve predictability and maximize customer investments.