Leverage operational data with clinical trial analytics

Improve efficiency and bring products to market faster

Clinical trials generate immense operational data, but functional data silos and numerous applications often hinder leaders who need a comprehensive view of their clinical trials portfolio over multiple global sites to make informed decisions. As a result, many hours are spent collecting and massaging diverse data needed to optimize trial operations and improve cost and resource efficiencies.

Deloitte's clinical trial analytics platform can provide a holistic end-to-end review of study-, site-, and program-level metrics to help leaders make data-driven decisions to improve trial operations and bring products to market faster.

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Clinical trial analytics case study

This global pharmaceutical organization had grown through a series of significant acquisitions. Its therapeutic area business units functioned autonomously with their own methodologies, data management systems, and CROs, which made accessing reliable portfolio information difficult.

Deloitte implemented a clinical trial analytics platform that collects R&D operations data from over 60 internal and external sources and enables stakeholders to quickly identify issues and traverse across portfolio-, to program-, to study-, and site-level detail.

Business value gained includes:

• Greater alignment and accountability among teams
• Transparent measurement of progress toward goals and milestones
• Proactive portfolio tradeoff decisions and clinical trial adjustments 
• Reduced trial process cycle times

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Gain an end-to-end view of all your clinical operational data

By consolidating operational data on a clinical trial analytics platform with predictive analytics capabilities, BioPharma companies can improve their ability to discern whether or not a data anomaly is a true risk—helping stage more productive and efficient visits.

Decide on key business metrics
First, evaluate your business and decide where you want to focus your efforts. What information do you need to make better operational decisions? Gain agreement on what should be measured, how it will be measured, and how that information will be incorporated into decisions across the clinical trial value chain.

Harmonize data to enable more informed decisions
Standardizing data gathered from dozens of internal and external sources may be your biggest obstacle. Deciphering various names and codes is a tedious process that requires in-depth clinical knowledge and a holistic view of the clinical trial process. Once data standards are established and built into the process, ongoing maintenance is simpler.

Gain an end-to-end view of your data
A consolidated view of the data collected and handled is not enough. If you use several clinical vendors to meet specific needs and reduce risk, consolidating all your data—whatever the source—on one shared analytic platform can foster interactivity and collaboration. It should provide role-based insights across vital metrics, ranging from enrollment rate and screen failure rate to risk proportion and protocol deviations.

Embed intelligence across the process
An effective integrated platform incorporates advanced analytics, including predictive analytics, at every stage of the process to uncover actionable insights that were difficult—or perhaps impossible—to attain before. It also incorporates a self-learning system designed to improve predictions and prescriptions over time. Data visualization tools can proactively deliver reliable analytic insights to users.

Transform insights into action
A collaborative platform that incorporates predictive and prescriptive analytics can inform proactive decisions to avoid problems before they happen. Advanced clinical enterprises may also adopt customized and adaptive nudges that can help overcome cognitive biases, leading to more objective decisions.

Implement to drive lasting change
Providing your people with easy access to the data they need, when they need it, can help make their jobs easier, more productive, and more engaging. But it's easy to slip back into old habits, which is why effective training and change management should be integrated into your implementation plans in an effort to gain sustained long-term benefits.

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Learn More

• The future of health analytics
  
• Moving to a precision medicine model in pharma
  
• Health care analytics
• Delivering medical innovation in a value-based world
• ConvergeHealth
• Measuring the return from pharmaceutical innovation 2016
• RWE benchmark study
• 21st century cures act
• Partnering for progress: How collaborations are fueling biomedical advances

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