A Guide to Establishing a Real-World Evidence Center of Excellence to Maximize High-Quality Data                

When life sciences companies are able to generate real-world evidence (RWE) from high-quality real-world data (RWD), they have the ability to create significant new insights that can help improve patients’ lives. The methods typically used to gain insights into disease progression and treatment effectiveness, are through individual RWD point in time studies. Though valuable, these one-time studies are limited, and do not provide the scope or flexibility that highly curated, refreshed disease-specific datasets can provide. A more advantageous approach to fully leverage advanced datasets, and common modeling techniques, is to establish an RWE Center of Excellence (CoE). 

Benefits of an RWE CoE

By centralizing RWE expertise and capabilities, a CoE enables companies to scale the use of RWD and accelerate broad-scale RWE generation. Organizations also become more data-driven across the drug product lifecycle with a streamlined approach that helps:

• Reduce risk from secure and compliance-ready cloud-based platform technology
• Lower overhead, compared to traditional data procurement processes
• Improve satisfaction among end users due to seamless and secure data availability
• Increase ROI from cross-utilization of data assets across multiple use cases
• Provide greater transparency, control, and traceability of data usage
• Build a leverageable library of best practices around modeling, data linking, and common use case frameworks

A strategic approach to building an RWE CoE allows companies to accelerate and drive innovation, enhance patient care, and deliver on business goals.

How to Get Started

Step One: Establish a Central CoE Organization

Establishing an RWE CoE begins with forming a robust team with the experience and know-how to pinpoint the necessary infrastructure and identify the right data partners. This team should be comprised of seasoned professionals who combine strategic perspectives with practical insights into data analytics, regulatory standards, and scalability requirements. Their collective experience and knowledge are crucial in shaping the foundation of the RWE CoE.

Step Two: Leverage a Scalable Technology Platform

A robust, efficient, and scalable technology platform is paramount. This platform should provide the technological backbone to manage, process, and analyze large volumes of data within the RWE CoE and across other business needs. The right platform aids in the seamless integration of disparate data sources, supports advanced data analytics applications, and provides the agility needed to adapt to evolving business needs and technological advancements.

When working with patient data and proprietary analyses, security is of utmost importance. Cloud-based platform solutions that offer a built-in marketplace, such as Amazon Web Services’ (AWS) Data Exchange, are secure, ensure regulatory compliance, and are highly scalable and adaptable to a wide range of business needs. The right platform serves as a strategic enabler, expanding a company’s analytical capabilities, improving its data access, and accelerating discovery.

Step Three: Access High-Quality RWD Assets

The lifeblood of any RWE CoE are high-quality RWD, which provide the raw material from which actionable insights are derived, and create the foundation for all RWE efforts. Robust RWD enables a holistic view of the patient journey, capturing the complexities and nuances of disease progression and treatment decisions. By delivering a deep and accurate understanding of this complex landscape, RWD can help organizations identify disease subtypes, enhance healthcare decision-making, and improve patient outcomes.

Collaboration is Key

Obtaining high-quality RWD can be difficult for a company to do alone. Meaningful datasets must include large numbers of disease-specific and treatment-specific patients, ideally spread across a multitude of clinicians, and collected over many years. This data must be expertly curated and de-identified to meet quality and patient privacy standards. Tools, such as secure artificial intelligence (AI), may be used to correctly categorize and label data points from complex, unstructured data sources (e.g., patient notes). Partnering with a third-party data provider, such as Verana Health, can help organizations obtain the best RWD to meet the goals of their RWE CoE.

Verana Health collaborates with leading solution providers, such as AWS, to make it easy, secure, and compliant to access deep patient data. 

To learn about one pharmaceutical company’s recent experience accessing Verana Health’s proprietary data through AWS Data Exchange, view our white paper here.