Effective Ingestion and Normalization of Real-World Data Sources

The use of real-world data (RWD) analysis to drive value-based care for patients and to drive real-world evidence (RWE) for regulatory stakeholders, continues to accelerate. As more sources of anonymized data become available, the ability to ingest and normalize these disparate data sets can limit the rate of creating insightful, analytical output.

Advances in technology are now keeping pace with an increase in available data. These advancements provide an unparalleled opportunity to bring together the most meaningful RWD, from claims data to physician notes to wearable device data and beyond. By first standardizing and then linking the collected data, one is able to create RWE capable of addressing specific questions asked at the beginning of a research study or asked by regulatory and market access stakeholders.

Natural language processing (NLP) is used to “read” unstructured RWD and machine learning to expedite advanced analytics and predictions within a data platform. Combined with powerful data handling, they drive efficiency and access to immediate insights. With these advanced technology tools in place, the ongoing ingestion, processing and analysis of new data can propel biopharma companies to improved, data-driven and evidence-based decision-making throughout the product lifecycle.

Creating a strategy to drive this process and identifying which data sources will provide the richest analytic landscape are also important steps to consider. It has become increasingly important for companies to utilize a broad array of RWD sets to measure a product’s true performance through real-world outcomes. This can then reinforce the product’s inherent value in the marketplace. Having access to a powerful, agile technology platform will ensure that no matter what data sources become available for future analysis, the framework is in place to support evolving requirements.

Join this free webinar to learn ingesting and normalizing a variety of RWD sources is paramount to produce powerful RWE.

Speakers

Bill Row, Divisional Principal, Real World Evidence Strategy and Analytics, ICON plc

Bill Row is a seasoned drug development professional with over 19 years’ experience in study design and execution, portfolio management, department building, strategic planning and relationship management. Bill is a recognized leader in the design, operational strategy, commercial and technology applications of RWE at both pharma and CROs. He has held leadership roles in executive management, clinical operations, project management, and strategy and innovation, with an emphasis on late phase and real world evidence programs.

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Bruce Capobianco, Senior Director, Technology, Real World Evidence Strategy and Analytics, ICON plc

Bruce Capobianco has over 25 years’ experience in the architecture, development and implementation of complex big data solutions. At ICON, he leads a team to develop, enhance and maintain technology solutions in the RWE group in order to deliver highly effective tools and services for ICON customers. He has a proven track record of identifying and implementing secure, usable and enduring technologies that augment business processes and optimize productivity. At Syneos, he led a global team of architects, developers, PMs and SQA staff in the development of a HIPAA-compliant, trial patient recruitment system, and established and drove disruptive technology trends for competitive advantage.

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Anand Dubey, Senior Business Solutions Architect, Saama Technologies

Anand Dubey joined Saama Technologies in April 2017 as Business Solutions Architect, Real World Evidence and is responsible for RWE product and solution development for clinical operational groups. Prior to joining Saama, Anand worked at Genpact, a global professional services firm, where he focused on technology-enabled solutions for various groups like clinical, data sciences and commercial teams.

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