likely to discontinue a drug or therapy for a chronic disease. With this analysis, pharma and biotech companies can then take action to focus on improving patient adherence and in turn, increase revenue.
The technology advancements of AI, ML and NLP, as seen in these examples, offer pharma and biotech companies the power to increase meaningful RWE output, decrease time to insights, and make the most of the vast data sources now available. An RWE technology platform that delivers smart data processing, analysis and outcomes offers an unparalleled opportunity to capitalize on these computing advancements. When used as part of an overall comprehensive RWE strategy, AI, ML, and NLP innovations can enhance drug development, improve patient treatment and access, and drive valuable new business opportunities.
About the Author
Bruce Capobianco has over 25 years’ experience in the architecture, development and implementation of complex big data solutions. He leads a team to develop, enhance, and maintain Real World Evidence (RWE) technology solutions for ICON clients. 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.