On-Demand Webinar
This webinar, part of our "Analytics in 20" series, focuses on the opportunity and impact of real-world data and evolving AI techniques on modernizing clinical trials.
If you missed the Part 1 overview, catch up now (no registration required) then register for the Part 2 demo.
Randomized clinical trials have provided valuable input for drug development for decades.
But with pressure mounting to bring effective therapies to market more quickly and to successfully translate the results from a trial into a broader patient population, the industry is looking to modernize its approach to clinical trials.
In this webinar, we’ll discuss a range of approaches to modernization, focusing on the use of real-world data (including wearable/sensor data) and the adoption of AI techniques such as machine learning, natural language processing/generation, computer vision and optimization.
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Becker has been a Principal Industry Consultant at SAS since 2013. Prior to joining SAS, he had been using SAS in the life sciences industry since 1988. He focused on clinical programming, data management and visualizations. Becker presented numerous papers and won best paper awards at DIA, PharmaSUG, SUGI and SAS® Global Forum, PHUSE, PharmaSUG China and numerous regional users group meetings.
Rogiers has more than 15 years of experience in the health and life sciences industries as a data analyst, working in a global context. He joined SAS in 2015 as an Industry Consultant and Strategist for the SAS Health and Life Sciences Global Practice group that sets the strategic direction of SAS’ health and life sciences solutions and provides industry domain knowledge to colleagues and customers. Rogiers worked both in the CRO and pharma industries before joining SAS. He is also a member of the European CDISC Coordinating Committee.
Box provides strategic insights across the life sciences industry, with a focus on optimizing the execution of clinical trials. He spent 18 years in the CRO industry, holding leadership roles in statistics, statistical programming, data management and information technology. Throughout his career, he’s used analytics and simulation to improve business processes across all aspects of an organization. Prior to joining his current team, Box spent a year with the SAS Solutions OnDemand Advanced Analytics Lab, working with customers on fraud detection, forecasting and modeling projects.