On-Demand Webinar

Augmented Clinical Trials: The Role of Virtual/Hybrid Trial Designs and the Internet of Medical Things

This webinar, part of our Analytics in 20 series, examines how life sciences companies are competing in the digital world by using AI and machine learning to evolve the clinical research process.

If you missed the Part 1 overview, catch up now (no registration required) then register for the Part 2 demo.

About the webinar

To drive better therapies to market faster and stay competitive in the age of digital health, life sciences companies must evolve the clinical research process.

This evolution requires achieving data interoperability and adopting new technologies and advanced analytical approaches.

The benefits of virtual and hybrid trial designs improve patient enrollment, compliance and experience.

They lead to increased trial outcomes as patient adherence, clinical biomarkers and other areas of clinical benefit are more easily measured and analyzed during development. And they enable real-time decisions to protect patients against possible adverse events or to prevent risks of supply shortage.

Machine learning and AI, supported by the Internet of Medical Things, are the analytics engine that enable this innovation in trial design by keeping researchers connected to patients and their data.

Join us to explore these driving forces of change in clinical research.

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About the Experts

Jim Box, Principal Data Scientist for Life Sciences, SAS

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.

Matt Becker, Advisory Consultant and Life Science Team Lead, SAS

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.

Mark Wolff, Chief Health and Life Science Analytics Strategist, SAS

Wolff has more than 25 years of experience in the health and life science industries as a scientist and analyst working in the US and Europe. He joined SAS in 2005 and currently focuses on methods and the application of machine learning to real-time sensor/IoT data in support of outcomes and safety research, visualization and development of intelligent decision support systems.