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Improving the Relationship between Statisticians and Programmers in Clinical Trial Studies

July 22, 2020

PharmaSUG is a Software Users Group of life science and health research professionals focused on the application of technological solutions in data analytics and regulatory support. The independent, all-volunteer, non-profit organization hosts an annual conference which is the premier event of the year for statistical programmers, statisticians, data managers, researchers, and others who analyze data in the life sciences.

Having participated as a premier sponsor over the past several years, Catalyst looks forward to exhibiting at the conference each year. Sadly, PharmaSUG 2020 was canceled due to the COVID-19 pandemic. Although we support the decision of the group, we also greatly missed the opportunity to reconnect in person, share knowledge, exchange ideas, and promote best practices. A number of Catalyst team members were slated to volunteer at the conference, perform duties as members of the conference committee, and participate in paper presentation sessions.

Although our participation has been postponed to next year, we welcome you to download the award-winning paper from the 2019 annual conference written and presented by Mai Ngo, Mary Grovesteen, and Vaughn Eason of Catalyst Clinical Research. Improving the Relationship between Statisticians and Programmers in Clinical Trial Studies won Best Paper at last year’s conference in the category of Leadership and Career Development. Download the paper below to learn how teams are facing increased pressure to produce outputs efficiently and on a timely basis as trials get more complex, and how a strong working relationship between the study statistician and the programming team is vital to the success of the analysis project. Based on personal reflections as well as conversations with colleagues, the authors present some of the key areas of frustration in the working relationship between a study statistician and the programming team, touch on perspectives from both the programmer and statistician and offer suggestions for alleviating these issues.