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The ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop is held annually in Rockville, MD to provide biostatisticians with the opportunity to collaborate and expand the frontiers of statistical knowledge. The 2025 ASA conference centered around the future of statistics in the era of artificial intelligence (AI) and machine learning (ML). Two statisticians attended on behalf of PROMETRIKA to explore current AI/ML research efforts and use cases from statisticians across industry, academia, and regulatory agencies. Across a three-day series of short courses, speaker sessions, panels, roundtables, and poster sessions, a clear message emerged that AI/ML has a strong potential to improve statistical frameworks throughout the drug development life cycle.
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The development of ‘artificial intelligence’(AI)-driven tools for data management has accelerated in the past few years. The promise of these systems is to provide a more intuitive experience for data management and sponsor teams, making it easier to track trends, spot anomalies, and generate near-real time data reports. These features, combined with AI’s ability to learn from data, make these tools a modern essential for improving data quality and accelerating clinical trials.
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Leveraging the advantages of electronically captured patient-reported data in early phase trials
As clinical trial planning begins, PROMETRIKA Clinical Trial Managers (CTMs) and Project Managers (PMs) are often asked by Sponsors to assess the pros and cons of using paper documentation (e.g., diaries) vs. electronic data entry for patient-reported data. Our broad experience with different phases of clinical trials helps us advise Sponsors on this decision.
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The importance of keeping an inspection-ready electronic trial master file (eTMF) at all times cannot be understated; the TMF tells the story of the clinical trial and should serve as the ultimate source of truth for the study. An inspection-ready TMF is complete without being redundant and efficient while still upholding high standards of quality. This might sound like a lot of work, but don’t let it intimidate you; an inspection-ready TMF can be achieved by following the steps outlined below.
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We had the opportunity to present our paper, “Optimizing SAS Programming Pipelines Using the %Unpack and %SearchReplace Macros for Version Control and Customization”, written by Ning Ning, Statistical Programmer I, and Assir Abushouk, Manager, Statistical Programming, at PharmaSUG 2025 in San Diago. The presentation focused on a practical SAS macro program we developed to address common challenges in clinical programming, particularly around version control, customization, and study startup efficiency in CROs.
THOUGHT LEADERSHIP
