THOUGHT LEADERSHIP

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.

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.

As a Senior Medical Writer, I participated in the 2024 annual conference of the American Medical Writers Association (AMWA) to lead a roundtable on protocol QC and keep up to date on trends and best practices in documents related to clinical research. While many of the best attended sessions were related to the current and upcoming use of AI in the field of medical writing, there were plenty of sessions and workshops (as well as discussions during the protocol QC roundtable) that served as reminders that it is still the human aspect of projects that make the greatest impact in the timeliness and quality of a document or project.

Members of PROMETRIKA’s Data Management (DM) team attended the recent Society for Clinical Data Management (SCDM) conference, held in Boston this year. This annual conference brings together the global data management community for discussions of the latest developments and challenges faced by DM professionals.

This year, PROMETRIKA team members have attended many industry conferences in which the hot topics always seem to be AI and automation of processes. Of course, the innovation cool crowd is excited to jump on board. What has really piqued my attention are the discussions amongst technology vendors about automating SDTM mapping. PROMETRIKA, as a full-service CRO, has a strong focus on biostatistics, statistical, and SDTM programming. Since SDTM mapping is a major part of the programming work that we do, I asked myself “Do we need a new business model for automating SDTM programming?” After hearing multiple viewpoints on the subject, I’ve come away with a list of pros and cons of automating SDTM mapping.