Track 11: Statistics and Data Science
This track will focus on topics related to the practice and application of statistical methods in medical product development throughout their lifecycle. Sessions will explore topics related to current statistical thinking which inform policy, regulation, development, review, and lifecycle management of medical products in the context of the current scientific and regulatory environments. A new aspect of the track is data science, a multidimensional area with the two major dimensions of curation and analysis. This track is focused on the analysis dimension, including analytics and predictive analytics.
DIA recommends this track for: biostatisticians, data scientists (analytics), statistical programmers, clinical pharmacologists, health economists, epidemiologists, regulatory scientists, physicians, project leaders, and other clinical development practitioners.
Included Topic Areas
Statistics, biostatistics, Bayesian statistics, novel statistical tools, data standards, analysis and analysis sets, data interpretation, data visualization, trial planning and design, adaptive designs, innovative designs, model-informed drug development, data monitoring committees, precision medicine and subpopulation analysis, biomarkers, multi-regional clinical trials, endpoint assessment, real-world evidence, pragmatic trials, use of historical control, pediatric/rare disease drug development.
Priority Topics
- Innovative Clinical Trials and Statistical Methods
- Current Challenges and Opportunities in Data Science and AI
- Estimands
- Statistical Methods Underlying AI/ML
- Quantitative Methods for Benefit-Risk
- Communication and Collaboration
- Therapeutic Area/Indication Specific Challenges
- Study Design and Analysis for Post-Marketing Studies