Dear Colleagues,
We are pleased to announce the opening of the Call for Abstracts for oral presentations for the 12th Statistics Workshop, entitled “From Data to Patients – CMC Statisticians’ Contributions to Quality, Safety, and Efficacy of Pharmaceutical Products.”
This in-person meeting will take place in Rockville, Maryland, USA, on October 20–22, 2026.
SAVE THE DATE
Every analysis, model, and decision in Chemistry, Manufacturing, and Controls (CMC) ultimately serves one goal—improving patient outcomes. CMC statisticians play a central role in this mission, ensuring that pharmaceutical products meet the highest standards of quality, safety, and efficacy.
Like chefs transforming ingredients into a finished dish, statisticians transform data—using their expertise in methodology and software—into insights that support sound scientific and regulatory decision-making. In a highly regulated environment, this work is rigorously evaluated by global health authorities, reinforcing the importance of analytical rigor, transparency, and clear communication. As Dr. Ji-Hyun Lee, former ASA President, noted, behind every data point is a patient’s story, reminding us of the direct connection between statistical excellence and patient well-being.
This workshop embraces the “big tent” vision of statistics, highlighting how diverse statistical approaches across the CMC lifecycle contribute to better science and better outcomes for patients.
CONFERENCE THEMES
The scientific program will focus on four core areas:
- Data
The early and strategic role statisticians can play in shaping data systems, improving data quality, and managing and leveraging increasingly complex CMC datasets.
- Software
The importance of reliable statistical software—both point-and-click and code-based—and their appropriate use in producing sound analyses within a regulated environment.
- Methodologies
Advances and best practices in statistical methodology within CMC, including:
- The fundamental role of frequentist statistics in CMC decision-making
- The growing influence of Bayesian methods for uncertainty quantification, inference, and modeling
- The potential of artificial intelligence and machine learning for predictive modeling and process optimization
- Regulatory Review
Perspectives from global health authorities on key statistical considerations in regulatory submissions and interactions.
DEADLINE
The Call for Abstracts is now closed.
LOGISTIC DETAILS
Please address your abstract to secretariat@iabs.org
Submit an abstract (in English) not more than 300 words (excluding title, authors, and affiliation), indicating which core area you would like to be considered for.
Valid format :
Should you require any further information or support, please feel free to reach out to secretariat@iabs.org
Looking forward to receiving your proposals.
The Organizing Committee
