2026 SORA-TABA Annual Workshop

The Division of Biostatistics in the Dalla Lana School of Public Health at the University of Toronto is pleased to host the 2026 SORA-TABA Annual Workshop. The event brings together regional and local statistical communities who are interested in biostatistics, artificial intelligence, data science, financial statistics, and other applied areas of statistics. Please join us in making this event a great success!

If you have any questions, please email Yeonkyung Namkoong at [email protected].

Scientific Head, Biostatistics Core, Centre for Addiction and Mental Health (CAMH)

Assistant Professor of Biostatistics, Dalla Lana School of Public Health, University of Toronto

Adaptive designs are clinical trial designs that allow for prospectively planned modifications to one or more aspects of the design based on accumulating data from subjects in the trial. Adaptive designs can increase the efficiency, accuracy, and flexibility of clinical trials. Adaptive features may be implemented across all phases of clinical development. This workshop will introduce the statistical design of selected adaptive designs. Participants will learn about the benefits and challenges of conducting adaptive trials. Participants will gain hands-on experience in designing different adaptive trials using R packages and interactive R Shiny tools.

This workshop is targeted for both statisticians and clinical investigators interested in designing adaptive trials. Faculty, staff, postdoctoral fellows, and students are welcome. Participants are recommended to have knowledge of basic clinical trial terminology and methods. No advanced statistical, mathematical, or coding background will be required.

Module 1: Overview of adaptive designs (9:00 AM – 10:30 AM)

1. Fixed vs. adaptive designs
2. Overview of 7 types of adaptative features
3. Motivating examples with adaptive features

Break 1 (10:30 AM – 10:45 AM)

Module 2: Bayesian adaptive phase 1 dose finding designs (10:45 AM - 12:15 PM)

1. Design of phase 1 trials using the continual reassessment method (CRM)
2. Design of phase 1 trials using the Bayesian Optimal Interval (BOIN) design
3. Adaptive dose finding case study

Lunch (12:15 PM – 1:30 PM)

Module 3: Group sequential designs (1:30 PM – 3:00 PM)

1. Group sequential trials with early stopping for efficacy and/or futility
2. Group sequential design case study

Break 2 (3:00 PM – 3:15 PM)

Module 4: Sample size re-estimation (3:15 PM – 4:45 PM)

1. Blinded sample size re-estimation
2. Unblinded sample size re-estimation
3. Sample size re-estimation case study

Closing remarks (4:45 PM – 5:00 PM)

Dr. Clement Ma is the Scientific Head of the Biostatistics Core at the Centre for Addiction and Mental Health (CAMH) and Assistant Professor of Biostatistics at the Dalla Lana School of Public Health at the University of Toronto. He completed his Ph.D. and post-doctoral training in Biostatistics at the University of Michigan in 2015. He was previously the Lead Biostatistician at the Dana-Farber/Boston Children’s Cancer and Blood Disorders Center and Assistant Professor of Pediatrics at Harvard Medical School from 2015 to 2020. Dr. Ma’s research focuses on developing and implementing innovative statistical methods to improve the accuracy and efficiency of clinical trials. Specifically, he has developed novel methods for adaptive dose finding, trials with co-primary endpoints, and adaptive basket designs.

• Registrants will be able to access the workshop recordings for three weeks following the event.
• All ticket sales are considered final. We do not offer refunds.

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Host or Publisher Dalla Lana School of Public Health