Please browse through our collection of videos and slides from past APBG events.
APBG Mid Year Meeting 2024
Introduction to Statistical Society of Australia’s (SSA) Mentoring Program
This topic was presented by Elizabeth Korevaar on 21st August 2024.
Abstract
Recognising a need to build better connections between early-career and more established statisticians in Australia, Karen Lamb created a mentoring program through the Biostatistics & Bioinformatics Section of the Statistical Society of Australia (SSA) in 2020. The program involved 10 mentor-mentee pairs from around Australia and ran for 12 months. The program has since expanded broadly across the SSA and is run by the Mentoring Program Committee, co-chaired by Karen and Lizzie Korevaar. The broader program is now in its 4th year, pairing between 20 and 30 mentees and mentors each year. In this talk, Lizzie will provide an overview of the program and its benefits to participants.
Introduction to ACTA Statistics in Trials Interest Group (STInG) Data and Safety Monitoring Board (DSMB) Mentoring Program
This topic was presented by Sabine Braat on 21st August 2024.
Abstract
Recognising a need to build better connections between early-career and more established statisticians in Australia, Karen Lamb created a mentoring program through the Biostatistics & Bioinformatics Section of the Statistical Society of Australia (SSA) in 2020. The program involved 10 mentor-mentee pairs from around Australia and ran for 12 months. The program has since expanded broadly across the SSA and is run by the Mentoring Program Committee, co-chaired by Karen and Lizzie Korevaar. The broader program is now in its 4th year, pairing between 20 and 30 mentees and mentors each year. In this talk, Lizzie will provide an overview of the program and its benefits to participants.
PK/PD Modelling and Simulation: How they can support drug development
This topic was presented by Zheng Liu on 21st August 2024.
Abstract
Pharmacokinetics (PK) plus pharmacodynamics (PD) equal to pharmacology, which plays an essential role in drug development. PK is the study of how our body treats the drug and PD is the study of how the drug treats our body. PK exposure is a key factor connecting dose to PD, efficacy and safety of the studied drug in question. PK/PD modelling and simulation has become a powerful approach to support drug development and regulatory review, which is often referred as Model-informed drug development (MIDD). This presentation will provide an introduction about the concepts of PK, PD, and seven case studies about how PK/PD modelling and simulation can support drug development.
Statistical Considerations in Drug Development – Adaptive Designs and Estimands
This webinar was presented by Dr Hideki Suganami on 28th June 2024.
Abstract
The mission of R&D-oriented pharmaceutical companies is to contribute to the improvement of health and welfare of people around the world through continuous R&D and stable supply of innovative pharmaceutical products.
One way to efficiently meet society’s demands is to shorten development time. Adaptive design, Bayesian statistics, and the use of external controls are some examples. Some trials that are considered complex innovative design are presented as examples of urgent clinical trials. In trials such as these, it is sometimes difficult to analytically assure control of Type I errors and can only be assessed by simulation. It is desirable to examine the operating characteristics of the estimated amount of bias before starting the test. The following is an organized discussion of precautions to be taken when simulation is used to demonstrate operating characteristics. The Potvin’s method is known as a method of sample size re-estimation in BE testing, but it does not always control for type 1 errors. There is some controversy about the estimand of BE tests, so we will introduce that point as well.
The Japan Pharmaceutical Manufacturers Association and how-to step-up ICH topics will be introduced.
Missing Data and Multiple Imputation
Presented at the APBG 2023 End of Year Meeting, this presentation by Michael Fitzgerald shares a case using simulated data based on a real study where the primary endpoint was recurrent event data. Described is the missing data strategy for the primary analysis and sensitivity analyses that were planned, plus a bonus method using multiple imputation and pattern mixture models for a tipping-point analysis which we recommend is used for future studies.
Australian Pharmaceutical Biostatistics Group 