Benefit-Risk SIG

The Benefit-Risk SIG was set up at the start of 2012 to help support those involved in this fast evolving area.

The main aims of the SIG are:

• To understand how best to apply Benefit-Risk methodologies across the Pharmaceutical Industry
• To discuss and make recommendations on key methodological issues
• To share examples of how Benefit-Risk has been used within pharmaceutical companies
• To share external information including new developments around Benefit-Risk

Currently the SIG has subgroups working on:
• Literature review
• Benefit-Risk in the HTA setting (together with the HTA SIG)
• Bayesian applications in Benefit-Risk
• Preference elicitation and  Benefit-Risk

We also develop relevant training in the area of structured  Benefit-Risk as needed.

If you have an interest in being involved in this SIG, or have an interesting case study or experience of carrying out a structured Benefit-Risk assessment to share, please contact Maria Costa (email:

Our BLOG can be found under It is a great source of information for all things Benefit-Risk related: upcoming conferences, journal publications, training, and much more.

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EventsFuture Events

  • Webinar: MCP-Mod – Theory, Implementation and Extensions - Dates: 08 – 08 May, 2019

    MCP-Mod (Multiple Comparisons & Modelling) is a popular statistical methodology for model-based design and analysis of dose finding studies. This webinar will describe the theory behind MCP-Mod (plus extensions), and how to implement it within available software. Pantelis Vlachos (Cytel) will provide a brief introduction to the methodology and illustrate the MCP-MoD capabilities in EAST 6.5. Saswati Saha (University of Brehem) will discuss new variations and alternatives to MCP-Mod and show how to implement them in R. Neal Thomas (Pfizer) will present further technical details of MCP-Mod by evaluating the method using results from least squares linear model theory.
  • PSI Toxicology SIG Workshop 2019 - Dates: 02 – 03 Apr, 2019

    This 1.5-day workshop will involve approximately 20 statisticians, focusing on discussions around “best practice” in the statistical analysis of various data types.​