Integrated Data Analysis

EFSPI/PSI SIG on Integrated Data Analysis (IDA)

  • The aims of the IDA SIG are to:
  • Keep abreast of current methodology and practice in the integration of data in the areas of
    • Efficacy assessment in Phases II and III;
    • Evaluation of Safety;
    • Network Meta-Analysis;
    • Sharing of clinical trial data on the part of the industry,
  • Develop new methodologies or practices where needed.
  • Write position papers and engage in public debate by making presentations at public meetings and conferences.

The IDA SIG was formed at the end of 2013 and has members from many different pharmaceutical companies. There are currently six working groups looking at the following topics:

  1. Analysis of rare events in safety data (led by David Ohlssen, Novartis, and Sally Hollis, Astra Zeneca).
  2. Safety labelling of drugs (led by Brenda Crowe, Eli Lilly).
  3. Active safety surveillance using large integrated data networks (led by Andrew Bate, Pfizer).
  4. Improving decision making at the Phase II/III transition point (led by Georgina Bermann, Novartis).
  5. Network Meta Analysis (led by Chrissy Fletcher, Amgen and Byron Jones, Novartis).
  6. Data Sharing and Transparency (led by Byron Jones, Novartis).

The chairman of the IDA SIG is Byron Jones (Novartis) who can be contacted at byron.jones@novartis.com

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EventsFuture Events


  • PSI Toxicology SIG Workshop 2018 - Dates: 24 – 25 Apr, 2018

    The Toxicology SIG provides a forum for statisticians working in regulatory and investigative toxicology to discuss issues and interact with one another. This 1.5-day workshop will involve hopefully approximately 20 statisticians, focusing on discussions around “best practice” in the statistical analysis of various data types.
  • PSI Toxicology SIG Webinar - Dates: 12 – 12 Dec, 2017

    This talk introduces a procedure to choose an optimal sparse sampling scheme and sampling time points using non-compartmental methods but which can be applied to further settings beyond this. We discuss how robust designs can be obtained and we apply and evaluate the approach to a range of scenarios to give an example of how it may be implemented.
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