Data Transparency SIG

Objectives

To share experiences and challenges of external patient level data sharing with particular focus on data privacy and anonymization processes.



Who we are

The Data Transparency SIG is a group of statisticians from industry and academia, with experience and interests in clinical trial data transparency and the associated challenges of patient data anonymization. This includes statistical methods supporting quantitative risk assessment and the privacy aspects of open publication of clinical documents in accordance with evolving regulatory requirements (e.g. EMA Policy 0070, Health Canada and FDA).



How to get in touch

Anyone wishing to join this SIG should contact Rebecca Sudlow (Rebecca.sudlow@roche.com)




Latest News

Since the SIGs inception in 2014 we have published a number of articles and held webinars and presentations on these topics. Links to the these are provided below.

Publications: Data sharing in pharma, includes articles on:

  • Statistical guidance for responsible data sharing: an overview,
  • Protecting patient privacy when sharing patient-level data from clinical trials,
  • Best practice for analysis of shared clinical trial data,
  • EFSPI/PSI working group on data sharing: accessing and working with pharmaceutical clinical trial patient level datasets – a primer for academic researchers,
  • Data sharing and the evolving role of statisticians

 

PSI Webinar recordings - Anonymising Clinical Data, Data Sharing and Data Privacy – what every statistician needs to know

PSI Conference 2018 Recordings - Data Sharing in Practice, Novartis journey in implementing CDP including performing a motivated intruder attack




Upcoming Events

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  • 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.​
  • PSI Journal Club: Missing Data - Dates: 24 – 24 Jan, 2019

    Our next journal club, held jointly with the DIA, features two papers on the topic of Statistical Considerations for Innovative Designs in Clinical Trials. Please join us to hear Jason Yuan and Xiangmin Zhang present their recent work.
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