PSI VisSIG Wonderful Wednesdays
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
PSI Leading for Impact Workshop
Whatever your current challenge(s) at work, this workshop will explore what's holding you back, and how barriers can be removed in order to progress and achieve.
PSI Training Course: Repeated Measured and Mixed Models Module
A PSI Training Course covering the statistical methods for repeated measures and other clustered data. Course will cover: Conditional models for continuous hierarchical data, Conditional models for continuous longitudinal data, Marginal models (GEE) for continuous longitudinal data & Discrete data.
Special Interest Groups
The Application and Implementation of Methodologies in Statistics (AIMS)
The Benefit-Risk SIG was set up at the start of 2012 to help support those involved in this fast evolving area.
Bridging Data Science knowledge and expertise across various groups and functions within the pharmaceutical industry to increase collaboration, awareness, knowledge sharing and enhance drug development. We’ll encourage the development of new statistical and machine learning methods and approaches as well as in novel applications of the well-established methods.
Sharing experiences and challenges of external patient level data sharing with particular focus on data privacy and anonymization processes.
The Quantitative Decision-making Special Interest Group (QDM SIG) was formed in October 2017. It is a group of statisticians from industry and academia, with experience and interests in statistical methods for quantitative decision-making in drug development.
What is the state of the art regarding approaches to incorporate historical data into the formal design and analysis of clinical trials, Which statistical methods should we use to make historical and current data comparable, What are the regulatory requirements necessary for the acceptance of historical data in drug approval?
The purpose of the Healthcare Technology Assessment SIG is to provide statisticians working in the Pharmaceutical Industry engaged in Health Technology Assessments, and others in related fields of research...
This SIG will connect the following two topics: general biostatistics Neuroscience community, and working groups on estimands & other topics in Neuroscience.
A special interest group to facilitate networking amongst ‘new starters’ (statisticians and programmers) working in medical research - the pharmaceutical industry, Contract Research Organisations and Clinical Trial Units. The group will organise between one and three events per year to achieve this. Networking will be facilitated through three types of event – symposia, development and social.
The draft addendum of the ICH E9 guideline on Statistical Principles for Clinical Trials was released in August 2017 and introduced an estimand framework. In February 2018, Evgeny Degtyarev from Novartis and Kaspar Rufibach from Roche started an informal working group to discuss how to implement the draft addendum in oncological clinical trials.
To provide a forum to discuss the statistical issues involved in Regulatory and Investigative Toxicology.
The regulatory SIG co-ordinates regulatory activities across the European Pharmaceutical Statistical community and to engage with European Regulatory statisticians.
A special interest group to increase collaboration and enhance awareness of strategies and methodologies applied in the utilization of Real World Data in the pharmaceutical industry.
The SIG “Small populations” provides a forum for identifying and discussing statistical methodology related to clinical development of treatments in small populations, and for sharing experiences.
Subgroup analysis is routinely conducted in drug development, in various settings; one key aspect is the regulatory requirement to demonstrate consistency of treatment effect across a pre-defined set of subgroups (e.g., ICHE5, E9, E17).
Creating a professional platform for statisticians in the Pharmaceutical industry, Regulatory agencies and Public Health organizations working on the research and development of vaccines to understand how best to apply methodologies.
Effective visualisation of data should belong to the core skills of statisticians as it represents an essential tool in exploring data as well as explaining data.