AIMS
The Application and Implementation of Methodologies in Statistics (AIMS)
Special Interest Groups
Our European Special Interest Groups (SIGs), sponsored by PSI and EFSPI, are playing a key role and foster connections across disciplines, industry, academia and countries/regions. The SIGs provide a forum for members to discuss topics of mutual interest, keep updated on developments in a particular area of industry, to organise events on their specialist field and/or to collaborate on developing the science of that field. Our current SIGs cover a wide range of topics as set out below. We also have a working party looking at the statistical implications of greater clinical trial data sharing and a group of volunteers providing a statistical briefing service on health stories in the lay media.
For further information on any of the SIGs, take a look at their pages on the website using the links below, or for general enquiries please contact Adam Crisp, PSI Board SIG liaison lead, or Emmanuel Pham, EFSPI SIG liaison.
SIG Lead Contacts
For the names & contact details of our SIG leads, please refer to our SIG Lead Contact Page.
Benefit-Risk
The Benefit-Risk SIG was set up at the start of 2012 to help support those involved in this fast evolving area.
Biomarkers
The PSI / EFSPI Biomarkers Special Interest Group has been formed with the aim of developing knowledge and opinions within the statisticians about biomarker usage and the related statistical and study design techniques that are involved.
Causal Inference
Apply advances in causal inference methodology to address industry applications in RCT’s, while taking into account the framework of ICH, e.g. E9(R1), as well as guidelines from health authorities...
COVID-19
Providing a forum for sharing experiences of statistical and methodological issues relating to clinical trials impacted by COVID-19, clinical trials investigating new treatments for COVID-19 and diagnostic/antibody tests for COVID-19
CSM/QTL
The CSM/QTL SIG is a joint collaboration including PSI, ASA BIOP & EFSPI providing a forum to discuss strategies and methodology with other interested parties in Centralised Statistical Monitoring and Quality Tolerance Limits
Data Science
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.
Data Sharing
Sharing experiences and challenges of external patient level data sharing with particular focus on data privacy and anonymization processes.
Decision Making
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.
Historical Data
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?
HTA
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...
Launch & Lifecycle
Providing a platform for statisticians from sponsors and CROs to working in the launch and lifecycle management (including traditional medical affairs area,
Neuroscience-Estimands
This SIG will connect the following two topics: general biostatistics Neuroscience community, and working groups on estimands & other topics in Neuroscience.
Oncology-Estimands
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.
Patient-Focused Drug Development
The purpose of the PFDD SIG is to connect statisticians in pharmaceutical industry roles who work on progressing the inclusion of patient-reported outcomes (PROs) and clinical outcome assessments (COAs) across all phases of drug development process to share their knowledge and also lead statistical thinking and methods to solve common statistical challenges of use of COAs in drug development.
Pre-clinical
To provide a forum to discuss the statistical issues involved in Regulatory and Investigative Toxicology.
Randomisation
Our passion is to change the way randomisation is considered and performed in clinical trials.
Regulatory
The regulatory SIG co-ordinates regulatory activities across the European Pharmaceutical Statistical community and to engage with European Regulatory statisticians.
RWD
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.
Small Populations
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.
Software Engineering
Welcome to the home page of openstatsware, a.k.a. the Software Engineering special interest group! Our primary goals are to: Collaborate to engineer selected R-packages and Develop best practices for engineering high-quality statistical software.
Subgroup Analysis
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).
Vaccines
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.
Visualisation
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.
