For clinical research statisticians, where specifically are AI & ML useful – considering regulatory requirements.

When it comes to R and open-source in the Pharma industry, we would like to point you in the right direction!

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

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.

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...

Chemistry, Manufacturing and Control Statisticians, working in Europe for pharmaceutical companies and CROs active in R&D, and we seek to collaborate and exchange in any precompetitive topic of our field.

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

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...

Providing a platform for statisticians from sponsors and CROs to working in the launch and lifecycle management (including traditional medical affairs area,

This SIG will connect the following two topics: general biostatistics Neuroscience community, and working groups on estimands & other topics in Neuroscience.

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.

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.

To provide a forum to discuss the statistical issues involved in Regulatory and Investigative Toxicology.

Our passion is to change the way randomisation is considered and performed in clinical trials.

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.

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. 

Treatment Effect Heterogeneity 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.