PSDM Networking Event 2026

Wednesday 4 November, 12.30 – 18.00
P-95 Julius Clinical in Zeist, the Netherlands

Please note that P-95 Julius Clinical has moved offices in 2025 and is now at the following address:
Nieuweroordweg 1, 3704 EC, Zeist

Registration is now open! Complete the registration form to register.

Program

Event sponsors

Thank you to our sponsors, P-95 / Julius Clinical and OCS Life Sciences.

 
Abstracts

Gyorgyi Kiss and Jacqueline Vromen-Wijsman, P-95 Julius Clinical
From Data Review to Data Intelligence: Risk-Based Data Management, Central Statistical Monitoring and AI
Abstract to follow

Berber Snoeijer, ClinLine
From Biomedical Concepts to the Schedule of Activities: Building a Reusable Study Design in USDM
The Schedule of Activities (SoA) is central to clinical study design, connecting protocol objectives and endpoints with the assessments, procedures, visits, and timing required to conduct the study. However, translating this information into operational systems remains largely manual, repetitive, and vulnerable to inconsistent interpretation.

During this presentation, it will be demonstrated how CDISC Biomedical Concepts and the Unified Study Definitions Model (USDM) can support a more structured and reusable approach. Using a practical example, we will follow an assessment from a library of company-specific instantiated Biomedical Concepts into a USDM-formatted study design. We will explore how the assessment is linked to study activities, scheduled across encounters and study epochs, and configured with the properties and responses required for the study.

The session will also show how targeted validation can confirm that the resulting content is sufficiently complete and internally consistent for its intended use. Finally, we will consider how a computable Schedule of Activities can support downstream automation, (including EDC configuration, data-transfer specifications, SDTM dataset creation, and Define.xml), while improving consistency and traceability across the clinical data lifecycle.

Ymkje Anna de Vries, CBG
Clinical study data analysis at the Medicines Evaluation Board: from pilot to New Pharmaceutical Legislation
Clinical study data submission will become a routine part of EMA regulatory submissions when the new pharmaceutical legislation (NPL) comes into effect in 2028. This presentation describes our experience so far participating in the clinical study data pilot (raw data pilot) as statistical assessors at the Medicines Evaluation Board (CBG-MEB) and looks forward to the upcoming transition and implementation phase of the NPL.

Floor van Oudenhoven, Danone Research and Innovation
Leveraging external data in clinical trials: an introduction
Clinical trials are becoming increasingly expensive and complex, while relevant data collected outside the current trial may be available from previous in-house studies, registries, and observational cohorts. The relevance of such external data depends on factors such as data quality, and population and endpoint comparability. This presentation introduces statistical methods for leveraging external data to use the information collected in a new clinical trial more efficiently.

Three broad strategies are discussed. First, external data can be used to reduce variability through prognostic covariate adjustment (PROCOVA). Historical data are used to build a model that predicts participant outcomes based on baseline characteristics. These predictions are then incorporated into the trial analysis, helping to separate true treatment effects from natural differences between patients. This can improve the precision and power of the study without increasing the risk of false positive findings. Second, external data can be used to increase effective sample size through methods such as Bayesian dynamic borrowing, which adaptively assigns more or less weight to external data depending on its similarity to the current trial data. Third, external data can be used to create additional study arms, such as external control groups in single-arm trials or a third arm of interest in randomized studies.

These approaches will be introduced in an accessible manner for a broad audience. Intuitive examples and a case study will demonstrate how data collected outside a trial can be used to increase precision, reduce the number of participants required, or provide additional context for interpreting study results.

Edwin van Stein, Raccoon Consulting
Analysis Concepts: A Standard for Executable Clinical Analysis
Statistical Analysis Plans have long been written as narrative text – ambiguous, incomplete, and impossible for machines to act on. The Analysis Concepts Framework, developed by the CDISC Analysis Concepts Working Group as part of the 360i initiative, directly addresses this gap by providing a structured, standards-based approach to expressing derivations and statistical analyses in a machine-readable and executable form.

Central to the framework is a strict separation between a specification layer – abstract, semantic, and language-agnostic – and an execution layer that binds concepts to data standards and code. Key components include Methods, Transformations, Concepts, Data Bindings, and Smartphrases, together enabling platform-independent code generation and bidirectional traceability from results back to USDM.

This presentation provides an overview of the framework, its linkages to USDM, ADaM, and ARS, and a demonstration of an eSAP being built and executed end to end.

Venue

P-95 / Julius Clinical
Nieuweroordweg 1
3704 EC Zeist
The Netherlands

Further information

We recommend to travel by public transport.

There’s limited car parking available at walking distance from the P-95 / Julius Clinical office.