Event

Enhancing Clinical Study Reporting with the Estimand Framework

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Date: Tuesday 21st April 2026
Time: 14:00 - 15:30 (GMT) / 15:00 - 16:30 (CET)
Location: Online via Zoom
Speakers: Vivian Lanius (UCB), Francesca Callegari (Novartis), Maarten van Dijk (Staburo GmbH) and Christian Loesch (UCB)

Who is this event intended for?:
Clinical researchers, medical writers, statisticians, and anyone engaged in reporting clinical trial results.

What is the benefit of attending?:
Key takeaways will be:
- Why estimands matter for decision-making and communication.
- Practical considerations for integrating estimands into study reports.
- Lessons learned from case studies and real-world applications.

Cost

This webinar is free to both Members of PSI and Non-Members.

Registration

To register for this event, please click here

Overview

Clear and transparent reporting of clinical trial results is essential for regulatory decision-making, scientific evaluation, and effective communication with healthcare professionals and patients. With the introduction of the ICH E9(R1) addendum on estimands and sensitivity analysis, the industry has a powerful framework to improve clarity around treatment effects. But how can this framework be effectively implemented in practice at the stage of reporting study results?

Join us for an insightful webinar where we explore practical strategies for applying the estimand framework in clinical study reporting. Drawing on real-world experiences and case studies, we will share recommendations to help you:
- Understand the role of estimands in improving transparency and interpretation of trial results.
- Navigate common challenges in implementing the framework during reporting.
- Apply best practices to enhance regulatory submissions, webposting in public registries (clinicaltrials.gov/CTIS), and scientific publications.

Whether you are involved in clinical trial design, data analysis, or regulatory submissions, this session will provide actionable guidance to realize the full potential of the estimand framework.

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