Date:
Language:
Location:
24 November 2026, 08:00 - 17:00
The event will be held in French and English.
Cité Internationale Universitaire de Paris, 17 boulevard Jourdan, 75014, Paris, France
Click here to register.
Abstract:
The DMB Annual Conference 2026 will take place on 24 November in Paris, bringing together professionals from the clinical data management community. This year’s theme, “DM by 2030: Transformations and Changes in the Profession Through Innovative Approaches,” explores the evolving role of data managers in a changing industry. Key topics include risk-based monitoring (RBM), artificial intelligence (AI), real-world evidence (RWE) and audit trail reviews. The program will address developments in clinical data management, providing opportunities to exchange experiences, discuss current challenges and explore innovative approaches. The conference also offers a platform for networking and sharing expertise with professionals across the field. wega will participate in the event to connect with industry professionals and exchange perspectives on how data, processes and digital solutions can support the evolving needs of life sciences sector.
More details about the event can be found here.
Our Presentation:
Title: Building FAIR Clinical Data Ecosystems for AI
Speaker: Nicolas Schaltenbrand
Date: Tuesday, 24 November 2026, 14:00 - 14:30
For us on site:
Nicolas Schaltenbrand
Head of Clinical Development Informatics at wega Informatik AG, Switzerland
Nicolas 's professional background is based on a dual qualification, as a clinical operational data expert and as an IT professional.
Nicolas has spent over 25 years in pharmaceutical/clinical development, business, informatics consulting and service delivery with a significant experience in the design and deployment of clinical information systems and technologies, with a special emphasis on cloud environment and international outsourcing business model related to clinical trials
Nicolas speaks both the language of clinical scientists and IT experts and can easily translate complex clinical process into operational reality.
He is interested in working towards improving efficiencies in Life Science industry using Machine Learning and Intelligence Artificial technologies.