Including discussion on the brand new draft of EU GMP Guide Annex 22 ‚Artificial Intelligence‘. If you book this conference together with the "1 Day Pre-Conference Course on Basics of AI", we will offer you a discount of € 400,-
5/6 November 2025, Copenhagen, Denmark
Course No. 22082
Speakers
Stefan Münch
Körber Pharma Consulting
Yves Samson
Kereon
Ib Alstrup
Danish Medicines Agency (DKMA)
Dr Jörg Stüben
Boehringer Ingelheim International
Daniel Wolf
Universitätsklinikum Ulm
Torsten Kneuss
Bayer
Dr Philipp Fey
Boehringer Ingelheim
Dr Torsten Schmidt-Bader
moveproTEC Compliance & Innovation Advisory
Dr Rolf Roth
Merck Healthcare
Kevin Françoisse
Ellion x Sagacify
Victor Bechmann
Kuatro group
Jorge Gil-Hernandez
Boehringer Ingelheim
Felix Krumbein
Head ECA Visual Inspection Group
Note: All times mentioned are CET.
If you book this conference together with the "1 Day Pre-Conference Course on Basics of AI", we will offer you a discount of € 400,-. Book both conferences directly as a combination here.
Background
Since ChatGPT, Bard, Midjourney and others, artificial intelligence (AI) has reached the general public. Opinions fluctuate between absolute euphoria and the evocation of the downfall of humanity. The foundations of AI were laid many years ago and can now be realised on a large scale thanks to the massive computing power available.
The topic has also found its way into the pharmaceutical and medical technology industry. The drafts published by the EU Commission on 7 July 2025 for the new version of EU GMP Annex 11 on computerised systems and the new Annex 22 on AI will also be dedicated to this topic.
The first applications have now been established in pharmaceutical companies. The interesting question is whether and how this technology is compatible with pharmaceutical regulations, specifications and the expectations of the authorities. Several case studies will look at various possible applications.
Target Group
The conference is aimed at managers and interested parties from the pharmaceutical industry, suppliers and service companies who decide on the use of AI and (want to) qualify and operate AI applications in a GxP environment.
Date / Venue / Presentations / Certificate
Date Wednesday, 5 November 2025, 09.00 h – 18.00 h (Registration and coffee 08.30 h - 09.00 h) Thursday, 6 November 2025 2025, 08.30 h – 16.30 h
The presentations for this event will be available for you to download and print before and after the event. Please note that no printed materials will be handed out on site and that there will not be any opportunity to print the presentations on site.
After the event, you will automatically receive your certificate of participation.
Programme
Overview of AI in GxP: Capabilities & Opportunities
General introduction
(Very) brief introduction to AI & ML
Drivers (for using AI & ML in pharma)
Regulations and guidances
AI Limitations and Areas of Concern
Current situation
What do you need to watch out for?
What are the risks?
Current regulatory Situation – the new EU GMP Guide Annex 11 and Annex 22 - and Expectations in the Context of an Inspection
Inspection Readiness
Overview of supporting processes: data management, risk management, change management
Have documentation ready – provide reasoning and justifications
How to setup mock inspections successfully
Aspects of AI Adoption “with and beyond Regulations”
Regulations and the degree of freedom
What you may want to consider
Examples and evaluation criteria
Interactive Presentations
AI in Imaging: An Interactive Introduction with Real-World Examples
Understand each key step in building an AI model for imaging: data preparation, training, pre-training, testing, and explainability
Learn through a real-world example: cancer diagnosis and prognosis based on CT scans
Explore what’s next: opportunities and risks of using large pre-trained multimodal AI models
Engage actively: think, ask, discuss - your participation shapes the session
Leave with a clear understanding of how AI can support your own imaging challenges
Basics of Prompt Engineering
Introduction to ChatGPT and current Large Language Models
Overview of prompt engineering
Prompt techniques
Zero-shot prompting, few-shot prompting
Chain-of Thought
Tree of Thought (ToT)
Reverse Engineering Prompting
Example use cases
Case Studies
Artificial Intelligence (AI) for Discrepancy Management
Detection of clusters based on Natural Language Processing
Validated AI tools in GxP Environment
Human centric approach to ensure quality and Control
Risk based approach to reduce work-load for investigators
Artificial Intelligence in Pharmaceutical Production – Example: Visual Inspection
Traditional image processing and its limitations
Opportunities through the use of artificial intelligence
Expectations, risks, and requirements for the use of AI
Planning, Implementation, Operation & Monitoring – a life-cycle approach following the risk-knowledge-infinity cycle
Documentation of model development: traceability and risk mitigation
AI Coding Agents
Overview: Evolution of AI coding agents
State-of-the-Art: Current capabilities and limitations
Use Cases: Beyond coding
Outlook & Transfer: Future vision and imaging agent capabilities
AI Deviation Assistant – Enhancing Deviation Workflows
Deviation management challenges in pharma
AI-powered solution: Knowledge Graph / LLM RAG
Key features, benefits, and impact
Demo and use cases
Validating LLMs for GMP: A Framework for Document-Centric Use Cases
Risk-based validation strategies for LLM-based systems
Defining appropriate performance metrics for mixed-content data
Human-in-the-loop controls to ensure accuracy and compliance
Considerations for traceability, auditability, and change management
Learning from the Banking Sector: Transfer of AI-based Inspection Tools into GxP regulated Environment
How we can learn from other industries: Conducting AI-based compliance audits in the banking & insurance sector (example: DORA regulation)
Goal: The way to systematic and GDPR-compliant document checks without language barrier
Solution: Fast-track AI-supported inspections of quality management systems in GMP systems
Why auditors are still mandatory: Checking the implementation status of written standards
AI never sleeps: Failure-free creation of risk-based compliance inspection reports
Verification versus GMP validation: The limitations of AI tools in GxP practice
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