Michael Wegmann
Formerly F. Hoffmann-La Roche
Referierende
Yves Samson
Kereon
Stefan Münch
Körber Pharma Consulting
Ib Alstrup
Danish Medicines Agency (DKMA)
Matthias Markus
Bayer
Jesper Wagner
Niras
Martin Heitmann
MH Consulting & Advisory
Martin Kisselbach
CSL Behring
Volkan Kocak
Novo Nordisk
Daniel Santak Wolf
Ulm University Hospital
Julia Tomasch
Takeda
Highlights
- News about EU GMP Guide Annex 22 ‘Artificial Intelligence
- What Questions about AI can be expected during an inspection?
- Case Studies from CSL Behring / NNIT / Takeda
Zielgruppe
Pre-Conference Course on Basics of AI
The pre-conference is aimed at
- Managers and interested parties from the pharmaceutical industry
- Suppliers
- Service companies
2nd Annex 22/ AI Conference 2025
The conference is aimed
- At managers and interested parties from the pharmaceutical industry
- Suppliers
- Service companies
Zielsetzung
Pre-Conference Course on Basics of AI
What can you expect in the Pre-Conference Course?
- Get to know the basics of AI (Artificial Intelligence) and ML (Machine Learning),
- Learn about the importance of data and models,
- Understand the difference between specialised AI and generative AI,
- Risk management and validation; how should these classic pharmaceutical topics be considered and applied in the context of AI and
- What are the applications and limitations in the GxP environment? Learn about the current state of development.
2nd Annex 22 / AI Conference
- You will gain an overview of the current state of regulatory development with regard to the use of AI in the pharmaceutical industry
- You will be able to better assess the possibilities and limitations of this technology
- You will learn more about the requirements for successfully implementing AI projects within the company
- Case studies from pharmaceutical companies will show you possible areas of application for AI
Programm
Pre-Conference Course on Basics of AI - 06 October 2026
Introduction to Artificial Intelligence (AI) and Machine Learning (ML)
- History of AI
- Types of AI
- Current situation and real-life examples
- Technological Basics
- Different learning / training Methods
- Example use cases
Data and Models
- Overview of core model architectures and data types
- Data splitting: training, validation, and testing phases
- Ensuring data quality, representativeness, and overcoming common bottlenecks
Specialised AI: How Task-Specific Models Work
- Specialized vs. General-Purpose AI: Understanding the key differences
- Step-by-step training process, using cancer diagnostics as a case study
- The roles of pre-training and fine-tuning
- Ensuring AI traceability and explainability in critical Tasks
General-Purpose AI: How Generative Models like GPT & Co. Work
- Fundamentals of Large Language Models (LLMs)
- Strengths and limitations of LLMs compared to specialized AI
- Introduction to LLMs acting as autonomous agent
Risk Management / Validation for AI/ML Solutions
- Applying ICH Q9 QRM to AI/ML
- QRM throughout the System Life Cycle
- Thinking critically about AI-enabled Computerized Systems
- Using the AI Maturity Model
- Achieving Data and Model Governance
Overview of AI/ML in Pharmaceuticals, Biotech and Medical Devices
- Challenges facing the life sciences industry in dealing with AI and ML
- GAMP® 5 meets AI: The GAMP AI Guide
- Use cases for AI in pharma and biotechGMLP (Good Machine Learning Practice): An SDLC for AI/ML
Annex 22 / AI Conference 2025 - 07-08 October 2026
Overview of AI in GxP: Capabilities & Opportunities
- General introduction
- Brief introduction to AI & ML
- Drivers for using AI & ML in pharma
- Regulations and guidance
AI Limitations and Areas of Concern
- Current situation
- What do you need to watch out for?
- What are the risks?
Current regulatory Situation – The Current Status in Regard to EU GMP Guide Annex 11 and Annex 22 - and Expectations in the Context of an Inspection
Risks and Limitations of Large Language Models (LLMs): A Critical Discussion
- Open-Source vs. Closed-Source: Transparency, control, and dependencies
- Bias in training data and its impact on results
- Data privacy and confidentiality when using generative AI
- Hallucinations: Why LLMs generate convincingly false information
Security Implications of AI for Pharma Manufacturing
- Overview: State-of-the-art cyber security & resilience
- AI as a threat versus AI as an opportunity
- Examples AI-based attacks
- Urgent call to action for the industry
Inspection Readiness
- Regulatory developments from an industry perspective
- What are inspectors looking for?
- How to prepare ahead of time
- Practical insights in inspection preparation
AI Strategy & AI Governance – The Big Picture
- What do organizations need to consider when approaching AI in GxP
- How does AI strategy interconnect within a typical corporate strategy layout
- What governance functions are relevant and how do they integrate
- How can enabling elements like data, Quality, and technology be activated
GenAI Platform: A Technical and Compliant Approach for Complaint GenAI Usage in a GxP-Regulated Environment
- Platform mindset: Embracing a platform-oriented approach to leverage GenAI capabilities effectively.
- Democratization of Technology: Ensuring easy access to GenAI tools across the enter-prise, empowering end-users to innovate responsibly.
- Quality Risk Management: Implementing a comprehensive quality risk management framework to evaluate and mitigate potential quality impacts associated with GenAI usage.
AI-Based Assistance Software to Increase Production Efficiency in a GMP-Regulated Environment
- Maintenance Challenges
- How knowledge databases work
- Framework Conditions for the Use of the AI-Based Assistant
- Quality Control of Knowledge Entries
- Benefits, Impact, and Outlook
Digitalization/Automation as the Basis for the Efficient Use of AI in QA and QC
- Basics for QC & QA on IT framework - digitalization - automation - use of AI
- Generation of raw data and data systems
- Real-life automation examples and AI examples from QA & QC
AI in Maintenance – Between Expectation and Reality
- Critical Reflection on AI in Maintenance
- Expectations and roadblocks
- Limits of data driven Models
- Pragmatic alternatives
- Practical experience at CSL
AI in the Pharmaceutical Industry: Regulations, Quality Assurance and Practice
- Regulatory requirements (EU AI Act, Annex 11, 22, Chapter 4, Part 11)
- AI governance: managing risks associated with non-GxP systems in a GxP environment
- Validation: CSV as a holistic approach for compliant AI
- Human-machine interaction: Human-in-the-loop vs. human-centric concept
- Practical examples: Benefits of AI in quality assurance / Thoughts on the potential and risks of AI for patient care
- Outlook: The future role of AI agents
AI and Data Integrity: Limitations (Guardrails) and Opportunities in a Regulated Environment
- Why data integrity is critical in the GMP environment – an overview of regulatory requirements
- Challenges posed by AI – risks to data integrity in generative and agentic systems
- Agentic AI in a regulated environment – the limits and potential of AI
- (Guardrails as a solution)
- Outlook – future developments/trends
Beyond Hype and Shadow AI: Building Trusted, Compliant AI in GxP
- Deep domain and process knowledge to correctly frame AI use cases
- Reliable data quality and availability as the bedrock of compliance
- Robust governance frameworks (e.g., the 4G model: Guard, Govern, Guide, Gate) to align with GxP, ISO, GDPR, and FDA expectations
- Practical use cases, such as applying AI to product risk management, showing how copilots can accelerate risk assessments while maintaining audit-readiness
Weitere Informationen
Radisson Blu Scandinavia Hotel
Amager Boulevard 70
2300 Copenhagen S, Denmark
Phone: 45 3396 50-00
Email guest.copenhagen@radissonblu.com
Amager Boulevard 70
2300 Copenhagen S, Denmark
Phone: 45 3396 50-00
Email guest.copenhagen@radissonblu.com
Accommodation
CONCEPT HEIDELBERG has reserved a limited number of rooms in the conference hotel. You will receive a room reservation form/POG when you have registered for the course. Reservation should be made directly with the hotel. Early reservation is recommended.
CONCEPT HEIDELBERG has reserved a limited number of rooms in the conference hotel. You will receive a room reservation form/POG when you have registered for the course. Reservation should be made directly with the hotel. Early reservation is recommended.
Conference language
The official conference language will be English.
Get Together
The official conference language will be English.
Get Together
On the evening of 07 October, the participants are cordially invited to a dinner. This event is an excellent opportunity to share your experiences with colleagues from other companies in a relaxed atmosphere.
Fees (per delegate, plus VAT)
ECA Members 3,080 EUR
APIC Members 2,880 EUR
Non-ECA Members 2,190 EUR
EU GMP Inspectorates 1,340 EUR
The conference fee is payable in advance after receipt of invoice and includes conference documentation, lunch on all conference days, social event including dinner on 07 October, and all refreshments. VAT is reclaimable.
You can also book an individual course separately.
>> Pre-Conference Course on Basics of AI
>> 2nd Annex 22 / AI Conference
ECA Members 3,080 EUR
APIC Members 2,880 EUR
Non-ECA Members 2,190 EUR
EU GMP Inspectorates 1,340 EUR
The conference fee is payable in advance after receipt of invoice and includes conference documentation, lunch on all conference days, social event including dinner on 07 October, and all refreshments. VAT is reclaimable.
You can also book an individual course separately.
>> Pre-Conference Course on Basics of AI
>> 2nd Annex 22 / AI Conference
Presentations/Certificate
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.
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.
Contact
Questions regarding content:
Dr Andreas Mangel, +49 6221 84 44-41, mangel@concept-heidelberg.de.
Questions regarding content:
Dr Andreas Mangel, +49 6221 84 44-41, mangel@concept-heidelberg.de.
Questions regarding Organisation:
Mr Maximillian Bauer, +49 6221 84 44-25, bauer@concept-heidelberg.de
Mr Maximillian Bauer, +49 6221 84 44-25, bauer@concept-heidelberg.de
Datum & Uhrzeiten
Pre-Conference Course on Basics of AI
Tue, 06 October 2026, 09:00-18:00 h
(Registration and coffee 08:30-09:00 h)
2nd Annex 22 / AI Conference
Wed, 07 October 2026, 09:00-18:00 h
(Registration and coffee 08:30-09:00 h)
Thu, 08 October 2026, 08:30-16:30 h
All times mentioned are CEST.
(Registration and coffee 08:30-09:00 h)
2nd Annex 22 / AI Conference
Wed, 07 October 2026, 09:00-18:00 h
(Registration and coffee 08:30-09:00 h)
Thu, 08 October 2026, 08:30-16:30 h
All times mentioned are CEST.
Teilnahmegebühr
| ECA-Member*: | € 2680,- |
| Non ECA Member*: | € 3080,- |
| EU/GMP Inspectorates*: | € 1340,- |
| APIC Member Discount*: | € 2880,- |
Alle Preise zzgl. MwSt. Wichtige Hinweise zur Umsatzsteuer.
* auch unkompliziert per Kreditkarte bezahlbar
Aufzeichnung/weitere Termine nicht verfügbar
Aufzeichnung/weitere Termine nicht verfügbar
This course is part of the GMP Certification Programme "ECA Certified Computer Validation Manager"
Haben Sie noch Fragen?
Wir stehen Ihnen für weitere Auskünfte gerne zur Verfügung.
E-Mail: info@concept-heidelberg.de
Für Lieferanten: Ausstellungs- und Sponsoringmöglichkeiten
Teilnehmerstimmen - das sagen andere über unsere Seminare:
