The conference is aimed
- At managers and interested parties from the pharmaceutical industry
- Suppliers
- Service companies
who decide on the use of AI and (want to) qualify and operate AI applications in a GxP Environment.
- 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
AI has 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 final versions of both documents are expected to be published in late 2026 - early 2027 respectively.
However, even without the final version of Annex 22, the first applications of AI have already become 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.
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
Radisson Blu Scandinavia HotelAmager 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.
Conference language
The official conference language will be English.
Social Event
On the evening of the first course day, 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 1,990 EUR
APIC Members 1,190 EUR
Non-ECA Members 2,190 EUR
EU GMP Inspectorates 1,095 EUR
The conference fee is payable in advance after receipt of invoice and includes conference documentation, social event including dinner on the first day, two lunches and all refreshments. VAT is reclaimable.
We offer you a discount of 400 EUR if you book this training course together with the course "1 Day Pre-Conference Course on Basics of AI" from 06 October 2026 here.
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.