(AI) Artificial Intelligence in an GxP Environment - Live Online Training
29/30 October 2024
Course No. 21458
Speakers
Yves Samson
Kereon
Stefan Münch
Körber Pharma Consulting
Stefan Hessel
Reusch Rechtsanwaltsgesellschaft
Daniel Wolf
Universitätsklinikum Ulm
Martin Heitmann
d-fine
Ib Alstrup
Danish Medicines Agency (DKMA)
Dr Juergen Schmitz
GSK Vaccines
Hendrik Rolshausen
DHC Dr. Herterich & Consultants
Urs Alexander Peter
HC Dr. Herterich & Consultants
Felix Georg Müller
plus10
Objectives
Why should you participate in this event?
You will learn the basics of AI / ML and its applicability in the GxP Environment
How can pharmaceutical basics, e.g. risk management and qualification / validation be applied to AI? You will experience first approaches!
Are relevant pharmaceutical regulations adapted to this new technology and what expectations does an inspector have during an inspection? First concepts will be presented!
In case studies, pharmaceutical companies show first practical and practised approaches to the use of AI
Background
At the latest, Artificial Intelligence (AI) has arrived in the general public since ChatGPT and Bard. Opinions range between absolute euphoria and the invocation of the downfall of humanity. The foundations of AI were laid many years ago and can now be widely implemented due to massively available computing power. The topic has also found its way into the pharmaceutical landscape. First applications have come into operation. The interesting questions here are whether and how this technology is compatible with pharmaceutical regulations, specifications and authorities’ expectations.
Target Group
The Live Online Training is aimed at managers and QA members as well as engineers from the pharmaceutical industry, suppliers and service companies who qualify and operate AI applications in a GxP environment.
Technical Requirements
We use Webex for our live online training courses and webinars. At https://www.gmp-compliance.org/training/online-training-technical-information you will find all the information you need to participate in our events and you can check if your system meets the necessary requirements to participate. If the installation of browser extensions is not possible due to your rights in the IT system, please contact your IT department. Webex is a standard nowadays and the necessary Installation is fast and easy.
Programme
Introduction to Artificial Intelligence (AI)
History of AI
Types of AI
Real life examples
Introduction to Machine Learning (ML)
Technological basics
Different learning / training methods
Example use cases
AI in Image Processing
Introduction to deep learning models for imaging
Deep learning for diagnosis and prognosis
Pre-training of deep learning models
Explainable Artificial Intelligence
AI/ML in Pharma, Biotech, and Med Devices
Challenges for the Life science industry
The GAMP-perspective on AI/ML
Use cases / Known scenarios
Regulatory Requirements / Concerns / Assessment
Pharmaceutical laws
EU-GMP Guide Annex 11
Inspection strategy
What do inspectors expect from the regulated user?
Inspection Readiness
Overview of regulatory guidance and evolving inspection practices
Overview of supporting processes: data management, risk management, change management
Have documentation ready – provide reasoning and justifications
How to setup mock inspections successfully
Data and Models
Overview of model and data types
Data split: training, validation, testing
Data quality, representativeness and typical data challenges
Use of synthetic data
Introduction to and Application of Generative AI in Regulated Pharma
Introduction to Large Language Models (LLM) and example use cases
Specialization and tailoring of LLMs in computerized Systems
Typical risks when using LLMs
Performance evaluation and validation strategies for LLMs
Generative AI - Legal Requirements and practical Implementation
AI and law: introduction and overview
Outlook and update on the EU AI Act
Copyright and trade Secrets
Data protection requirements and processing of personal data
Practical implementation and best practicess
Validation Approaches
Maturity: Increasing autonomy and transferring Control
Governance: Developing and operating AI solutions in GxP-regulated areas
The Use of Artificial Intelligence in Pharmaceutical Manufacturing, Developments, Implementation, and Examples
Risks and Opportunities
Preparing the Quality Management System for AI
Where to implement and what to avoid
Pactical examples and attention Points
Validation requirements
Future Developments
Risk Management for AI/ML
Basics of a ML Risk and Control Framework
Applying QRM to development and operation of AI applications
Using hazard clusters to guide the risk process
Efficiency Increase in Pharma Production Lines through GMP-compliant AI Tools – Case Study Review
Lessons learned from primary and secondary packaging lines and Auto-Injectors production
When continuously learning and situationally acting tools can help and when not
Introduction of Use cases for live learning optimization tools in GMP-environment
Short Intro: AI-based behavior learning on high frequency machine data of whole production lines
Obstacles during validation
Learnings from 24/7-operations Integration
Review of realistic and unrealistic benefits
Trustworthy AI: Innovative Approaches for Transparency in Validation
Black box or partner: How can transparency of AI be increased?
Interpretability of AI-based decisions
Foundations of Explainable AI
Approaches for the validation of AI systems in GxP environment
This course is part of the GMP Certification Programme "ECA Certified Computer Validation Manager" Learn more
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Testimonials
Seminar Programme as PDF