(AI) Artificial Intelligence in an GxP Environment - Online Training Recording
Course No. 21359
Speakers
Yves Samson
Kereon
Stefan Münch
Körber Pharma Consulting
Dr Arno Terhechte
GMP inspectorate / Bezirksregierung Münster
Dr Mario Holl
INSPECTIFAI
Dr Hadj Latreche
F. Hoffmann-La Roche
Haluk Dönmez
B. Braun
Christophe Girardey
wega Informatik
Thomas Singer
Merck
Julius Kittler
Merck
Nicolas Schaltenbrand
Wega Informatik
Objectives
Why should you participate in this online training?
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 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
To participate in an on demand training course or webinar, you do not need any software. The recordings are made available via a streaming server. In general, the recording is provided in MP4 format, which any PC (Microsoft Windows, Apple IOS) or tablet can easily display.
Timing and Duration:
When you register for the on demand Training course or webinar you can decide at what date you want to follow the training course online. For a 1-day training course you will have 2 days in which the stream is available (for 2-day training course 3 days and for a 3-day training course 4 days). Within in this timeframe you can start & stop the stream according to your needs.
In time before the scheduled date (your desired date) you will receive an e-mail from us with a link for direct participation as well as your log-in data.
Training Course Documentation and Certificate:
The presentation will be made available as PDF-files via download during the online training course. After the successful completion of the online training, you are able to download the certificate of attendance.
Programme
Regulatory Requirements / Concerns Dr Arno Terhechte
Pharmaceutical laws (AMG and other)
EU-GMP Guide Annex 11
Concept Paper Revision of Annex 11
Software as Medical Device
Validation Approaches Stefan Münch / Yves Samson
Maturity: Increasing autonomy and transferring Control
Governance: Developing and operating AI solutions in GxP-regulated areas
Risk Management Stefan Münch / Yves Samson
Power with control: Explaining the outcomes of trained models
Applying QRM to development and operation of AI applications
Regulatory Requirements / Assessment Dr Arno Terhechte
Inspection strategy
What do inspectors expect from the regulated user?
Case Study: Predictive Control of Yield & Titer Dr Hadj Latreche
Apply Advanced Analytics to enable predictive Titer/Yield and reduce variability while increasing mean toward high-end value
In-Flight predictive and adaptive process oversight for shop floor to target Titer/Yield Golden Batches
Prove the value of utilizing Advanced Analytics as a digital product leveraging different data sources and advanced predictive algorithms
Build site future capabilities required for a sustainable way of working using Advanced Analytics
Case Study: AI in Medical Device Area Christophe Girardey
Introduction on the regulations in Medical Device area
AI in Medical Device:
Patient risk: more direct than in Pharma?
Reality not future: FDA list of devices released.
Guidelines on AI:
(FDA GMLP > optional as already covered in one of the other sessions)
AI & Cybersecurity (ENISA guideline)
NMPA Guideline on AI
Examples of a use case:
Electrocardiogram analysis with AI
Case Study: Revolutionizing Visual Inspection with Artificial Intelligence Dr Mario Holl
Pain points in visual inspection
A machine-agnostic AI solution Framework
Strategies for developing robust and reliable AI models
Qualification and necessary documentation
Results of AI powered visual inspection
Case Study: Challenges and Limitations of Machine Learning Systems in Automated Visual Inspection Systems Haluk Dönmez
Introduction and Basics
Application and Challenges
Approach and ML Training
Testing and Qualification
Conclusion
Enhancing Production Efficiency: An End-to-End Process Perspective through Data Science Julius Kittler / Thomas Singer
Introduction and Overview of the Use Case
Consolidating the Tablet Production Process into a Comprehensive Dataset
Theoretical Basics of Machine Learning and Gradient Boosting Decision Trees
Application of Machine Learning to Identify Critical Factors Impacting Production Target Variables
Key Takeaways and Lessons Learned
Recording from 10 October 2023 Duration of Recording: approx. 5:01 h
This course is part of the GMP Certification Programme "ECA Certified Computer Validation Manager" Learn more
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