(AI) Artificial Intelligence in a GxP Environment - Live Online Training With a half-day Pre-Training Course on IT Basics for AI

9/10 October 2023

Seminar Nr. 21232

This course is part of the GMP Certification Programme "ECA Certified Computer Validation Manager". Learn more.

Unser Seminarservice

Kosten

*ECA-Member:**	EUR 1490,--
*Non ECA Member:**	EUR 1690,--
*EU/GMP Inspectorates:**	EUR 990,--
*APIC Member Discount:**	EUR 1590,--

Alle Preise zzgl. MwSt. Wichtige Hinweise zur Umsatzsteuer.

Zur Anmeldung

* auch unkompliziert per Kreditkarte bezahlbar

Rückfragen unter:
Tel.: 06221 / 84 44 0 E-Mail: info@concept-heidelberg.de

Sprecher

Haluk Dönmez, B. Braun, Melsungen, Germany
Christophe Girardey, wega Informatik, Basel, Switzerland
Dr Mario Holl, INSPECTIFAI, Karlsruhe, Germany
Julius Kittler, Merck, Darmstadt, Germany
Dr Hadj Latreche, F. Hoffmann-La Roche, Basel, Switzerland
Stefan Münch, Körber Pharma Consulting, Karlsruhe, Germany
Yves Samson, Kereon, Basel, Switzerland
Nicolas Schaltenbrand, Wega Informatik, Basel, Switzerland
Thomas Singer, Merck, Darmstadt, Germany
Dr Arno Terhechte, GMP Inspectorate / Bezirksregierung Münster, Germany

Zielsetzung

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

Hintergrund

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.

Zielgruppe

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.

Programm

Pre-Training Course on IT Basics for AI - 9 October 2023

Introduction to Artificial Intelligence (AI)
Stefan Münch / Yves Samson

History of AI
Types of AI
Real life examples

Introduction to Machine Learning (ML)
Stefan Münch / Yves Samson

Technological Basics
Different learning / training Methods
Example use cases

AI/ML in Pharma, Biotech and Med Devices
Stefan Münch / Yves Samson

Challenges for pharmaceutical Industry
The GAMP-perspective on AI/ML
GMLP: SDLC for AI/ML
Use cases / Known scenarios

Data Science as Basis for AI
Nicolas Schaltenbrand & Christophe Girardey

Pre-requisites for AI: Data Governance, Data Science, Data Understanding, FAIRification.
Specificities in the lab
- Lack of standardization, Lack of connectivity.
- Chances with standards: AniML, SiLA
Specificities in clinical development

The Regulatory Landscape for AI/ML
Stefan Münch / Yves Samson

US / FDA: Expectations and guidance
EU / EMA: Expectations and guidance
Special case: Generative AI

(AI) Artificial Intelligence in a GxP Environment - 10 October 2023

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

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