Digitalisation & Artificial Intelligence

Objectives

Reasons to attend this conference:

  • You will get an overview of current digitalisation and artificial intelligence in the pharmaceutical industry.
  • You will learn how efficiency and quality can be improved through the implementation of digitalisation.
  • In various case studies of pharmaceutical companies, projects from practice are presented.

Background

New forms of digitalisation are finding their way more and more into the pharmaceutical industry. If the automation stage is already well advanced, topics such as AI, IOT and Industry 4.0 are waiting in the wings. Artificial Intelligence has arrived in the general public since Chat GPT and Bard but has also found its way into the pharmaceutical industry.
Therefore, the track will primarily be dedicated to Artificial Intelligence and present and discuss initial experience from established projects. The focus will be on GxP-relevant aspects from the perspective of the pharmaceutical industry and the regulatory authorities.


Digitalisation & Artificial Intelligence

click on the image to download the programme as PDF.

Target Audience

The event is directed at specialists from the pharmaceutical industry as well as at engineers and planners who have to deal with digitalisation and AI projects. It particularly addresses the departments IT, Production, Quality assurance and Engineering / Technology.

Registration


Moderators

Stefan Münch, Körber Pharma Consulting
Yves Samson, Kereon

Detailed Programme

Tuesday, 19 March 2024

An Overview on AI/ML in GxP Environments
Stefan Münch, Körber Pharma Consulting
Yves Samson, Kereon

  • Basics of AI/ML
  • AI/ML along the pharmaceutical value chain
  • Promising use cases in pharma manufacturing
  • Regulatory challenges of AI/ML in GxP
  • Risks and Controls of AI/ML in GxP

Regulatory Requirements and Inspector’s View on Artificial Intelligence
Ib Alstrup, Danish Medicines Agency, DMA

Use of AI in daily Deviation and CAPA Management
Dr Sven Alexander Moritz, Sanofi-Aventis Deutschland

  • Use of Ai to discover early signals in deviation trending
  • Shorten investigation time
  • Improve CAPA definition and implementation based on real life data

Validation of AI/ML in the GxP Environment
Dr Ulrich Köllisch, GxP-CC

  • Regulatory overview: What are the new guidelines, best industry practices and discussion papers on AI/ML validation (EMA, FDA)
  • Prerequisites for AI/ML validation (Data Governance) and the AI/ML model Lifecycle
  • Two case studies: High Level Risk Assessment for NLP implementation in the QMS and for visual inspection; Application of ICHQ9 (R1) with a patient-centric mindset
  • Conclusion and Outlook: An industry overview of the current status and what is to be expected next

When Data runs wild – Data Integrity as a Control Tool for AI
Galit Lisaey, Gal.IT Data Integrity Consulting

  • The Importance of Data Integrity in Decision-Making
  • Challenges: Transition to Automated Systems
  • Data Integrity as an Organizational Interest
  • Risks and Reliability in AI-Based System
  • Immediate Solutions: Regulatory Tools and Methodologies

Simplified Extractables and Leachables Assessment using prior Knowledge and IT Solutions
Dr Armin Hauk, Sartorius Stedim Biotech

  • Prediction of extractables profiles for SU devices of different sizes and complex assemblies
  • Calculation of exposure data, with a subsequent automated safety-assessment; including a discussion of deviations and propagation of deviations
  • Equivalency study of extractables profiles of a SU assembly before and after a component change, including the evaluation of the impact on the safety assessment
  • Using the system to extrapolate extractables data to USP <665> conditions for a safety assessment of a large volume injectable drug product

Wednesday, 20 March 2024

Applying Industry 4.0 – What are the Use Cases and how can they be successfully implemented
Dr Andreas Aemissegger, Bachem
Yvonne Duckworth, CRB

  • The pharma industry is ready to move into the digital age and hungry for 4.0 advancements, but decision-makers are still unsure where and how to apply these technologies
  • The speakers examine Pharma’s use of Industry 4.0 from three angles: the owner, the service provider, and the governance
  • Get an overview and examples of Industry 4.0 concepts along typical manufacturing processes within BACHEM AG  
    Learn how the AEC industry is incorporating 4.0 into pharma facilities

How the Digital Transformation could really improve Inspections & Audits Effectiveness and Efficiency
Dr Jean-Denis Mallet, Former head of the French Inspection Department AFSSAPS, Pharmaplan

  • What e-technologies could add to the desired transparency of the inspection / audit process?
  • How confidence can be built through the e-technological approach?
  • Is 'AI' a Dr Jekyll approach or a Mr Hyde too?
  • Conclusion: how to help 'AI' in the inspection / audit process?

Quality Contracts in the Era of Digitalisation and AI
Ioannis Tsiagkas, Pharmathen

  • Digitalisation and AI can be utilized within pharmaceutical quality contracts to improve efficiency, accuracy, and compliance
  • Document Management: AI-powered document management systems
  • Supplier Quality Management: AI can assist in evaluating and monitoring the quality performance of suppliers involved in pharmaceutical manufacturing
  • Compliance Monitoring: AI systems can detect deviations from contractual obligations and regulatory standards, providing real-time alerts and facilitating corrective actions
  • Real-time Quality Monitoring: AI-powered monitoring systems can continuously collect and analyze data from various sources

Bridging Innovation and Compliance: Open-Sourcing Data Computation Platform (DCP) for GxP-Compliant Pharma 4.0 Advancements
Dr Tobias Ladner, Roche Diagnostics

  • Introducing Data Computation Platform (DCP): Enabling GxP-Compliant Advancements and Supporting Tools in One Platform
  • Validation: Ensuring GxP Compliance and Reliability of the Data Computation Platform (DCP)
  • Use Case: Leveraging DCP for GxP-Compliant Multivariate Data Analytics Process Monitoring
  • Journey Towards Open-Sourcing: Overcoming Challenges and Fostering Collective Progress

Enabling ML Applications by a “Data Expert Team“
Dr Jörg Stüben, Boehringer Ingelheim International
Martin Heitmann, d-fine

  • Relevance of data in ML enabled applications
  • The Subject Matter Expert‘s view: Searching for the right use case
  • The Data Scientist’s view: Searching for the right method
  • Reaching the common goal: The „Data Expert Team“ featuring insights from real world examples

Panel/Plenary Discussion

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