2026-06-12 2026-06-12 , online online, 1,790 € zzgl. MwSt. Maik Lange https://forum-institut.de/seminar/26102227-ai-in-pharma-foundations-use-cases-and-implementation-in-europe/referenten/26/26_10/26102227-seminar-online-ai-in-the-pharmaceutical-industry_lange-maik.jpg AI in Pharma: Foundations, Use Cases and Implementation in Europe

Learn how artificial intelligence is transforming the pharmaceutical industry in Europe. This foundation course covers AI concepts, key use cases, EU AI Act and GDPR essentials, GxP implications and practical steps to implement AI safely and at scale.

Topics
  • Core AI concepts for pharmaceutical companies
  • EU perspective: AI Act and GDPR essentials for AI projects
  • Key AI use cases across the pharmaceutical value chain
  • Roles and responsibilities for the "human in the loop" in AI-supported GxP processes
  • AI as a strategic differentiator in pharma: from proofs of concept and pilots to scaled solutions
  • Systematic selection and evaluation of AI use cases
  • Governance and risk management for AI projects in pharmaceutical organisations
  • Practical implementation and evaluation of an AI use case, including change management


Who should attend
This course is designed for professionals and leaders in the pharmaceutical industry who already have a basic understanding of artificial intelligence and now want to deepen their skills for practical application.
Basic understanding means you have heard of common AI tools such as ChatGPT or Gemini and can roughly distinguish between the terms AI, machine learning and large language models (LLMs).

By attending, you will significantly deepen your understanding of AI in the pharmaceutical context and strengthen your competence in identifying, evaluating and implementing AI use cases in line with European requirements.
Aims and objectives
Artificial intelligence is reshaping core processes in the pharmaceutical industry at remarkable speed. At the same time, the EU AI Act, GDPR and GxP requirements set a demanding framework for governance, data quality and documentation.

This two-day foundation course provides a structured overview of key AI concepts, concrete use cases along the pharmaceutical value chain and proven approaches for implementation in European organisations. Experienced speakers from leading pharmaceutical companies (including AstraZeneca, Merck and Bayer) share how to move AI initiatives from first pilots to scalable solutions.

This course is the core module of the qualification course "AI Management in the Pharmaceutical Industry". You can find the full programme of the qualification course under webcode 60012205.

The course can alternatively be booked as a stand-alone module.
Your benefit

After this course, you will be able to

  • speak confidently about core AI concepts in a pharma specific way
  • distinguish between different types of AI systems and understand where they can add value in your organisation
  • recognise high risk versus lower risk AI use cases from both a regulatory and a business perspective
  • understand the key elements of the EU AI Act and GDPR that affect AI initiatives in pharmaceutical companies
identify and evaluate promising AI use cases using clear criteria
  • anticipate typical pitfalls that prevent AI pilots from scaling and know how to address them
  • structure the implementation of an AI use case, including change management and governance aspects

Online Seminar - AI in the Pharmaceutical Industry

AI in Pharma: Foundations, Use Cases and Implementation in Europe

Benefits
  • Professional education provider with more than 45 years of experience
  • Learn how to identify, prioritise and implement AI use cases
  • Officially certified according to ISO 9001 and ISO 21001

Webcode 26102227

Jetzt buchen

JETZT Buchen
Referenten

Maik Lange

Bayer AG, Berlin, GERMANY

Generative AI Transformation Lead & Mission Master, Visionary Strategist Marketing & Healthcare Innovation Enthusiast

Oliver Patel

AstraZeneca, Barcelona, SPAIN

Head of Enterprise AI Governance; Oliver Patel is Head of Global Enterprise AI Governance at AstraZeneca, overseeing responsible AI across a 80,000+ employee organization and a complex AI ecosystem. He is a former academic and UK Government policy adviser, experienced public speaker and commentator (BBC, Sky News, CNN) and trusted translator between technical and non-technical stakeholders.

Álex Turpin

AstraZeneca, Barcelona, SPAIN

Head AI Governance R&D; Alex Turpin is Head of AI Governance, R&D at AstraZeneca, where he leads the design and evolution of governance frameworks for advanced AI systems across research and development. With a PhD in physics and more than 15 years of experience across deep tech, healthcare, and AI-driven innovation, he combines deep technical understanding with a strong systems and innovation mindset. His background spans academia, neuroscience-related research, health-tech startups, and senior AI leadership roles, including Technical Director positions in fast-growing environments. At AstraZeneca, Alex focuses on one of the most critical challenges facing the industry today: how can we make sure that governance of technology (including AI) is not a limiting control layer, but a strategic capability that enables speed, trust, and responsible innovation at scale. He is also a co-founder of a deep-tech AI startup in remote health and ambient monitoring, and is actively involved in shaping thought leadership at the intersection of AI, governance, and real-world clinical impact.

Wei Wannhoff

Merck Healthcare KGaA, Darmstadt, GERMANY

Associate Director Technology and Data Analytics; After completing her bioinformatics studies in Germany, Wei gained hands-on experience in data management and SAE management in clinical research. She is an experienced professional with 15 years of industry experience and a strong focus on pharmacovigilance and drug safety management. Throughout her career, she has combined excellence, innovation, and compliance within drug safety and safety data analytics. With a comprehensive understanding of regulatory requirements and a proven track record in data analysis, software tool development, and compliance management, Wei has demonstrated expertise in leading cross-functional teams and driving process improvements. As an AI Champion, she leads internal AI use cases in the drug safety domain.

Alles auf einen Blick

Termin

13 - 14/10/2026

13 - 14/10/2026

Zeitraum

Day 1: 09:00 - 17:00 CET
Day 2: 09:00 - 14:30 CET

Day 1: 09:00 - 17:00 CET
Day 2: 09:00 - 14:30 CET
Veranstaltungsort

online

online

Downloads
Market Access: Basic Concepts and Processes
Market Access: Basic Concepts and Processes
Gebühr

Event - 1,790€ plus tax
The participation fee includes documentation for download, a certificate, access to the Learning Space and technical support including PreMeeting.

Event - 1,790€ plus tax
The participation fee includes documentation for download, a certificate, access to the Learning Space and technical support including PreMeeting.

Inhouse-Angebote
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Inhouse-Angebot anfordern

Jetzt buchen

Your contact

Leila Dörfler
Team Leader

+49 6221 500-695
l.doerfler@forum-institut.de

Details

Learn how artificial intelligence is transforming the pharmaceutical industry in Europe. This foundation course covers AI concepts, key use cases, EU AI Act and GDPR essentials, GxP implications and practical steps to implement AI safely and at scale.

Topics

  • Core AI concepts for pharmaceutical companies
  • EU perspective: AI Act and GDPR essentials for AI projects
  • Key AI use cases across the pharmaceutical value chain
  • Roles and responsibilities for the "human in the loop" in AI-supported GxP processes
  • AI as a strategic differentiator in pharma: from proofs of concept and pilots to scaled solutions
  • Systematic selection and evaluation of AI use cases
  • Governance and risk management for AI projects in pharmaceutical organisations
  • Practical implementation and evaluation of an AI use case, including change management


Who should attend
This course is designed for professionals and leaders in the pharmaceutical industry who already have a basic understanding of artificial intelligence and now want to deepen their skills for practical application.
Basic understanding means you have heard of common AI tools such as ChatGPT or Gemini and can roughly distinguish between the terms AI, machine learning and large language models (LLMs).

By attending, you will significantly deepen your understanding of AI in the pharmaceutical context and strengthen your competence in identifying, evaluating and implementing AI use cases in line with European requirements.

Aims and objectives

Artificial intelligence is reshaping core processes in the pharmaceutical industry at remarkable speed. At the same time, the EU AI Act, GDPR and GxP requirements set a demanding framework for governance, data quality and documentation.

This two-day foundation course provides a structured overview of key AI concepts, concrete use cases along the pharmaceutical value chain and proven approaches for implementation in European organisations. Experienced speakers from leading pharmaceutical companies (including AstraZeneca, Merck and Bayer) share how to move AI initiatives from first pilots to scalable solutions.

This course is the core module of the qualification course "AI Management in the Pharmaceutical Industry". You can find the full programme of the qualification course under webcode 60012205.

The course can alternatively be booked as a stand-alone module.

Your benefit

After this course, you will be able to

  • speak confidently about core AI concepts in a pharma specific way
  • distinguish between different types of AI systems and understand where they can add value in your organisation
  • recognise high risk versus lower risk AI use cases from both a regulatory and a business perspective
  • understand the key elements of the EU AI Act and GDPR that affect AI initiatives in pharmaceutical companies
identify and evaluate promising AI use cases using clear criteria
  • anticipate typical pitfalls that prevent AI pilots from scaling and know how to address them
  • structure the implementation of an AI use case, including change management and governance aspects

Detailed programme

Day 1: 09:00 - 17:00 CET
Day 2: 09:00 - 14:30 CET

09:15

Álex Turpin

What is Artificial Intelligence? Core concepts for pharma
  • Definitions and terminology: Artificial Intelligence, Machine Learning, Deep Learning
  • Types of AI systems and where they typically show up in pharma organisations
  • Machine Learning and Neural Networks
  • Generative AI - Foundation Models, LLMs and Diffusion Models

10:45 Break


11:00

Oliver Patel

Legal & Governance Essentials for AI in Pharma in Europe
  • AI Act & High risk AI in pharma practice
  • GDPR and data for AI: essentials for non lawyers

12:45 Lunch break


14:00

Wei Wannhoff

AI in Pharma: key use cases across core functions
  • Overview of AI use cases across key functions: R&D and clinical development, regulatory affairs, pharmacovigilance, medical affairs etc.
  • Distinguishing lower risk vs. higher risk AI use cases from a business perspective

15:30 Break


15:45

Wei Wannhoff

AI across the pharmaceutical value chain - with a focus on GxP data and documentation
  • Specific challenges in GxP regulated environments when introducing AI:
    • Data integrity and data quality in GxP systems
    • Traceability, audit trails and documentation requirements
    • Roles and responsibilities for the "human in the loop" in AI supported GxP processes
  • How inspectors and quality units are likely to look at AI supported GxP processes

17:00 End of Day 1


09:00

Maik Lange

AI as a strategic differentiator - from pilots to scale
  • Why AI matters for competitiveness in pharma
  • Typical patterns: proof of concepts, pilots and the "pilot purgatory" problem
  • What distinguishes successful, scaled initiatives from never ending pilots

09:30

Álex Turpin

Selecting and evaluating AI use cases
  • How to find good AI use cases in your organisation
  • Evaluation criteria:Business value and impact
    • Technical feasibility and data readiness
    • Multi country feasibility in European organisations
  • Typical reasons why pilots do not scale - and how to address them
  • Collaboration with external partners - when does it make sense?

11:00 Break


11:15

Álex Turpin

Keeping AI projects safe and under control
  • Why AI in pharma needs governance - Being clear about the purpose ("intended use")
    • What the AI system is supposed to do and in which context (which data, which process)
    • What it is not allowed to do (boundaries)
  • Working with vendors - what to ask and responsibilities

12:15 Lunch break


13:15

Wei Wannhoff

Implementation and evaluation of an AI Use Case together with the participants
  • What needs to be considered when moving into implementation?
  • What are the requirements for effective change management?

14:30 End of day 2


Your benefit

Qualification Course "AI Management in the Pharmaceutical Industry"

This seminar is part of the qualification course "AI Management in the Pharmaceutical Industry". Further information is available under webcode 60012205.

Technical requirements

You need a reliable Internet connection to take part in our online events. To have the best possible learning experience, we recommend that you use the latest version of the Microsoft Edge or Google Chrome browsers. You will need a headset, loudspeaker or telephone to play the audio. Further information is available here. Please check beforehand that your microphone or headset and camera are working properly. Do not access our services from a VPN since there are issues with the audio over such connections.

We have integrated Zoom video conferencing software into our Learning Space for our online training courses. If you are not authorised to use Zoom, please get in touch with us so we can make alternative arrangements for you to take part in our online training.

This distinguishes our events

of 5 stars of all ratings from 2025

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