The AI for Medical Affairs Course

• Defining the world of AI: Machine Learning, Neural Networks, Generative AI (GenAI) and Large Language Models (LLMs)
• Overview of how AI has been used in pharma to date (e.g., in R&D)
• Classification of GenAI applications: personal use – developmental projects – enterprise solutions
• Explaining the current world of LLMs, their chatbots, and how you can use them as a “calculator for words”

• Practical examples of using GenAI chatbots in day-to-day tasks
• Tips & tricks for optimal performance, such as:
  • Creating and clearing the context window
  • How to prompt for effective results
• Discussion: Sharing experiences and tips for maximising GenAI benefits 

Participants will explore how language GenAI tools, such as GPT, Claude, and Copilot, can assist in generating a medical slide deck.

Working in small groups, you will:

• Experiment with AI to tackle specific steps, such as summarising clinical data, creating slide titles, and drafting key messages.
• Discuss and evaluate which steps the AI supports most effectively.
• Share observations on optimising AI outputs for accuracy and relevance.

By the end of the session, participants will better understand how GenAI can streamline slide creation while maintaining medical communication standards.

• Ethical guidelines for GenAI usage in pharma companies
• Addressing challenges: Bias, data privacy and model updates 

Participants will work in small groups to tackle ethical challenges in generative AI through interactive, quiz-like scenarios. Each group will receive case studies or hypothetical situations (e.g., bias in AI outputs, potential data privacy breaches) and will:

• Identify key ethical risks by answering multiple-choice and open-ended questions.
• Propose solutions for mitigating these risks.
• Discuss how their recommendations align with their own company’s rules and policies, sharing insights with the group.

The session will conclude with a plenary discussion to highlight common themes and best practices. Templates will be provided to guide group discussions and capture insights. 

• Detailed walkthrough of a recent Medical Affairs project that used AI
• Challenges faced and solutions implemented
• Outcomes and lessons learned
• Q&A session

• Key success factors: Data quality and strategic alignment
• Developing a strategic roadmap for AI implementation
• Criteria for prioritising projects 

Participants will use a planning framework, which evaluates AI projects based on their ability to deliver efficiency, value, and innovation. Working in small groups, they will:

• Identify a potential use case for GenAI in their organisation (e.g., automating content creation, improving HCP engagement).
• Assess the project idea using the framework to determine whether it meets the criteria for a good AI project.
• Use GenAI tools (e.g., GPT or Claude) to test and refine ideas, generating brainstorming outputs or exploring alternative approaches.

By the end of the session, participants will have a prioritised use case and initial ideas for how AI could be applied, setting the stage for more detailed planning in Part 2.

• Introduction to AI image, video, and audio generation
• Practical use cases for pharma brands
• Example of using image analysis and generation for a pharma brand 

Participants will use a structured planning framework to refine and develop GenAI project ideas that deliver efficiency, value, and innovation. In small groups, they will:

• Refine project concepts: Build on ideas from Day 1, considering key factors such as stakeholder needs, business impact, and alignment with strategic goals.
• Prototype outputs: Use multi-modal AI tools (e.g., MidJourney for images, Runway for video, ElevenLabs for voice synthesis) to create prototypes that illustrate their project concepts.
• Prepare and deliver presentations: Each group will present their refined project plans and prototypes to the wider group, showcasing: 
  • The problem their project addresses.
  • How GenAI will deliver a solution.
  • A demonstration of their prototypes, created with AI. 

• What’s coming up in AI: Emerging technologies and trends
• The future of AI coaching and its applications in Medical Affairs
• Exploring the potential of multi-modal and other developments in GenAI 

Participants will:

• Learn how GPT can generate Python scripts for routine tasks like parsing CSV files or summarising data.
• Run GPT-generated scripts in Google Colab, experimenting with outputs.
• Edit the code to customise results and discuss practical applications in their day-to-day roles.