Training: Use of AI Power in your Medical Device lifecycle

Accelerate medical device development, approval, and post-market activities with compliant use of LLMs.

Learn in just 2 half days how to leverage large language models (LLMs) in medical device development – from the initial idea to post-market surveillance.
Boost your productivity, stay ahead of disruption, and future-proof your role in a rapidly evolving knowledge-based industry. Those who adapt and learn to work smarter with AI will be better positioned to thrive in the years ahead.

Introduction / Overview

Turn generative AI from a promising experiment into a practical accelerator for medical device development, Including regulatory tasks. This hands-on training shows professionals responsible for the quality of medical devices how to use large language models across the product lifecycle – from product ideas and requirements to risk management, documentation, approval, and post-market activities – while addressing regulatory expectations and responsible use.

This training is arranged by GBA Key2Compliance, in collaboration with Johner Institute.

Learning Outcomes / Benefits

• Assess where and how LLMs can support development, approval, quality management, and post-market activities.
• Write effective prompts and structure tasks to produce more reliable, useful outputs.
• Select when to use prompts, system prompts, structured data, RAG, model parameters, fine-tuning, agents, and agentic workflows.
• Apply generative AI to requirements, risk analysis, architecture, test cases, software development, and document generation and review.
• Recognize the prerequisites, competencies, limitations, and governance needs associated with AI.
• Explain and demonstrate a compliant approach to AI use to notified bodies and authorities.
• Identify practical next steps towards an AI strategy map and an AI-first organization.

Course Content

• Module 1: Medical device lifecycle and AI opportunities – Map lifecycle activities and deliverables where LLMs can create measurable value.
• Module 2: Generative AI models and tools – Understand model types, providers, model selection, operating principles, capabilities, and limitations.
• Module 3: Prompting and context engineering – Practise prompt techniques, task structuring, prompt chaining, structured outputs, model parameters, RAG, MCP, and fine-tuning decisions.
• Module 4: Guided medical device use cases – Apply LLMs to product ideas, customer and product requirements, hazards and risk analysis, system architecture, software development, test cases, and document generation and review.
• Module 5: AI technologies and infrastructure – Explore agents, agentic workflows, tools, skills, and options for operating a company-owned AI infrastructure.
• Module 6: Compliance and organizational adoption – Address requirements for AI use in quality management processes and outline a roadmap towards an AI-first company.

Target Audience

Who should attend: This course is ideal for employees of medical device and IVD manufacturers who are responsible for product development, quality assurance, regulatory affairs, or product lifecycle activities and want to adopt AI efficiently and responsibly. >
Relevant roles include development managers, engineers and developers, regulatory affairs professionals, quality managers, and product managers.

Prerequisites

• You should have basic knowledge of AI and a general understanding of medical device development processes and the product lifecycle.
• It is helpful to have experience working with digital technologies.
• You should be open to integrating innovative AI-supported approaches into your daily work.

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