Description
Large Language Models (LLMs) such as ChatGPT and similar AI technologies are opening up new possibilities for data-driven processes in laboratories. They analyze large text and data sets, provide accurate analyses, and support informed decision-making—from automated documentation to the optimization of complex workflows.
The strengths of LLM are also evident in quality management. There, AI tools automatically generate and update documents such as SOPs and audit reports, and assist auditors with planning and reporting. In addition, QM AI makes it easier to search through large and/or complex documentation and answers questions without the need for time-consuming research.
The seminar provides a practical overview of how AI can be integrated into laboratory processes and quality management systems, ranging from automated plausibility checks to innovative documentation solutions.
This seminar is intended for:
- Laboratory supervisors and managers in research, development, and quality control who wish to gain a basic understanding of the use of AI in a laboratory setting.
- Quality managers and quality assurance representatives who want to leverage the benefits of AI to optimize their laboratory and quality processes.
- IT, LIMS, and data managers who are preparing to implement AI solutions in the laboratory setting.
After this seminar
- You have gained a solid understanding of the fundamental concepts and mechanisms of large language models (LLMs).
- you will be able to identify and critically evaluate the potential and limitations of LLMs in a laboratory setting.
- You are familiar with the basic concepts and benefits of using AI in quality management.
- Are you familiar with any possible use cases or techniques for automating documentation in quality management?
- you can develop strategies for planning, conducting, and evaluating AI-assisted audits more efficiently.
You can find the full program here.
