生成式人工智能的有效性取决于数据和提示。

在写作环境中实施生成式人工智能的一个常见误区，是对 LLMs 如何解释提示和分析所接触到的数据的误解。Source data is the lifeblood of regulatory submissions, but the complexity of data and file formats (docx, PDF, tables, figures) can impact the quality of AI generated content for your submission.

This session will provide best practices for leveraging generative AI against various source data files. This will include a close-look at various data sources used to develop documents within the submission dossier, how each data source can be leveraged differently by generative AI, and how users can best prompt the generative AI model to receive desired results.

Key Learning Objectives:

• • Understand the nuances of prompt engineering for the effective use of generative AI.

• • Define how best to use generative AI based on source data available and desired outputs.

• • Identify where and when generative AI is effective in the submission drafting process.

演讲嘉宾： Nick Brown and Liam O’Leary