Generative Ai In Drug Regulatory Affairs

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Generative Ai In Drug Regulatory Affairs

Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 677.54 MB | Duration: 1h 49m

Top 5 Use Cases in Regulatory Affairs for application of Generative AI

What you'll learn
Application of Generative AI in Drug Regulatory Affairs
Generative AI Fundmentals
Use of ChatGPT for Text Processing Based Operations
Implementation Details of Generative AI Applications
Requirements
Foundational Understanding of Drug Regulatory Affairs
Description
In this comprehensive tutorial, you will explore the cutting-edge application of Generative AI within the drug regulatory affairs landscape. This course dives into real-world use cases, including:Regulatory Intelligence: Automating the analysis of regulatory trends and gathering insights.Content Creation: Streamlining the generation of regulatory submission documents, labels, and reports.Language Translation: Enhancing multilingual submissions and compliance documents with AI-powered translation tools.Named Entity Recognition (NER): Extracting critical information from large datasets to improve efficiency in compliance and submissions.Data Analysis: Leveraging AI for advanced analysis and insights from clinical trials, safety data, and regulatory submissions.Besides, it will also cover use cases related to personal productivity and productivity at workplace. Amongst other topics, it will try to explain in brief, some foundational concepts of the technology behind Generative AI, products available in the market and capabilities of Generative AI in general.This course includes quiz assignments, mini-project tasks, and real-time examples to reinforce learning and allow you to practice applying these AI techniques in regulatory affairs scenarios. By the end of the course, you'll be able to identify high-impact areas for AI implementation in drug regulatory processes.Disclaimer:This training is for educational purposes only. Learners should exercise due diligence before applying any concepts in real-time business environments.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 What to Expect from the Tutorial
Section 2: Let's Set the Foundations of Generative AI
Lecture 3 What is Generative AI?
Lecture 4 AI Vs Generative AI
Lecture 5 Technology Behind Generative AI
Lecture 6 Generative AI Products in the Market
Lecture 7 How to find Use Cases for Generative AI Application
Lecture 8 Content Creation in Regulatory Affairs
Section 3: Regulatory Intelligence using Generative AI
Lecture 9 Introduction - What is Regulatory Intelligence?
Lecture 10 Generative AI for Regulatory Intelligence
Lecture 11 Demonstration of Regulatory Intelligence with ChatGPT
Lecture 12 Demonstration of Building a Custom GPT
Section 4: Regulatory Translation Using Generative AI
Lecture 13 Introduction - Language Translation in Regulatory Affairs
Lecture 14 Translation Capability of Generative AI
Lecture 15 Demonstration of Translation using Generative AI
Lecture 16 Evaluation of Language Translation
Lecture 17 Reverse Translation and Evaluation
Section 5: Named Entity Recognition using Generative AI
Lecture 18 Introduction - Named Entity Recognition (NER) in Drug Regulatory Affairs
Lecture 19 Named Entity Recognition - Traditional vs Gen AI approach
Lecture 20 Demonstration of Named Entity Recognition using ChatGPT
Section 6: Implementing a Generative AI Solution
Lecture 21 Solution Implementation Approaches
Lecture 22 Step by Step Approach for Developing a Generative AI Solution
Lecture 23 Fine tuning a Model
Lecture 24 Integrating with Data Sources
Section 7: Issues and Constraints with Generative AI Solutions
Lecture 25 Issues with Generative AI - Hallucination
Lecture 26 Creativity Vs Consistency - What's Important in Regulatory Affairs
Lecture 27 Prompt Engineering - Remediating Hallucination
Lecture 28 Content Grounding - Remediating Hallucination
Section 8: Conclusion
Lecture 29 Thank you
Drug Regulatory Affairs Professionals,Pharmacovigilance Professionals,Pharmaceutical Professionals,IT Professionals working in Drug Regulatory Affairs

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