Generative Ai In Drug Regulatory Affairs

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