AI & Digital Transformation for Pharma & Biotech

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AI & Digital Transformation for Pharma & Biotech

Instructors: Starweaver

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4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Analyze the impact of AI-driven digital transformation in Pharma & Biotech.
Analyze and compare AI applications across pharma operations and commercial ecosystems.
Evaluate AI tools, platforms, and data systems used in Pharma & Biotech.
Assess governance, regulatory, and strategic dimensions of AI in Pharma & Biotech.

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There are 4 modules in this course

Discover how AI in Pharma and Digital Transformation Biotech are reshaping the life sciences industry with this comprehensive course, AI and Digital Transformation for Pharma and Biotech. Designed for pharmaceutical professionals, clinical research staff, and healthcare graduates, this beginner-to-intermediate program explores real-world applications of AI Drug Discovery, Clinical Trial AI, and Precision Medicine AI across the entire pharma value chain. Learners will gain practical, strategy-focused insights into how artificial intelligence accelerates molecule identification, optimizes clinical trial design, and strengthens regulatory compliance — all without requiring any coding or programming background. Bridging life sciences expertise with digital innovation, this course empowers professionals to identify high-impact AI opportunities, evaluate emerging technologies, and lead data-driven transformation initiatives within their organizations.

From Pharma 4.0 and Smart Pharmaceutical Manufacturing to Biotech Data Analytics and Healthcare Digital Innovation, this course delivers hands-on exposure to leading AI tools and platforms used across drug discovery, manufacturing, supply chain, and commercial operations. Through interactive labs, role-play simulations, and a capstone project on building a strategic AI transformation roadmap, learners will develop critical skills in AI Strategy in Pharma, Clinical Data Analytics, and Regulatory & Ethical AI Assessment. By course completion, participants will be equipped to evaluate AI-driven digital transformation strategies, assess governance and compliance frameworks, and confidently contribute to innovation initiatives — positioning themselves at the forefront of AI in Life Sciences and the future of intelligent, data-driven pharmaceutical development.

This module introduces the core principles of Artificial Intelligence and digital transformation within pharmaceutical and biotechnology industries. It explores foundational technologies, strategic drivers, and the evolving role of AI across drug development and healthcare innovation ecosystems.

What's included

11 videos2 readings1 assignment1 peer review1 discussion prompt

11 videosTotal 78 minutes

Welcome and Course Goals 5 minutes
Module Introduction 3 minutes
Overview of Artificial Intelligence 6 minutes
AI Technologies in Life Sciences 6 minutes
Benefits and Challenges of AI Adoption 6 minutes
Traditional v/s. AI-Driven Drug Discovery 7 minutes
AI Tools for Drug Screening 10 minutes
Predictive Modeling in Drug Research 9 minutes
AI-Enhanced Clinical Trial Design 8 minutes
AI in Patient Recruitment 10 minutes
Predictive Analytics in Trial Outcomes 9 minutes

2 readingsTotal 10 minutes

Welcome to the Course: Course Overview 5 minutes
AI Applications in Drug Discovery 5 minutes

1 assignmentTotal 20 minutes

Introduction to AI and Digital Transformation in Pharma and Biotech20 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Identify AI Use Cases in a Pharma Workflow10 minutes

1 discussion promptTotal 10 minutes

Rethinking Drug Discovery Timelines with AI10 minutes

This module explores how Artificial Intelligence is applied across the pharmaceutical and biotechnology value chain. Learners will examine AI use cases in manufacturing, supply chain optimization, quality assurance, and commercial operations, highlighting efficiency, compliance, and scalability benefits.

What's included

10 videos1 reading1 assignment1 peer review1 discussion prompt

10 videosTotal 71 minutes

Module Introduction 4 minutes
Smart Manufacturing and Automation 7 minutes
Predictive Maintenance in Pharma Plants 7 minutes
How Artificial Intelligence Enhances Quality Control in Manufacturing 7 minutes
Supply Chain Digitization 5 minutes
How AI Tools Improve Demand Forecasting Accuracy in Supply Chains7 minutes
Logistics and Distribution Optimization 7 minutes
AI in Pharma Sales and Marketing 7 minutes
AI-Powered CRM and Engagement Tools 12 minutes
Market Access and Pricing Analytics 8 minutes

1 readingTotal 5 minutes

AI in Pharmaceutical Manufacturing 5 minutes

1 assignmentTotal 20 minutes

AI Applications Across Pharma Value Chain20 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Drug Analysis by Chatbot10 minutes

1 discussion promptTotal 10 minutes

Can AI Prevent the Next Drug Shortage?10 minutes

This module explores the technological infrastructure enabling AI adoption in pharmaceutical and biotech industries. Learners will examine AI platforms, specialized pharma tools, data ecosystems, and integration frameworks that support research, regulatory, and operational intelligence.

What's included

10 videos1 reading1 assignment1 peer review1 discussion prompt

10 videosTotal 77 minutes

Module Introduction 5 minutes
Overview of Pharma AI Platforms 8 minutes
Using AI Assistants in Pharma Workflows 9 minutes
Evaluating AI Tool Capabilities 8 minutes
Pharma Data Sources and Types 7 minutes
Data Integration Platforms 9 minutes
Interoperability and Data Standards 8 minutes
Introduction to Real-World Evidence 7 minutes
AI Analytics for Safety Monitoring 8 minutes
Biomarker Discovery Using AI 8 minutes

1 readingTotal 5 minutes

AI Applications in Drug Discovery & Delivery 5 minutes

1 assignmentTotal 20 minutes

AI Tools, Platforms and Data Ecosystems in Pharma20 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Critical Analysis of AI-Driven Drug Discovery Insights10 minutes

1 discussion promptTotal 10 minutes

Choosing the Right AI Platform10 minutes

This module explores regulatory frameworks, governance models, and ethical considerations surrounding AI adoption in pharmaceutical and biotechnology sectors. It also examines future innovation trends, strategic implementation roadmaps, and global compliance requirements.

What's included

10 videos1 reading1 assignment2 peer reviews1 discussion prompt

10 videosTotal 73 minutes

Module Introduction 4 minutes
Global AI Regulatory Landscape 9 minutes
AI Validation and Compliance Models 7 minutes
Risk Management in AI Systems 7 minutes
Ethical Risks of AI in Healthcare 6 minutes
Implementing Responsible AI Frameworks 7 minutes
Patient Data Privacy and Security 7 minutes
Emerging AI Innovations in Pharma 9 minutes
Building an AI Transformation Roadmap 9 minutes
Workforce and Skill Transformation 9 minutes

1 readingTotal 5 minutes

AI Regulatory Guidelines in Pharma 5 minutes

1 assignmentTotal 20 minutes

Governance, Compliance and Future of AI in Pharma20 minutes

2 peer reviewsTotal 70 minutes

Hands-On-Learning: AI Compliance Risk Assessment Exercise10 minutes
Project: Designing a Strategic AI Transformation Roadmap60 minutes

1 discussion promptTotal 10 minutes

Building Responsible AI Governance10 minutes

Instructors

Starweaver

STARWEAVER

606 Courses1,250,343 learners

Offered by

STARWEAVER

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