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CAIP-LS™: AI for Life Sciences & GxP Compliance
Master AI strategy, GenAI, GxP governance, validation & responsible implementation in Life Sciences.
5.03 reviews3 learners
- All Levels
- 3h 51m video
- 57 lectures
- English
- Captions
- Updated 2026
Taught by Rafat Alghubari
- 3h 51m of on-demand video
- 57 lectures across 7 sections
- One-off payment — no subscription
- Lifetime access on web and mobile
- Closed captions (English)
Curriculum
7 sections57 lectures3h 51m total
- 1.1 Welcome to the CAIP-LS Program5:57
- 1.2 Why Artificial Intelligence Matters in Life Sciences5:43
- 1.3 What is Artificial Intelligence?6:37
- 1.4 The Evolution of Artificial Intelligence6:51
- 1.5 Opportunities, Risks, and Limitations of Artificial Intelligence6:48
- Module Assignment — Capstone Workbook Entry #10:19
- Transition to Module 20:14
- 2.1 From Data to Intelligence4:54
- 2.2 How Artificial Intelligence Learns4:15
- 2.3 Types of Artificial Intelligence3:36
- 2.4 Machine Learning Fundamentals4:03
- 2.5 Deep Learning Fundamentals4:16
- 2.6 Generative AI Fundamentals4:44
- 2.7 Essential AI Terminology for Life Sciences Professionals4:39
- Module Assignment — Capstone Workbook Entry #20:17
- Transition to Module 30:13
- 3.1 Large Language Models (LLMs)4:06
- 3.2 Multimodal Artificial Intelligence3:42
- 3.3 AI Agents3:56
- 3.4 AI Copilots3:46
- 3.5 Retrieval-Augmented Generation (RAG)4:10
- 3.6 Fine-Tuning vs RAG3:42
- 3.7 AI Knowledge Bases, Vector Databases & Semantic Search3:47
- 3.8 Selecting AI Models & Building an AI Strategy for Life Sciences4:00
- MODULE 3 CAPSTONE CHECKPOINT — Designing Veritas Pharma's First AI Roadmap0:45
- Transition to Module 40:16
- 4.1 — AI in Drug Discovery3:54
- 4.2 AI in Preclinical Research3:47
- 4.3 AI in Clinical Development3:39
- 4.4 AI in Technology Transfer3:42
- MODULE 4A CHECKPOINT — Capstone Progress0:17
- Transition to Module 4B0:13
- 4.5 AI in Pharmaceutical Manufacturing6:10
- 4.6 AI in Quality Management Systems (QMS)5:39
- Case Study 1:1:17
- Case Study 2:1:04
- 4.7 AI in QC & Analytical Laboratories4:36
- 4.8 AI in Validation & Qualification5:03
- 4.9 AI in Regulatory Affairs4:26
- 4.10 AI in Pharmacovigilance4:44
- 4.11 AI in the Pharmaceutical Supply Chain4:41
- 4.12 AI for Inspection Readiness: Building an AI Inspection Copilot4:46
- 4.13 The AI-Enabled Life Sciences Organization6:22
- Transition to Module 50:12
- 5.1 Why AI Governance Matters6:05
- 5.2 The AI Lifecycle in Life Sciences5:54
- 5.3 AI Risk Assessment in Life Sciences6:13
- Lesson 5.4 — AI Validation in GxP Environments6:17
- 5.5 AI Monitoring, Model Drift & Continuous Improvement5:45
- 5.6 AI Governance Operating Model6:06
- 5.7 Developing an Enterprise AI Policy & SOP5:39
- 5.8 Global Regulatory Expectations for AI6:14
- 5.9 Implementing AI in Life Sciences: A Practical Roadmap8:24
About this course
This course contains the use of artificial intelligence. AI tools were used to help develop course scripts, slide content, and narration for this course. All content has been reviewed, fact-checked, and validated by the instructor to ensure accuracy and quality. Artificial Intelligence is already reshaping Life Sciences — from drug discovery and manufacturing to deviation investigations, regulatory operations, and inspection readiness. The question for most professionals isn't whether AI will reach their function…
Before you start
- No AI, coding, or data science background required — every concept is explained from first principles.
- Familiarity with a GxP-regulated environment (pharmaceutical, biotech, medical device, or another Life Sciences setting) is helpful but not mandatory.
- A notebook or blank document to keep a running "Capstone Workbook" — this becomes your final project by the end of the course.
Who it’s for
- Quality, Compliance, and Validation professionals who need to evaluate or govern AI tools introduced into GxP workflows.
- Regulatory Affairs, Pharmacovigilance, Manufacturing, and Supply Chain professionals who want to identify realistic AI applications in their own function.
- R&D and Clinical Development professionals exploring how AI is changing drug discovery, preclinical research, and clinical development.
- Life Sciences managers and leaders who need to sponsor, approve, or oversee a first AI pilot responsibly.
- Anyone pursuing the CAIP-LS™ certification who wants a practical, case-study-driven path through it — not just theory.
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