Gain the knowledge, tools and confidence to apply AI effectively in your role without compromising GxP, compliance or data integrity. Learn from Martin Lush, one of the most respected voices on AI in pharma.
AI is already transforming pharmaceutical operations. The opportunity is significant, but so are the risks. This practical two-day course gives you the tools to identify where AI can improve your work, evaluate its outputs, manage compliance risks and make informed decisions about responsible adoption. Learn from real world experience across 25+ pharmaceutical companies and leave with a personalised 30/60/90-day AI action plan you can put into practice.
of in-depth practical training
by Martin Lush, 40+ years in senior pharma
of previous attendees would recommended
personal action plan
Stay in compliance with your legal duties in the era of AI
Build the judgement to certify with confidence in an AI-enabled world
Scale AI's value without scaling the gaps in quality oversight
Audit AI with the same rigour you bring to everything else
Practical AI applications that improve productivity without increasing risk
Advise your clients on AI with credibility and practical depth
Understand how the industry is adopting AI and what good looks like
Deploy AI that meets GxP expectations
Every module is built on real scenarios from 25+ companies already using AI.
Understand AI, machine learning & generative AI in a pharmaceutical context. Build governance policies covering accountability, permitted use & human-in-the-loop oversight
Evaluate AI-influenced evidence in batch records, validate AI tools for GxP use and set clear boundaries for human oversight in release decisions
Use AI to simplify SOPs, predict deviations, improve CAPA effectiveness and prioritise change controls, all demonstrated with pharmaceutical examples
Audit AI systems for GMP compliance and prepare for inspector questions around Annex 11, GAMP 5 and the EU AI Act.
Identify low-risk quick wins, upskill teams, evaluate AI vendors and build a credible business case for further investment.
Master prompt techniques for faster, more reliable results from AI tools while sharpening critical thinking and written communication.
With over 40 years in senior leadership roles across the pharmaceutical industry, Martin brings a depth of experience that is unmatched. As former global VP of Pharma, Biotech and Medical Devices at NSF, he has spent decades working in quality, compliance and operational excellence. Today he works with pharmaceutical organisations worldwide, helping leadership teams adopt AI safely, compliantly and with measurable results. His courses have been attended by current and former regulatory inspectors, a testament to the credibility and relevance of what he teaches.
AI in pharma refers to the use of machine learning, generative AI and other intelligent systems to support pharmaceutical operations. The goal is to improve efficiency and reduce risk while maintaining full GMP compliance and data integrity.
Key applications include
This AI in pharma training course covers how to evaluate, adopt and govern these applications responsibly in a GxP environment.
This AI training course is designed for pharmaceutical professionals who want to understand how AI can enhance their role and their organisation's performance.
This course is ideal for
No prior technical AI experience is required.
The course covers six practical areas designed to give you both strategic understanding and hands-on application.
What you will learn
No prior technical AI experience is required.
When implemented with appropriate validation and human oversight, AI reduces risk while improving quality outcomes across pharmaceutical operations.
AI can support pharmaceutical quality in the following areas
This course demonstrates each application with pharmaceutical case studies and practical methods you can apply in your own environment.
This AI regulatory compliance training covers EU and US expectations for AI in pharmaceutical manufacturing and quality.
Practical guidance includes
Current and former regulatory inspectors have attended this course.
No. This practical AI in pharma course is designed for pharmaceutical professionals, not data scientists. Every concept is explained in plain language and every exercise is rooted in pharmaceutical operations you will recognise from your own work.
Whether you are new to AI or already experimenting with it, the course meets you where you are.
Yes. This AI in pharma training programme can be delivered on-site at your premises or as a virtual tutor-led session.
In-house training includes
Contact us to discuss your requirements.
A Qualified Person should understand three things before using AI in batch release.
The three essentials
This AI training for Qualified Persons covers all three areas with practical exercises, so you leave with a clear method for evaluating AI-influenced evidence and maintaining defensible human oversight of release decisions.
Start with an AI governance framework that defines accountability, permitted use cases, validation requirements and human oversight responsibilities.
Then focus on three priorities
This course provides implementation steps drawn from experience across 25+ pharmaceutical companies.
AI identifies patterns in deviation data that human review often misses, enabling earlier intervention and more targeted preventive action.
How AI supports deviation management
With appropriate validation and human oversight, AI strengthens rather than weakens GMP compliance.
The course demonstrates this with pharmaceutical case studies and a practical method you can apply in your own environment.
AI validation for GxP use follows risk-based principles similar to those applied to other computerised systems, but with additional considerations for how AI models learn, change and produce outputs.
Key validation steps
The course covers AI validation approaches aligned with GAMP 5 and Annex 11 principles, including what evidence regulators will expect and how to document your rationale proportionately.
