AI Director · Pharmaceuticals
AI for Pharma Directors: Master the Full Playbook
You already know clinical trials, market access and regulatory affairs from the inside. Here you'll connect that knowledge to AI: how drug discovery algorithms work, what the FDA and EMA expect from AI-driven submissions, how companies like Roche or Novartis structure their AI governance, and where the real bottlenecks sit between R&D, manufacturing and compliance. Every lesson ties back to your sector's players, figures and rules, not generic AI theory.
Alongside that, you get the general AI track to build a solid base, interactive tools to practice on real scenarios, a playbook you can apply directly to your team's projects, and an assessment built specifically for Pharma AI leadership. You'll finish knowing where you stand and what to do next.
27 lessons · ~5 h · resumes where you left off
Your program
A focused program built on your vertical's content: the sector first, then your discipline applied to it.
The generalist AI track
The full craft of the discipline, beyond your sector.
More resources
Frequently asked questions
Who is the AI for Pharma Directors track designed for?
It targets directors and senior managers already working inside pharma: clinical development, market access, regulatory affairs, manufacturing or medical. The content assumes you know how a trial or a submission works and focuses on connecting that knowledge to AI, rather than teaching the pharma basics again.
Do I need a technical background to follow it?
No. The AI for Pharma Directors track is built for decision-makers, not for people who will write the code. You learn how drug discovery algorithms and machine learning models behave, what questions to ask your data teams, and where the risks sit, without needing to program anything yourself.
What's the difference between the sector track and the general AI track?
The general AI track builds the base: how models work, what they can and cannot do, how to frame a use case. The pharma track applies that base to your reality, with the players, figures and regulatory constraints of the industry. Most people run both, starting with the general one if AI is new to them.
Is the training free, and what does creating an account change?
Reading is free and open, with no paywall on the lessons. An account only saves your progress so you can pick up where you left off and keep your assessment results. There is no diploma or state-recognised certification attached to it.
What does the training say about FDA and EMA expectations on AI?
It covers what regulators look for in submissions involving AI-driven methods: how the model was built, how data quality and traceability are documented, and how decisions remain explainable. The point is to help you anticipate the questions an FDA or EMA reviewer will raise before your team commits to an approach.
What can I actually use with my team after finishing?
Two things: the playbook, which you apply directly to a project in progress, and the interactive tools, which let you rehearse real scenarios before facing them internally. The assessment built for pharma AI leadership tells you where you stand and what to tackle next.