AI in Pharma & Life Sciences
A ~36-minute playbook for biopharma execs, R&D heads, clinical ops + regulatory affairs leaders. 5 plays within GxP guardrails. Grounded in FDA GMLP + EMA AI reflection + ICH + 21 CFR Part 11.
8
Chapters
~36 min
Duration
Advanced
Level
No
Certification
Who this is for
For biopharma executives, heads of R&D, clinical operations leaders, regulatory affairs heads, and chief digital officers in life sciences.
How this course works
- 8 audio-narrated slide chapters · ~36 min of focused content
- Capstone with interactive Markdown builder you take to your team
- Trust trip-wires on every play — what not to cross
- Free verifiable certificate on completion
What you'll walk out with
Specific outcomes from this course — no fluff.
- AI accelerates discovery and operations within GxP guardrails — patient safety + data integrity + regulatory accountability are non-negotiable
- 5 plays — discovery · trial operations · regulatory submission · pharmacovigilance + RWE · commercial + medical affairs
- Honestly read the AI discovery disappointment pattern — AI accelerates early stages, not guarantees clinical success
- Keep investigator + medical monitor accountable under GCP — AI assists, humans decide
- Apply citation discipline to AI-drafted regulatory content — every citation verified (Mata cross-domain), Part 11 audit trail
- Preserve medical review on PV — qualified safety physician's causality assessment cannot be replaced by AI
- Run AI promotional content through MLR — off-label suggestions and unsourced claims are enforcement targets
- Validate AI in GxP contexts — 4 validation components and audit-ready documentation before deployment
Course content
8 chapters · ~36 min
Welcome
A 1-minute orientation — what the course covers, how to navigate, and what you walk out with. No audio on this screen.
The pharma + life sciences landscape
AI accelerates within GxP guardrails · patient safety/data integrity/regulatory accountability non-negotiable · 5 plays · regulatory frame (FDA/EMA/ICH/GxP).
Drug discovery
4 areas (target ID · lead gen · ADMET · protein engineering) · the disappointment pattern · validation discipline (wet-lab confirms, diverse held-out sets).
Clinical trial operations
4 use cases (patient ID · site selection · protocol optimisation · data quality) · the GCP constraint · the consent question.
Regulatory submission preparation
3 use cases · the citation discipline (Mata cross-domain) · 21 CFR Part 11 audit trail.
Pharmacovigilance + real-world evidence
3 PV use cases · medical review preserved · RWE with pre-specified analysis plan.
Commercial + medical affairs
3 use cases · promotional compliance line (OPDP + EMA) · disclosure question (EU AI Act Art 50).
Validation, audit + GxP fit
GxP applicability · 4 validation components · audit-readiness discipline · quality unit involvement.
Making it stick: your pharma AI roadmap
18-month rollout · 4 trust trip-wires · interactive Markdown builder for your head of R&D or chief digital officer.
Want this delivered inside your organisation?
The course is the starting point. The same content powers a 4-week pilot, an org-wide rollout, or a continuous build engagement — set up on your data, with your team, by Gennoor Tech.