Curriculum
- 5 Sections
- 24 Lessons
- 1 Day
Expand all sectionsCollapse all sections
- The New Era of Pharma Communication with AI6
- 1.1Why pharma teams struggle with presentations: overload, compliance pressure, and story flow gaps
- 1.2How AI transforms documentation and reporting workflows
- 1.3Introduction to Generative AI, LLMs, Prompt Engineering in pharma context
- 1.4Overview of ChatGPT, Perplexity, Gamma: Capabilities, strengths, limitations
- 1.5Concepts: Generative AI, Large Language Models (LLMs), Prompt engineering, AI hallucination, compliance risk mitigation
- 1.6Medical-legal content accuracy, visual hierarchy, storytelling for regulators
- Structuring Plant-Level Presentations Using ChatGPT & Perplexity7
- 2.1ChatGPT for structuring slides: deviation reports, validation summaries, training decks
- 2.2Prompt writing for targeted outputs: audit responses, SOP breakdowns, batch summary decks
- 2.3Using Perplexity for regulatory trends, CAPA insights, and technical updates
- 2.4Customizing tone for regulators, auditors, and internal teams
- 2.5Real-Life Example 1 : Batch deviation explanation for USFDA inspection
- 2.6Real-Life Example 2 : Internal deck for process validation summary
- 2.7Real-Life Example 3 : Product transfer pitch for CRO or CDMO
- Smart Design & Delivery with Gamma AI6
- 3.1Using Gamma for slide layout, visuals, and pharma-compliant formatting
- 3.2Modes: Generate, Paste, Import – choosing the right mode
- 3.3Embedding MOA videos, visuals (e.g., chromatograms, audit dashboards)
- 3.4Polishing: speaker notes, CTA, brand-consistent design
- 3.5Modular slide design, collapsible data cards, CTA (Call-to-Action), medical graphics, MLR alignment
- 3.6Gamma hacks: reusable slide decks, visual storytelling for process deviations
- Hands-On Simulation: AI Tools in Action1
- Best Practices, Pitfalls & Strategic Takeaways4
- 5.1When AI can help vs when it can’t (compliance limits, human review needs)
- 5.2Creating reusable slide templates (e.g., for SOP updates, training decks, validation reports)
- 5.3Common pitfalls in AI outputs: hallucination, data inaccuracy, misalignment with audience tone
- 5.4Pro-tips to maintain pharma-grade presentation quality