I share regular thoughts on LinkedIn about AI strategy, responsible implementation, and the intersection of domain expertise with AI capability. This page highlights key posts and themes.
Follow me on LinkedIn for more frequent updates.
Recent Posts
AI Regulatory Frameworks: Three Different Approaches
January 2026
Pharmaceutical and healthcare organizations operating across multiple jurisdictions face a complex AI regulatory landscape. The EU's comprehensive prescriptive framework with clear August 2026 deadlines contrasts sharply with the UK's principles-based "pro-innovation" approach and the US's fragmented state-by-state system. Understanding these different philosophies isn't just regulatory compliance - it's strategic planning...
Read full post on LinkedIn →Announcing the AI & ML Reference Guide
December 2025
I've put together an AI & ML reference guide that's helped me consolidate my learning in AI & Digital Transformation. Covers the fundamentals through to current systems (transformers, foundation models, RLHF, agentic AI) with a search function for quick lookup. Deployed it publicly in case it's useful to others...
Read full post on LinkedIn →Ryan v2.0: Transitioning from Pharma to AI Strategy
November 2025
After 12 years in pharmaceutical consulting - navigating HEOR, market access, and value communication across rare diseases, hematology, and oncology - I'm making a deliberate transition to AI strategy. Not abandoning domain expertise, but multiplying its value by adding AI capability. The pharmaceutical industry needs people who understand both the technology and the operational reality...
Read full post on LinkedIn →Key Themes
Responsible AI Governance
AI regulation is evolving rapidly across jurisdictions. I track developments in EU AI Act implementation, UK principles-based approaches, and US state-level legislation. The focus isn't just compliance - it's understanding how different regulatory philosophies shape strategic implementation.
Particularly relevant for pharmaceutical organizations operating across multiple markets, where AI governance intersects with existing healthcare regulation.
Domain Expertise + AI Capability
The most valuable AI consultants aren't necessarily the most technical - they're the ones who can bridge domain knowledge with AI understanding. I explore this through the lens of pharmaceutical industry challenges: evidence requirements, stakeholder complexity, regulatory frameworks.
How do you maintain scientific rigor while adopting AI? How do you communicate AI-driven insights to payers, clinicians, regulators? Where does AI genuinely add value versus where it's just complexity?
Learning in Public
I document my MA journey openly - sharing projects, insights, and lessons learned. This serves multiple purposes: reinforces my own learning, creates portfolio evidence, builds professional network, and potentially helps others on similar paths.
The approach is strategic: each post, each project, each interaction compounds over time into a track record of public work.
Upcoming Topics
I'm currently researching and writing about:
- Stakeholder Analysis with AI: How AI can facilitate more comprehensive perspective-taking in pharmaceutical strategy
- HEOR + AI: Where machine learning intersects with health economics methodologies
- AI Literacy for Families: Making AI accessible and understandable for everyday users
- Evidence Standards for AI Systems: What does "validation" mean in healthcare AI contexts?
Want to discuss these topics?
I'm always open to conversations with people working at the intersection of AI and healthcare, or anyone interested in responsible AI implementation. Get in touch or connect with me on LinkedIn.