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Notes on Hybrid AI for Pharma
Architecture, cost and strategy for private and managed AI in R&D, clinical, safety and regulatory work.
Latest Articles
Hybrid AI in pharma: what goes private, what goes managed
A task-by-task guide to routing trial, safety, compound and literature work between private models in your cloud and managed models such as Claude or GPT.
Why per-token AI pricing breaks at pharmacovigilance volume
Safety case volumes grow with every product on the market. Here is where the break-even point sits, and why owned capacity wins for high-volume work.
When every lab runs the same AI, know-how stops being an edge
If every company uses the same assistant, the SOPs and judgement that set a strong R&D organisation apart start to disappear.
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