Novo Nordisk cuts clinical study documentation from 10+ weeks to 10 minutes
By Novo Nordisk (Waheed Jowiya, Louise Lind Skov)Built and shared by Novo Nordisk (Waheed Jowiya, Louise Lind Skov), not by me. Summarised from the public sources below. Check them before you rely on a number.
- Who
- Novo Nordisk (Waheed Jowiya, Louise Lind Skov)
- Category
- Research & science
- Source
- Web
- Dates
- Published Sept 2026 · Found 17 Oct 2026
Novo Nordisk built NovoScribe, an AI documentation platform that writes regulatory-grade clinical study reports and other trial documents. According to Anthropic's case study, producing clinical study documentation went from more than ten weeks to ten minutes.
What they built
NovoScribe combines retrieval-augmented generation with expert-approved text blocks and case-specific variables to produce clinical study reports (up to 300 pages), device verification protocols, study booklets and patient guides. It runs on Claude via Amazon Bedrock with MongoDB Atlas, and a development team of 11 used Claude Code to build it. Non-technical staff also used Claude Code to build prototypes in natural language.
The result
Self-reported via vendor: clinical study documentation reduced from 10+ weeks to 10 minutes, CSR writing time cut by 90%, and 95% fewer resources needed for device verification protocols. A complete study booklet and patient guide takes under a minute.
Sources
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By Kristina Lång and colleagues (Lund University, Skåne University Hospital)
Lund University ran a randomised trial with about 106,000 women in the Swedish screening programme, comparing AI-supported mammography with standard double reading. AI found 29% more cancers, cut radiologists' reading workload by 44%, and a 2026 Lancet follow-up showed higher sensitivity with no rise in interval cancers.
GPT-5 supplied the key step in a proof in quantum complexity theory
By Scott Aaronson (UT Austin)
Computer scientist Scott Aaronson says that a central technical step in the proof in his new paper on QMA amplification came from GPT-5 Thinking. It is the first time this has happened in his career.
DTU researcher co-designs AI proteins that protect mice from lethal snake venom
By Timothy Patrick Jenkins (DTU Bioengineering) and David Baker (University of Washington)
Timothy Patrick Jenkins of DTU and David Baker's lab at the University of Washington used deep learning to design new proteins that bind and neutralise cobra toxins. The designed proteins protected mice from lethal doses, which could lead to cheaper and safer antivenoms.
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