Novo Nordisk accelerates clinical documentation and drug development with Claude
Novo NordiskClaude Code · Amazon Bedrock · MongoDB AtlasNovo Nordisk, a global pharmaceutical company headquartered in Europe, built NovoScribe, an AI-powered documentation platform using Claude Code, Amazon Bedrock and MongoDB Atlas, to automate clinical study report (CSR) generation. Claude helped cut writing times on CSRs by 90%, reducing time spent producing clinical study documentation from 10+ weeks to 10 minutes, and delivered a 95% reduction in resources needed to create device verification protocols. The platform expanded from clinical trial reports to device protocol documentation and patient materials, and an 11-person development team, including non-technical staff, now prototypes features using Claude Code.
Overview
Novo Nordisk, a global pharmaceutical company headquartered in Europe, built NovoScribe, an AI-powered documentation platform using Claude Code, Amazon Bedrock and MongoDB Atlas, to automate clinical study report (CSR) generation. Claude helped cut writing times on CSRs by 90%, reducing time spent producing clinical study documentation from 10+ weeks to 10 minutes, and delivered a 95% reduction in resources needed to create device verification protocols. The platform expanded from clinical trial reports to device protocol documentation and patient materials, and an 11-person development team, including non-technical staff, now prototypes features using Claude Code.
This entry has 15 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
For pharmaceutical companies, the path from drug discovery to patient access is paved with paperwork. Producing the documentation for a clinical trial consumed so much time and so many resources, even with help from external agencies, that it was slowing down the organization's ability to bring new medicines to market. Staff writers averaged only 2.3 CSRs per year, and the manual process remained prone to errors and subjective interpretation.
The solution
Novo Nordisk used Claude Code to develop NovoScribe, a generative AI documentation platform built on Amazon Bedrock and MongoDB Atlas, with Claude models as the frontier intelligence driving the entire system. The platform combines retrieval-augmented generation (RAG) with domain expert-approved text and case-specific variables to produce accurate, compliant documentation. Initially the team focused on perfecting NovoScribe for clinical study report (CSR) production, then expanded to device protocol documentation and patient materials.
Reported business value
Claude has helped Novo Nordisk cut writing times on clinical study reports (CSRs) by 90%. Time spent producing clinical study documentation was reduced from 10+ weeks to 10 minutes, and device verification protocols saw a 95% reduction in resources needed. For new trials, the team can now produce a complete study booklet and patient guide in under a minute.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other life sciences entries in the register.
Protecting Crops Today to Feed Billions Tomorrow
Syngenta built Gaia, the first crop protection R&D data platform for analytics and innovation, on Databricks to unify siloed data across 70-plus countries. The platform cut data access times from as long as nine months to minutes, reduced time to value by 70%, decreased engineering costs by 50%, and now publishes over 200 data products handling more than 2 million queries per month.
SyngentaDatabricks · Delta Lake · Unity Catalog +3
Novo Nordisk uses machine learning and computer vision to automate pharmaceutical manufacturing quality checks
Novo Nordisk, a Danish pharmaceutical company that supplies nearly 50 percent of the world's insulin, built an automated ML pipeline on AWS using Amazon SageMaker Pipelines to train, deploy, and monitor computer vision models on edge devices. The system automates previously manual tasks including counting drug cartridges in boxes and detecting bacterial anomalies on agar plates, using a robotic arm, camera rig, and edge inference, with results monitored via an Amazon QuickSight dashboard. The solution deploys ML models at scale to different edge devices, automates quality-assurance tasks, improves time to market, and was successfully repurposed from the cartridge-counting use case to the agar-plate anomaly detection use case with minimal changes.
Novartis: Accelerating Drug Development with AI-Powered Clinical Trial Transformation
Novartis partnered with AWS Professional Services and Accenture to modernize their drug development infrastructure and integrate AI across clinical trials, with the goal of reducing trial development cycles by at least six months. The initiative built a GXP-compliant data mesh platform on AWS with Databricks for processing, enabling AI use cases including protocol generation and an intelligent decision system (digital twin). Early results from the patient safety domain showed 72% query speed improvements, 60% storage cost reduction, and 160+ hours of manual work eliminated. The protocol generation use case achieved 83-87% acceleration in producing compliant protocols.
NovartisAmazon Web Services (AWS) · Databricks · Amazon S3 +8
Genome Institute of Singapore accelerates whole genome processing with Databricks
Genome Institute of Singapore (A*STAR), working with Precision Health Research Singapore (PRECISE) on the National Precision Medicine strategy, used the Databricks Data + AI Platform with Delta Lake and Glow to run joint calling of 10,000 whole genomes in under 72 hours, a 15x improvement over their prior approach, to support population-scale precision medicine research.
Was this helpful?
Your feedback helps us improve our use case database