A nonprofit built a medical knowledge LLM platform on NVIDIA NIM for 17,000+ practitioners in 19 countries.
Clinicians in low- and middle-income countries lacked current medical knowledge because of poor connectivity, local content and language gaps. Techies Without Borders built CMES-AI with NVIDIA T4 GPUs, Jetson Nano for clinics and NIM microservices. The page reports query time cut from 5 minutes to 2 seconds, 17,000+ practitioners supported, and care improved for 20 million people annually.
NVIDIA is a computing and AI company whose BioNeMo and Clara platforms provide models and accelerated tools for drug discovery, genomics and medical imaging.
This sits in the Ship stage of the AI use-case lifecycle: Named examples from the vendors pharma teams use to get an AI system live inside a real, regulated production workflow — validation, CRM, safety and clinical systems of record.
Published by NVIDIA on its own site — read the original case study on nvidia.com ↗
Related use cases
- 01Amgen trained antibody language models on NVIDIA BioNeMo and DGX Cloud, reaching three-month goals in four weeks.
- 02Biofy cut infectious disease diagnosis from five days to four hours with an NVIDIA-accelerated genome pipeline.
- 03Astellas trained its own antibody language models on NVIDIA BioNeMo to predict antibody properties before measurement.
- 04Deloitte built its Quartz Atlas AI drug discovery platform on NVIDIA BioNeMo, DGX Cloud and NIM microservices.
- 05Transforming Content Operations for 2x Faster Time to Market
- 06Astellas: Breaking Access Barriers with Veeva Compliant Chat