Lunit and Discovery Life Sciences Partner on AI Tissue Analysis
Lunit and Discovery Life Sciences announced in a press release a collaboration that will bring the Lunit SCOPE pathology platform into Discovery's biomarker and tissue analysis workflows.
The companies will tailor the AI pathology tools to individual biopharma research programs. The service will combine Lunit's image analysis software with Discovery's biospecimen network and laboratory capabilities, covering specimen sourcing, molecular pathology and quantitative analysis.
Discovery says it has provided biomarker services for more than 2,000 clinical trial programs and currently supports over 350 active programs. The collaboration will give pharmaceutical and biotechnology companies access to standardized tissue data for biomarker research, translational studies and drug development.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Life AI Weekly, Enterprise AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from Life Sciences
Oct 12 Flo Health Partners With Google Health on Wearables and Women's Health AI Oct 12 Immorta Bio completes preclinical studies of AI designed senolytic peptide Oct 12 POMDOCTOR Outlines Predictive Healthcare Strategy Oct 12 Emplify Health adds Pearl Health AI tools for Medicare care Oct 12 Sopris Capital Acquires Blackford Analysis from BayerMore from Enterprise
Oct 12 EY and Watershed Partner on Sustainability Reporting Oct 12 Fedstack Becomes an OpenAI Select Partner Oct 12 Saksoft Appoints Gurmeet Chahal as CEO Oct 12 Flo Health Partners With Google Health on Wearables and Women's Health AI Oct 12 insidepacket Launches AI Access Platform for GPU Cloud ConnectivityLife AI Weekly
Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Linearis Joins Two Canadian AI Health Data Projects
Danaher Plans AI Autonomous Lab for Antibody Research
Domino Data Lab and EPAM Partner on Validated AI for Life Sciences
Cellular Intelligence Adds Yann LeCun and Three Scientists to Advisory Board
MediSights Reports Study Using AI Agents for Myeloma Market Research
Daily AI Brief: the AI news that matters, in your inbox.