Shifting Into High Gear: Lunit, Maker of FDA-Cleared AI for Cancer Analysis, Goes Public in Seoul

The long-time NVIDIA Inception member uses AI to analyze chest X-rays, mammograms and more.
by Renee Yao
Lunit employees drawing representation of their AI model

South Korean startup Lunit, developer of two FDA-cleared AI models for healthcare, went public this week on the country’s Kosdaq stock market.

The move marks the maturity of the Seoul-based company — which was founded in 2013 and has for years been part of the NVIDIA Inception program that nurtures cutting-edge startups.

Lunit’s AI software for chest X-rays and mammograms are used in 600 healthcare sites across 40 countries. In its home market alone, around 4 million chest X-rays a year are analyzed by Lunit AI models.

Lunit has partnered with GE Healthcare, Fujifilm, Philips and Guardant Health to deploy its AI products. Last year, it achieved FDA clearance for two AI tools: one that analyzes mammograms for signs of breast cancer, and another that triages critical findings in chest X-rays. It’s also received the CE mark in Europe for these, as well as a third model that analyzes tumors in cancer tissue samples.

“By going public, which is just one step in our long journey, I strongly believe that we will succeed and accomplish our mission to conquer cancer through AI,” said Brandon Suh, CEO of Lunit.

Lunit raised $60 million in venture capital funding late last year, and its current market cap is some $320 million, based on its latest closing price. Following its recent regulatory approvals, the startup is expanding its presence in the U.S. and the European Union. It’s also developing additional AI models for 3D mammography.

Brandon Suh, CEO of Lunit, beats a drum in celebration of the company’s IPO at the Korean Exchange.

Forging Partnerships to Deploy AI for Radiology, Oncology

Lunit has four AI products to help radiologists and pathologists detect cancer and deliver care:

  • Lunit INSIGHT CXR: Trained on a dataset of 3.5 million cases, this tool detects 10 of the most common findings in chest X-rays with 97-99% accuracy.
  • Lunit INSIGHT MMG: This product reduces the chance that physicians overlook breast cancer in the screening mammography by 50%.
  • Lunit SCOPE IO: Demonstrating 94% accuracy, this AI helps identify 50% more patients eligible for immunotherapy by analyzing tissue slide images of more than 15 types of cancer, including lung, breast and colorectal cancer.
  • Lunit SCOPE PD-L1: Trained on more than 1 million annotated cell images, the tool helps accurately quantify expression levels of PD-L1, a protein that influences immune response.

GE Healthcare made eight AI algorithms from INSIGHT CXR available through its Thoracic Care Suite to flag abnormalities in lung X-rays, including pneumonia, tuberculosis and lung nodules.

Fujifilm incorporated INSIGHT CXR into its AI-powered product to analyze chest X-rays. Lunit AI connects to Fujufilm’s X-ray devices and PACS imaging system, and is already used in more than 130 sites across Japan to detect chest nodules, collapsed lung, and fluid or other foreign substances in the lungs.

Philips, too, is adopting INSIGHT CXR, making the software accessible to users of its diagnostic X-ray solutions. And Guardant Health, a liquid biopsy company, made a $26 million strategic investment in Lunit to support the company’s innovation in precision oncology through the Lunit SCOPE tissue analysis products.

Accelerating Insights With NVIDIA AI

Lunit develops its AI models using various NVIDIA Tensor Core GPUs, including NVIDIA A100 GPUs, in the cloud. Its customers can deploy Lunit’s AI with an NVIDIA GPU-powered server on premises or in the cloud — or within a medical imaging device using the NVIDIA Jetson edge AI platform.

The company also uses NVIDIA TensorRT software to optimize its trained AI models for real-world deployment.

“The goal here is to optimize our AI in actual user settings — for the specific NVIDIA GPUs that operate the AI,” said Donggeun Yoo, chief of research at Lunit.

Over the years, Lunit has presented its work at NVIDIA GTC and as an NVIDIA Inception member at the prestigious RSNA conference for radiology.

“It was very helpful for us to build credibility as a startup,” said Yoo. “I believe joining Inception helped trigger the bigger acknowledgements that followed from the healthcare industry.”

Join the NVIDIA Inception community of over 10,000 technology startups, and register for NVIDIA GTC, running online Sept. 19-22, to attend the session “Accelerate Patient-Centric Innovation with Makers and Breakers in Healthcare Life Science.”

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