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Proscia is working with Samsung Medical Center on a big development

The health IT startup is developing an algorithm to predict the spread of lung cancer.

Proscia's team. (Courtesy photo)

Proscia is developing an algorithm that would give doctors a new way to predict (and prevent) the spread of cancer.
The startup launched by Johns Hopkins grads has a new partnership with Samsung Medical Center. The aim is to develop an algorithm that could predict the likelihood of metastasis, which is when cancer cells break away from a lung tumor and grow in the lymph nodes, said Proscia CEO David West.
According to a statement from Dr. Insuk Sohn, chief senior researcher at Samsung Medical Center, there is currently no way to accurately determine whether metastasis is likely. With such a method, they could have a better sense for which patients would benefit the most from undergoing a procedure that removes cancer tissue.
West said specialists at the South Korean-based research institute will provide datasets and other clinical data, and Proscia’s team will look to train its system to the point where it can be used as a diagnostic test. The two teams hope to develop a pipeline with lung cancer, then continue working together to address other types of cancers, West said. Proscia has also worked on lymph node metastasis of breast cancer.
“There is a predictive aspect of this,” West said. “The algorithm is designed to look at the image and look at pattern and make a prediction about the cancer spreading.”
Work on the algorithm is part of Proscia’s wider effort to develop a platform that brings digital tools to the work of diagnosing cancer, which is known as pathology. It’s a big leap for a field that relies on doctors analyzing slides through microscopes.
The Spark-based company closed a $1 million seed round in June 2016, and quickly expanded its dev team. In October, the company released a trio of image analysis tools. Proscia recently earned a nod on our realLIST of local startups to watch.
“We very much believe that the use of not just computer based image analysis tools but the really intelligent machine learning-based, cancer-specific diagnostics is the future of digital pathology,” West said.

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