According to Granzow, Philips' approach to computational pathology will be that of an "open ecosystem" in which it will seek to collaborate with multiple partners, with complementary strengths.

He cites the company's collaboration with Mount Sinai Health System — intended to create a digital image repository comprising patient tissue samples and data analytics — as an example of this. The repository, which was announced in 2015, will be used to uncover new tissue-based tests and advance clinical research.


In a partnership announced earlier this month, Philips and LabPON, a pathology lab in the Netherlands, will utilize the IntelliSite Pathology Solution to aggregate sets of annotated pathology images and big data to develop image analytics algorithms for computational pathology and pathology education.

Per the arrangement, LabPON will contribute its repository of approximately 300,000 whole-slide images that it generates each year to the database. These images comprise a broad range of tissue and disease types as well as other diagnostic information that’s needed for deep learning.

In June 2016, Philips CEO Frans van Houten told Reuters the company's digital pathology business has been "doubling every year."

"We're acquiring a company that has deep clinical knowledge and technology to analyze cancerous cells," said Van Houten, adding that the partnership "will widen the capabilities of our pathology business and make it even more attractive for pathologists to adopt."

It's costly to ship conventional glass slides for a second opinion and the time that's required accounts for 41 percent of delays in cancer diagnosis, according to the National Patient Safety Agency. With a digital pathology workflow, it only takes 60 seconds for a glass slide to be scanned and ready for viewing at 40x magnification.

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