PictorLabs, a digital pathology company developing an AI-powered virtual staining platform, formally announced its launch at the start of December.
PictorLabs, a Los Angeles-based digital pathology company developing an artificial intelligence (AI)-powered virtual staining platform, formally announced its launch at the start of December 2022. The company launched with more than $18.8 million in funding since its founding in 2019.
According to a Dec. 1, 2022 press release, the company’s technology is designed to apply deep learning algorithms to efficiently and accurately stain tissues in silico, producing near-instantaneous virtual stains. From a single unstained tissue sample, PictorLabs’ proprietary platform can produce an unlimited number of virtual stains that are indistinguishable from analogous chemical stains. This eliminates the need for chemical staining, reduces the time to results, and allows for repeated biomarker testing without the need for multiple tissue samples.
PictorLabs has also demonstrated successful virtual staining for several well-validated disease biomarkers, according to the press release. The company is now pursuing additional opportunities in disease areas with high unmet need. The company plans to use its latest round of funding to expand its biomarker portfolio, develop novel products, grow the company’s talent base, and build out its corporate infrastructure.
“PictorLabs’ platform overcomes inherent issues in histopathology through the application of AI-powered algorithms that produce virtual stains which are indistinguishable from their chemistry-based counterparts,” said Yair Rivenson, CEO and chief technology officer, PictorLabs, in the press release. “By virtually staining tissue images in the digital realm, our approach simplifies and accelerates workflows, speeding up drug discovery and diagnostic decision-making with the goal of ultimately improving patient outcomes. With the support of our experienced investors, we’re now well placed to systematically expand our platform.”
Source: PictorLabs
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