PRINCETON, NJ, Nov. 03, 2022 (GLOBE NEWSWIRE) — PharmaNest, an emerging leader in quantitative digital pathology and artificial intelligence, today announces that it will present, alongside collaborators, three abstracts at the This year’s Liver Meeting | AASLD Conference, November 4-8, 2022 in Washington, D.C. Abstracts highlight the utility and performance of FibroNest, the first quantitative multi-vendor digital pathology image analysis and translational platform for the assessment of severity and progression of fibrosis and disease activity in NASH and cirrhosis, and other fibrotic conditions.
“Automated quantification of the fibrosis severity phenotype from the same slides examined by pathologists offers a robust and scalable method for generating continuous scores across the continuum of NAFLD, NASH and cirrhosis. At high detection thresholds, the FibroNest method can measure fainting changes and specific disease regression traits induced by drug candidates,” said Mathieu Petitjean, CEO and Founder of PharmaNest.
The first two abstracts are a retrospective analysis of liver biopsies from the Phase 2 LiFT trial of LPCN1144 (NCT04134091). They show (i) how the FibroNest Continuous Fibrosis Score detects drug effects that are missed by conventional histological methods and (ii) that the quantification of the anti-steatosis effect of LPCN1144 is similar whether one uses MRI-PDFF, FibroNest steatosis scores or histological steatosis grades (in partnership with Lipocin, Inc.).
A third abstract describes the performance of the FibroNest fibrosis score along the cirrhosis spectrum (N=100) and shows how the phenotypic nature of this score reduces the coefficient of intra-(“geographical”) variability of liver biopsies compared to previously reported values of 47% down to 16% on average (in partnership with Mount Sinai University).
Specific details of these abstracts are available on the PharmaNest website at fibronest.com/science.
As a multi-vendor platform, FibroNest is compatible with all kinds of digital image formats, including conventional digital pathology stained slides (Picro Sirius Red, Trichrome or Antibody stains for fibrosis) acquired by CT scanners. FDA-approved digital pathology and other digital microscopes. This is a research-only tool at this time.
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Figure 1: FibroNest Ai scores
FibroNest fibrosis severity score in liver biopsies from NASH patients
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