SAN MATEO, Calif., July 9, 2020 /PRNewswire/ — NuMedii, Inc., a data-driven drug discovery company, today announced the availability of the world’s first single-cell sequencing atlas for idiopathic pulmonary fibrosis (IPF) that was the result of a strategic research collaboration including the Yale School of Medicine, Baylor College of Medicine, Brigham and Women’s Hospital, and NuMedii. This comprehensive catalog reveals the complexity and diversity of 35 aberrant cellular populations in IPF. An orphan disease, IPF is a chronic, progressive, and usually fatal interstitial lung disease for which the origin is unknown and current approved therapies have limited effects on survival or quality of life.
Two of the world’s leading experts in interstitial lung disease – Naftali Kaminski, MD, Boehringer-Ingelheim Endowed Professor of Internal Medicine, and Chief of Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine; and Ivan O. Rosas, MD, Lester and Sue Smith Chair in Lung Health, and Professor and Section Chief, Department of Medicine, Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine – led the development of this index with the goal of identifying novel therapeutic targets and biomarkers in IPF. The atlas’s formation was published in the July 8, 2020 issue of the scientific journal, Science Advances, and the data are available at www.IPFCellAtlas.com.
“The opportunity to apply NuMedii’s AI-driven technology to such a rich dataset has fostered a greater understanding of the mechanisms driving lung fibrosis and greatly augmented our IPF therapeutic discovery programs,” said Heather Arnett, Ph.D., Vice President of Research, NuMedii. “We thank the researchers in Ivan and Naftali’s laboratories who brought this immense project to fruition, as well as the patients and their families for their contributions to science. There is no doubt that this work will advance the development of new ways to treat this fatal lung disease.”
NuMedii’s proprietary and dynamic AIDD (Artificial Intelligence for Drug Discovery) technology employs deep learnings of human biology consisting of hundreds of millions of structured molecular, pharmacological, and clinical data points that the Company has curated and harmonized. The Company couples these data with proprietary machine learning and network-based algorithms to discover and advance precise, effective new drug candidates, as well as biomarkers predictive of efficacy for subsets of patients in a broad spectrum of therapeutic areas including orphan diseases like IPF.
Funding for this work was provided by the NIH National Heart, Lung, and Blood Institute and Three Lakes Partners.
About NuMedii, Inc.
NuMedii discovers effective new targets, drugs and biomarkers via its exclusive AIDD (Artificial Intelligence for Drug Discovery) drug discovery technology originally developed at Stanford University. The technology consists of both public and proprietary data and is geared to improve the probability of therapeutic success. NuMedii partners with pharmaceutical companies for development and commercialization. For more information, please visit www.numedii.com.