NuMedii Announces Research Collaboration with Yale, Brigham and Women's Hospital

NuMedii announced the formation of a strategic research collaboration with Yale School of Medicine and Brigham and Women's Hospital with the goal of utilizing single-cell sequencing to identify novel precision therapies and biomarkers in idiopathic pulmonary fibrosis (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.

Under the collaboration, NuMedii will work with 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, Associate Physician, Brigham and Women's Hospital and Associate Professor, Harvard Medical School – and their respective laboratories to identify novel therapeutic targets and biomarkers in IPF. The collaboration brings together a rich single-cell RNA sequencing data repository from patients with IPF together with NuMedii's Artificial Intelligence for Drug Discovery (AIDD) technology to discover new therapeutics and biomarkers for IPF.

"The combination of NuMedii's AIDD technology with this rich data repository will provide unparalleled discovery capabilities to uncover novel mechanisms, cell types, targets and biomarkers that we believe will be instrumental in identifying and developing precision therapies for orphan diseases like IPF," said Gini Deshpande, Ph.D., chief executive officer, NuMedii. "We are excited to partner with two of the world's leading experts and their research teams at these world-class institutions to help further advance our work in this fatal lung disease for which there exists a significant unmet medical need."

NuMedii's AIDD 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.

"Our teams have been at the forefront of analyzing human IPF samples using high throughput technologies for many years," said Dr. Kaminski, who also co-Directs P2MED, Yale's Center for Pulmonary Precision Medicine. "The data we will derive by molecularly profiling thousands of single cells in every patient's sample will allow us to understand disease at an unprecedented resolution and should allow us to identify new cell types and biological mechanisms involved in IPF."

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