HiberCell and the Strasbourg Institute of Precision Medicine Release Data and Machine Learning Approach on Causal Biology of Severe COVID-19
Artificial intelligence, machine learning (AI / ML) approach, developed in cancer and cardiovascular disease, identifies gene expression network in acute respiratory distress syndrome (ARDS) in a subset of COVID patients -19 published in Science Translational Medicine
Posted: October 26, 2021 at 6:19 PM EDT|Update: 7 hours ago
NEW YORK, October 26, 2021 / PRNewswire / – HiberCell, a clinical-stage biotechnology company that develops therapies to treat cancer relapses and metastases, and its academic collaborators in Strasbourg (France) published data from a study focused on defining the biological networks believed to be responsible for severe and often fatal acute respiratory distress syndrome (ARDS) in a cohort of younger COVID-19 patients. This study, titled “Identification of conductive genes for severe forms of COVID-19 in a cohort of deeply phenotyped younger patients,” appears online in Scientific translational medicine.
Focused on the underlying biology of COVID-19 in the absence of confounding factors that include age and underlying health issues, the study investigated a subset of COVID-19 patients who did not present no underlying medical condition and were under the age of 50. The aim of the study was to define the biological networks responsible for severe and often fatal ARDS in COVID-19 patients. Mapping and categorization of putative interactions between a network of 600 genes in these patients showed that abnormal ADAM9 expression was a key causative factor for COVID-induced ARDS.
“The study further supports the utility of our biologically validated AI / ML platform that focuses on advancing our portfolio of cancer therapies,” said study co-principal investigator , Tom chittenden, PhD, DPhil, PStat, CTO of HiberCell and co-founder of the HiberCell AI initiative. “This study underscores the agnostic potential of our causal biology, AI / ML approach that is well positioned to provide disease information even with limited patient cohorts.”
“This is an important example of the potential impact of machine learning on the life sciences,” commented Daniel Lidar, PhD, Viterbi professor of engineering at the University of Southern California (USC) and a HiberCell employee. “Using several independent ML methods, including a quantum variant, this study builds on our work in breast cancer, further validating the utility of unconventional ‘Ising-like’ ML in quantum computing. It is based on results Posted in April in which we identified replicable signals in high dimensional data in small cohorts. “
“This work provides a deeper understanding of COVID-19 in a subset of younger, healthier patients,” said Co-Principal Investigator Seiamak Bahram, MD, PhD, President of Immunology at Faculty of Medicine of the University of Strasbourg, INSERM unit 1109 and Strasbourg University Hospitals. “We further supported these results in additional cohorts, strengthening the identification of these biological networks. We are actively working to further elucidate the importance of ADAM9 in virus uptake and replication in human lung cells. These data may provide an alternative therapeutic approach for COVID -19 or in broader terms, ARDS in general. “
“Recognizing the need for further research, these data highlight the potential of our patient-centric AI / ML initiative at HiberCell, which is driving the validation of pharmacodynamic biomarkers in our leading pipeline of stress modulators in cancer. “, said Alain Rigby, President and CEO of HiberCell.
About HiberCell
HiberCell is a clinical-stage biotechnology company dedicated to advancing new therapies designed to overcome fundamental molecular barriers that prevent patients from living cancer-free longer. HiberCell’s approach uses AI / ML to integrate the multi-omic and phenotypic profiles of tumors to generate in-depth information that links this data to clinical outcomes. Based on this data, HiberCell identifies and validates the causal features of cancer that can be targeted with their new therapies in order to tackle the most common causes of cancer mortality: resistance, relapse and metastasis. To this end, HiberCell is developing therapies designed to resolve “stress” through mechanisms that involve stimulating innate and adaptive immunity to reprogram an immunosuppressive tumor immune microenvironment or to modulate the adaptive stress-induced response that is essential to survival of cancer cells.
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SOURCE HiberCell
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