CytoReason Collaborates with Sanofi, Using its AI Technology to Gain Better Understanding of Disease Mechanisms

TEL AVIV, Israel, June 17, 2021 - CytoReason, an AI company developing a computational disease model of the human body for clinical drug development, today announced the initiation of a project with French global biopharmaceutical company Sanofi, which will utilize its cell-centered models and deconvolution techniques to suggest mechanistic insights for each asthma endotype.

The focus of this project is to gain clarity on the heterogeneity of asthma patients, with the goal of identifying stable and reproducible asthma endotypes, as well as associated diagnostic features, using minimal invasive procedures. For this project, CytoReason's AI platform will use one of the most comprehensive datasets in moderate to severe asthma, covering samples from both adults and children.

Asthma is a complex disease with genetic and environmental factors that lead to airway inflammation, resulting in excess mucus in a patient's airway, which causes coughing, wheezing and shortness of breath. It can appear in several degrees of severity, ranging from mild to severe, and can be classified as either Type 2 asthma, which includes allergic and eosinophilic asthma, or non-Type 2 asthma, which is associated with low eosinophil counts often presented with altered innate immune response and activation of Th17 cells. Though symptoms of the disease can often be controlled, asthma, which is a key area of research for Sanofi, cannot be completely cured. One of the main challenges in the disease is classification of patients to find the most suitable treatment.

"We are very excited to be launching our collaboration with Sanofi," said David Harel, CEO and Co-founder of CytoReason. "It represents a chance to make a real difference in driving better understanding of the heterogeneous and complex nature of asthma and its diversified manifestation in patients. Additionally, the work we do with Sanofi could enhance future research in this field and could inform precision medicine strategies for improved patient benefit."