The aim is to analyze the proteomic plasma profile of SARS-Cov-2 patients with the aid of a machine learning approach to derive a novel diagnostic test for the prediction of disease severity in patients suffering from SARS-Cov-2. The development of such a diagnostic test is of high potential impact as it will allow health care providers to stratify patients and plan for the availability and allocation of medical and infrastructural resources required for adequate clinical care.
Currently, there is no test that can predict COVID-19 disease severity. The development of this diagnostic test will use a COVID-19 patient’s immune-profile and apply machine learning to predict COVID-19 disease severity and can also be used as a companion diagnostic tool. This test will allow doctors to prioritize high-risk patients and make informed decisions on treatment choice, use of scarce therapeutic resources, and predict whether a COVID-19 patient will need an ICU bed and ventilator.
At a population scale, when used with antibody-based COVID-19 tests, our test will provide actionable information to local and federal governments and healthcare organizations to drive resource allocation and deployment. Furthermore, while the elderly population and subjects with pre-existing comorbidities (e.g. hypertension and T2D) are at greatest risk, severe cases have also been registered in the younger population with no clear explanation regarding their susceptibility.
If you are interested in partnering with us for joint projects, please contact Asli Gozoren at Asli@edificehealth.com
About EDIFICE Health
EDIFICE Health is a spin-out company from the ‘Stanford 1,000 Immunomes Project’ which received $30M in funding from the NIH/NIHA during the course of the 10-year research. The project followed 1,000 people up to 10 years to discover the association between immune health and disease. The resulting ‘Inflammatory Age’ score is a measure of the degree of a weakened immunity, which can predict multiple chronic diseases, and in this current pandemic, reduce global disease burden.