What You Should Know:
– OnScale announced the kickoff of the Project BreatheEasy by leveraging massively scalable cloud bioengineering simulation and AI to create “Digital Twins” of the lungs of COVID-19 patients.
– The goal of the project is to optimize the utilization of limited ventilator and respiratory equipment and improve patient outcomes.
– OnScale is currently testing the solution with medical experts and is actively seeking additional partners and advisors.
OnScale, a provider of Cloud Engineering Simulation, announces Project BreathEasy, a consortium of multiphysics FEA/CFD vendors, medical device manufacturers, engineers, and doctors from around the world who are developing digital twins of the lungs of COVID-19 patients to help doctors improve patient outcomes and optimize the use of limited ventilator resources in major outbreak areas.
Latest COVID-19 outbreak predictions estimate that cases will far exceed available ventilator resources by 10 times or more. COVID-19 patients die from acute respiratory distress syndrome (ARDS), and with limited availability of ventilators in the US, maximizing the per-patient utility of ventilators will be critical to saving lives. Doctors currently rely on textbook predictions of ventilator requirements, but more accurate predictions will maximize ventilator utility. Even a 10% improvement may save thousands of lives.
About Project BreathEasy
OnScale and LEXMA, a leading provider of advanced fluid flow and biomechanical simulation technology, have partnered to create patient-specific digital twins that may accurately predict oxygen and blood flow in a patient’s lungs, helping doctors make critical decisions about ventilator and intubation requirements for COVID-19 patients.
What Is A Digital Twin?
A Digital Twin is a real-time digital representation of a physical system. Digital Twins are built using 3D data (e.g. from CT or Xray images, in the case of a human organ), advanced 3D simulation, real-time physical data from sensors, and artificial intelligence. Each digital twin is patient-specific and built from a combination of medical images (for example from CT scans and X-rays) and thousands of simulations of lung airflow and blood flow using the LEXMA Moebius fluid dynamics solver running on OnScale’s Cloud Simulation platform. AI trained on simulated and measured patient data is used to make fast and accurate predictions of oxygen and blood flow throughout the ventilation and intubation process.
For example, doctors can use Digital Twins of human lungs of COVID-19 patients to make more informed decisions about ventilator settings and ventilation time for a patient. Ideally, better decision making will lead to better patient outcomes and better utilization of limited ventilator resources.
OnScale and LEXMA are currently testing the solution with medical experts and are actively seeking additional partners and advisors. For more information, contact email@example.com.