Reinhard Laubenbacher, PhD
Borna Mehrad, MD
Even before the COVID-19 pandemic, pneumonia was among the most urgent global health threats, with morbidity and mortality greater than ischemic heart disease and the top cause of death in low-income countries. Effective control of pneumonia through improved individualized treatment of pneumonia patients in the hospital is an urgent need and would have a world-wide impact on the reduction of disease burden. For this purpose, we will propose to ARPA-H a 5-year project to build and validate a “digital twin” for the early stages of pneumonia to predict the subsequent course of the disease and optimize treatment. The final deliverable will consist of an algorithm based on a personalized dynamic computational model incorporating key mechanisms relevant for infection control, predict the course of the infection for a given patient, and inform treatment decisions that are free from bias. This technology can also be used to generate virtual patient cohorts for drug trials. We will build and validate this tool to a level that enables transition to commercial development. The scientific and technological innovations resulting from this project will be applicable to other instances of medical digital twin technology as well as drug development.