Jessica Oakes
Inria@SiliconValley Post-Doc
Jessica Oakes received her PhD from University of California San Diego in Mechanical Engineering. She started collaborating with the CARDIO team during a three-month internship in 2011 and returned as a Whitaker Postdoctoral Scholar for a year in 2014. Jessica is now continuing her work with the support of an Inria@SiliconValley postdoctoral fellowship.
Jessica’s research interests lie in working on the interface of engineering and medicine to develop novel experimental and computational tools to predict aerosol fate in the lung.
.
What are the health consequences of airborne toxins (e.g. air pollution and cigarette smoke)? Can we optimize drug delivery to treat lung (e.g. asthma and emphysema) or whole body diseases (e.g. diabetes)? Is it possible to develop and employ physiologically accurate models to predict aerosol fate in the lung? To answer these questions we must take an inter-disciplinary approach and bring together experts in computational physics, engineering, and medicine.
The Inria Associate Team CARDIO was first established in 2008. The initial objectives were to develop in silico models to predict blood flow in healthy and pathological states. Recently, the team’s objectives expanded to include developing computational models to predict airflow and particle transport in in the lungs. This team includes researchers from University of California San Diego, University of California Berkeley, Stanford, and Inria Paris-Rocquencourt.
Particle deposition location for inhalation (panel A) and exhalation (panel B) in image-based rat airways.
The goal of this current work, a collaborative effort between University of California Berkeley (Dr. Jessica Oakes and Professor Shawn Shadden) and Inria Paris-Roquencourt (Drs. Irene Vignon-Clementel and Celine Grandmont) is to develop a novel whole lung in silico model. Recent advances in computational resources have enabled sophisticated airflow and particle transport simulations in the pulmonary airways, however it is not currently feasible to solve for transport for all length and time scales of the lung. This new framework couples 3D and 1D flow and transport models, enabling predictions of whole lung particle deposition throughout respiration.
