Chemical Engineering Seminar

Predicting tissue function based upon an individual's unique cells requires a multiscale Systems Biology approach to understand the coupling of intracellular signaling with spatiotemporal gradients of extracellular biochemicals.  In the cardiovasculature, extracellular species are also controlled by convective-diffusive transport.  Using high throughput experimentation, we obtained a large set of platelet responses to combinatorial activators in order to train a neural network (NN) model of platelet activation for several individuals.  Each NN model was then embedded into a kinetic Monte Carlo/finite element/lattice Boltzmann simulation of stochastic platelet deposition under flow.  In silico representations of an individual's platelet phenotype allowed prediction of blood function under flow, essential to prioritizing patient-specific cardiovascular risk and drug response or to identify unsuspected gene mutations.