Download Chemical & Biomolecular Seminar Series Friday, February 24, 2012

Chemical & Biomolecular Seminar Series
Friday, February 24, 2012
10:00-11:00am (refreshments available at 9:45am)
102 Colburn Laboratory
Scott L. Diamond (BS Cornell University 1986, PhD Rice University 1990) holds the Arthur
E. Humphrey Chair of Chemical and Biomolecular Engineering. He is the founding director of the Penn Center for Molecular Discovery which conducts high throughput chemical
and biological screening. Currently, Dr. Diamond is the Director of the Penn Biotechnology Masters Program, one of the largest in the country with more than 130 students. Dr.
Diamond also serves as Associate Director of the Institute for Medicine and Engineering.
Scott Diamond
Arthur E. Humphrey Professor
Chemical & Biomolecular
Engineering
University of Pennsylvania
Dr. Diamond researches Cardiovascular Therapeutic Technologies in several key areas:
mechanobiology, blood clot dissolving therapies and protein therapeutics, blood coagulation, drug discovery, and gene delivery technologies.
His laboratory has advanced chemical and biomolecular engineering methods with more
than $23 million in research funding from the American Heart Association, NSF and NIH.
He has produced over 150 publications and patents. He is the recipient of the NSF National Young Investigator Award, the NIH FIRST Award, the American Heart Association
Established Investigator Award, and the Allan P. Colburn Award, and is an elected fellow
of the Biomedical Engineering Society.
“High Throughput and Multiscale Patient-Specific Systems Biology”
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 speices are controlled by convective-diffusive transport. Using high throughput experimentation, we obtained a large sets 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 allows prediction of blood function, essential
to prioritizing patient-specific cardiovascular risk and drug response or to identify unsuspected gene mutations.