Center for Quantitative Sciences in Biomedicine
atNorth Carolina State University
The following are examples of current and planned CQSB research projects.
This project, for which CQSB Director Marie Davidian, a statistician; Co-Director
H. T. Banks, an applied mathematician; and
Associate Director
Eric Rosenberg, an
immunologist/infectious disease clinician, serve as investigators, is
supported by a grant from the National Institute of Allergy and Infectious
Diseases. One goal of the project is to use
mathematical-statistical models that represent the interplay between
the human immunodeficiency virus and the host immune system as a basis
for designing realistic longitudinal treatment strategies for HIV
infection that seek to slow the progression of the disease and
clinical trials to study these strategies. A second goal is to design
and carry out a clinical trial that will evaluate such strategies and
collect intensive, detailed longitudinal data on the participants to
be used to inform the development of more realistic models.
More information on this project is given in an
article in
Results, the NCSU publication focused on
Research and Graduate Studies at the University.
Based on longitudinal data collected by
Dr. Rosenberg over several years at Massachusetts General Hospital on
over 100 individuals acutely infected with HIV-1, this team has
developed a complex mathematical-statistical framework to represent the
dynamics of HIV within subjects in the infected population and to
describe the variation in dynamics across the popluation. The team
has demonstrated that these models can be used to predict the
immunological and virological progression of the disease both for
specific subjects and for the population. As a consequence, this
model framework is an elegant tool that may be used to better inform
the design of new HIV treatment strategies through the use of control
theory and simulation. The team has used the models to design the clinical
trial, which will start in January 2008 at Massachuesetts General Hospital.
This
project, which will begin in January 2008, exploits the simulation
capability being developed in the HIV project above to provide a
critical resource to the research community engaged in the study and
formulation of so-called dynamic treatment regimes. This project is
an outgrowth of the very successful
Statistical and Applied Mathematical Sciences
Institute (SAMSI)
Summer 2007 Program on Challenges in Dynamic
Treatment Regimes and Multistage Decision-Making, held in
June 2007 in Research Triangle Park. Dynamic treatment regimes are
sets of sets of sequential decision rules that specify how treatment
should be given over time based on accumulating information on the
patient up to the point of the next decision, thereby tailoring
treatment decisions to the patient. The objective in developing such
multistage decision-making strategies is to improve patient outcomes
over time.
Methodology for designing optimal dynamic treatment regimes based on
data is an emerging area in statistics, applied mathematics, computer
science, operations research, and engineering. In order to test and
evaluate such methodology and benchmark competing methods, "test-bed,"
"generative" data sets that have been generated specifically for this
purpose are an important resource. The CQSB is uniquely poised to
produce a suite of such data sets to be made available to the research
community.
Immediately after an organ is implanted into the body, the human
immune system launches a massive immunologic attack to "reject" it,
and thus immunosuppressive agents are given to transplantation
recipients to eliminate organ rejection, which often must be taken for
the rest of a patient's life. Although life saving, these drugs also
suppress the immune system, leaving the patient vulnerable to further
illness. This presents several key challenges for which
mathematical-statistical modeling holds considerable promise. These
include understanding the reemergence of the hepatitis C virus (HCV)
and/or cytomegalovirus (CMV) and its prevention in patients who have
undergone liver or kidney transplants; dissecting the interplay
between common viruses, such as members of the herpes family, and the
immune systems of transplant patients undergoing immunosuppressive
anti-rejection treatment, who often endure such viral infections; and
designing strategies for optimal use of immunosuppressive therapies in
these patients.
The CQSB is a natural setting for an integrated effort involving some
of the world's top transplant scientists at Massachusetts General
Hospital and Emory University and internationally known quantitative
scientists at NCSU.