Speaker: Feilim Mac Gabhann
Abstract:
Bone marrow transplant shows promise as a curative treatment for HIV; computational models can assist us in understanding early trials and in designing improved treatment. In particular, moving away from models of 'typical' or 'average' patients to populations of patient models based on patient data can identify treatment characteristics and biomarkers that influence treatment efficacy across the population. We have developed a molecular-detailed, mechanistic model of HIV infection to design stem-cell therapies that incorporate anti-HIV gene therapy and to identify logistics of successful treatment, e.g. levels of gene expression and the percentage of augmented T cells and macrophages (transduction efficiency). The model simulates the dynamics of HIV infection to track key restriction factors and their interactions with HIV-encoded proteins, the virus, and multiple immune cell types: CD4+ T-cells, macrophages, latently-infected T-cells, and CTLs. Using viral load and T-cell count data from HIV-infected individuals, we created a virtual population of HIV patients to explore interpatient variability of stem-cell therapies.
Scales: Proteins, Cells, Organ, Population
Fields: Non-drug therapy; Cell-based therapy; Interpatient Variability; Virtual Clinical Trial
About the Speaker:
Dr. Mac Gabhann is an Assistant Professor in Biomedical Engineering and part of the Institute for Computational Medicine at Johns Hopkins University. The Mac Gabhann lab uses computational models and systems pharmacology methods to design therapeutic approaches to combat diseases including peripheral artery disease, cancer, ALS, pre-eclampsia and HIV. Dr. Mac Gabhann is a Sloan Research Fellow and recipient of a K99/R00 NIH Pathway to Independence Award, the 2010 August Krogh Young Investigator Award from the Microcirculatory Society, and the 2012 Arthur C. Guyton Award for Excellence in Integrative Physiology from the American Physiology Society. He is the author of over 50 peer-reviewed papers, and is an Associate Editor for PLoS Computational Biology.
Link: http://www.bme.jhu.edu/people/primary.php?id=928
Return to the 2015 MSM Consortium Agenda
Event Date:
Wednesday, September 9, 2015