• Sickle cell disease (SCD) is an inherited genetic disease of the blood with no known cure at this time.
• Stem cell gene therapy is an emerging experimental therapy for SCD with the potential for lifelong cure but it is an expensive multi-step treatment regimen with several months to over a year before treatment stabilization.
• We developed a quantitative systems pharmacology (QSP) model to predict how varying treatment parameters such as stem cell dose and vector copy number will affect post-treatment hemoglobin and red blood cell dynamics after autologous stem cell gene therapy.
• The model was validated with published clinical data.
• The QSP approach used here can guide rational therapeutic design of gene therapy for SCD and other genetic disorders.
• This webinar is ideal for scientists and decision makers in drug R&D who want to leverage systems pharmacology for drug discovery and development.
Raibatak has a PhD in Chemistry from Cornell University. Before joining Applied BioMath he was in academia. Raibatak's prior research areas include single molecule biophysics, immunology and imaging. His areas of expertise are mathematical biology and applied statistics.
Date: Tuesday, November 30, 2021
Time: 2pm ET / 11am PT
Duration: 1 Hour
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