Wojciech Krzyzanski PhD, MA
Associate Professor, University at Buffalo
Pharmacodynamic age structured population model for cell trafficking
October 19, 2022, 9:00-10:00 AM PDT

Registration 
(Free)<https://attendee.gotowebinar.com/register/3755313121478798349?source=Website>:
 https://rosaandco.com/webinars
Abstract
Cell trafficking encompasses movement of the immune system cells (e.g., 
granulocytes, lymphocytes) between the blood and the extravascular tissues 
(e.g., lymph nodes). Basophils are effector cells responsible for inflammatory 
reactions during the immune challenge. Basophils are used as biomarkers of 
inflammatory responses. Corticosteroids are known to suppress cell trafficking. 
Existing models of cell trafficking employ the methodology of compartmental 
systems where the cells transfer between two compartments at first-order rates. 
Such an approach limits the model ability to account for prolonged times most 
of the immune cells spend outside the vasculature before recirculating to the 
blood.

The age-structured population models introduce the transit time as a structure 
that allows to quantify the distribution of times the immune cells spend in the 
blood and the extravascular tissues. The key tools are the hazards of transfer 
between the tissues and hazards of cell death. The hazard can depend on the 
cell age (e.g., the time it spends in the tissue) and the time (e.g., through 
the time-dependent drug effect).

This webinar will show how to apply the well-known McKendrick age-structured 
population model to describe drug effects on cell trafficking between blood 
cells and cells in the extravascular space. The model was validated using 
published data on corticosteroid inhibition of the basophil counts in healthy 
volunteers using mixed effects modeling. The corticosteroid effect decreases 
the hazard of cell recirculation from the extravascular tissues. We will show 
that the age structure is essential to explain the rebound observed in the 
blood count response to a single dose drug. We will also provide insights on 
how to use age-structure population models to describe pharmacodynamics of 
other cell populations.

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