Lymph node digital twins for predictive pharmacology and target validation in HIV

Active Project Grant Awarded Last action

Award ID
F31AI203275
Recipient
Awarding agency
Obligated
$73,436

Award facts

Assistance listing
93.855 Allergy and Infectious Diseases Research
Completion date 0% complete
Originally
Place of performance
Newark, DE 19713, USA

Award details come from USAspending.gov.

Description

As the agency reported it.

Abstract
Despite the success of antiretroviral (ARV) therapy in transforming HIV into a manageable chronic illness, viral rebound occurs in nearly all patients upon treatment interruption. This is facilitated in part due to the persistence of virus in pharmacological sanctuary sites, areas of the body that arvs cannot penetrate at effective concentrations, resulting in a population of virus that can recover once systemic therapeutic concentrations are low. One of these sites is the lymph node (LN). The inability of arvs to penetrate the LN at therapeutic levels is due to the LN's highly compartmentalized architecture. This architecture evolved to facilitate high rates of interaction between immune cells and antigen-presenting cells (apcs) necessary to develop an adaptive immune response to foreign antigens. The interactions between lymphocytes and apcs primarily take place in the lobule, which, unlike the rest of the LN, is sparsely vascularized. IT has been shown that LN size plays a role in drug penetration; however, other geometric aspects, such as those altered by HIV-induced inflammation, are not well understood. In addition, LNS are highly plastic organs that undergo structural remodeling due to factors that include prior infections, HIV disease stage, SEX, and age. This variability in LN geometry complicates the evaluation of new arvs and treatment regimens for effective LN penetration across a population of individuals with HIV. Therefore, pharmacokinetic (PK) models are often used to test and define the LN-penetrating properties of different arvs. Current pharmacokinetic (PK) models lack the resolution needed to capture spatial drug heterogeneity and its impact on viral persistence. A clearer understanding of how LN structure governs ARV distribution is essential for designing effective treatments. This project will develop a computational framework to model LN geometry and predict ARV distribution. The goal of aim 1 is to determine a relationship between structural remodeling due to inflammation and ARV transport in the LN. Sensitivity analysis will identify a relationship between geometric parameters that scale with inflammation stage and resultant ARV distribution. Aim 2 will generate a virtual patient population of 3D lymph nodes using sparse 2D imaging data. These studies will improve our ability to personalize HIV treatment and advance toward a functional cure. This work will also provide the applicant with interdisciplinary training in computational modeling, machine learning, and translational virology.

Transactions

Action Obligated Date
Amendment $0
Original award $36,718

Quick answers

Who received award F31AI203275?

F31AI203275 was awarded to University Of Delaware by National Institute of Allergy and Infectious Diseases (National Institutes of Health) on February 13, 2027.

How much is award F31AI203275 worth?

$73,436 has been obligated on F31AI203275.

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