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Lymph Node Digital Twins for Predictive Pharmacology and Target Validation in HIV

Award Number: F31AI203275
ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: FELLOWSHIP/SCHOLARSHIP/STUDENT LOANS
PERIOD OF PERFORMANCE START DATE: 08/15/2026
PERIOD OF PERFORMANCE END DATE: 08/14/2029

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Lymph Node Digital Twins for Predictive Pharmacology and Target Validation in HIV - 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.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $36,718 )
2026	2026	UNIVERSITY OF DELAWARE	550 S COLLEGE AVE	NEWARK	DE	19713	NEW CASTLE	USA	Allergy and Infectious Diseases Research	001	1	8/13/2026	NEW	$0
2026	2026	UNIVERSITY OF DELAWARE	550 S COLLEGE AVE	NEWARK	DE	19713	NEW CASTLE	USA	Allergy and Infectious Diseases Research	000	1	8/13/2026	NEW	$36,718
														Subtotal = $36,718

Grand Total All Awards = $36,718

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Lymph Node Digital Twins for Predictive Pharmacology and Target Validation in HIV

Award Number: F31AI203275

ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: FELLOWSHIP/SCHOLARSHIP/STUDENT LOANS

PERIOD OF PERFORMANCE START DATE: 08/15/2026

PERIOD OF PERFORMANCE END DATE: 08/14/2029

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