Models of Viral Population Dynamics

Padmanabhan, Pranesh; Dixit, Narendra M.

doi:10.1007/82_2015_458

Cited by 9 publications

(9 citation statements)

References 161 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We followed the practice of representing the within-host dynamics of viral infection with a system of ordinary differential equations [ 25 – 32 ]. Eqs ( 1 – 4 ) describe the model of viral infection and immune response in the absence of N-803 treatment.…”

Section: Methodsmentioning

confidence: 99%

“…Computational models are well-suited to quantify and deconvolute the effects of multiple interacting mechanisms in complex systems. Ordinary differential equation (ODE) models have been used to study HIV and its treatment (reviewed in [ 25 , 26 ]). ODE models have investigated the potential of various treatment strategies, including reactivating latent infections [ 27 , 28 ], cytotoxic cell stimulation [ 27 ], and cellular vaccines [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mathematical modeling of N-803 treatment in SIV-infected non-human primates

et al. 2021

View full text Add to dashboard Cite

Immunomodulatory drugs could contribute to a functional cure for Human Immunodeficiency Virus (HIV). Interleukin-15 (IL-15) promotes expansion and activation of CD8+ T cell and natural killer (NK) cell populations. In one study, an IL-15 superagonist, N-803, suppressed Simian Immunodeficiency Virus (SIV) in non-human primates (NHPs) who had received prior SIV vaccination. However, viral suppression attenuated with continued N-803 treatment, partially returning after long treatment interruption. While there is evidence of concurrent drug tolerance, immune regulation, and viral escape, the relative contributions of these mechanisms to the observed viral dynamics have not been quantified. Here, we utilize mathematical models of N-803 treatment in SIV-infected macaques to estimate contributions of these three key mechanisms to treatment outcomes: 1) drug tolerance, 2) immune regulation, and 3) viral escape. We calibrated our model to viral and lymphocyte responses from the above-mentioned NHP study. Our models track CD8+ T cell and NK cell populations with N-803-dependent proliferation and activation, as well as viral dynamics in response to these immune cell populations. We compared mathematical models with different combinations of the three key mechanisms based on Akaike Information Criterion and important qualitative features of the NHP data. Two minimal models were capable of reproducing the observed SIV response to N-803. In both models, immune regulation strongly reduced cytotoxic cell activation to enable viral rebound. Either long-term drug tolerance or viral escape (or some combination thereof) could account for changes to viral dynamics across long breaks in N-803 treatment. Theoretical explorations with the models showed that less-frequent N-803 dosing and concurrent immune regulation blockade (e.g. PD-L1 inhibition) may improve N-803 efficacy. However, N-803 may need to be combined with other immune therapies to countermand viral escape from the CD8+ T cell response. Our mechanistic model will inform such therapy design and guide future studies.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mathematical modeling of N-803 treatment in SIV-infected non-human primates

et al. 2021

View full text Add to dashboard Cite

show abstract

“…1,2 Modeling studies have since yielded key insights into the pathogenesis of HIV, including the evolution of drug resistance and immune escape, and guided strategies of intervention. 3,4 Much of this knowledge has been gleaned from studies on patients with HIV-1 subtype B (HIV-1B) infection. In the present context of the HIV epidemic, HIV-1 subtype C (HIV-1C) is the most prevalent subtype, particularly in low and middle-income countries (LMIC) like India, South Africa, and Ethiopia, and accounts for nearly 48% of all global infections.…”

Section: Introductionmentioning

confidence: 99%

Viral Decay Dynamics and Mathematical Modeling of Treatment Response: Evidence of Lower in vivo Fitness of HIV-1 Subtype C

Shet

Nagaraja

Dixit

2016

JAIDS Journal of Acquired Immune Deficiency Syndromes

Self Cite

View full text Add to dashboard Cite

show abstract

“…The viral population within an infected individual comprises virions containing closely related but not identical viral genomes (Andino & Domingo, ; Padmanabhan & Dixit, ). V i denotes the viral subpopulation containing genomes of type i .…”

Section: Effector Functionmentioning

confidence: 99%

“…Variants of the model have captured the changes in viral load when this balance is perturbed using antiretroviral therapy (ART) and yielded estimates of the half‐lives of virions and infected cells in vivo (Ho et al, ; Nowak & May, ; Perelson, ; Perelson, Neumann, Markowitz, Leonard, & Ho, ; Wei et al, ). The models have also been extended to other viruses (Best et al, ; Dixit, Layden‐Almer, Layden, & Perelson, ; Neumann et al, ; Nowak et al, ; Padmanabhan & Dixit, ; Padmanabhan, Garaigorta, & Dixit, ). It has been of interest to estimate the contribution of effector CD8 + T cells in the observed loss of infected cells (Gadhamsetty, Beltman, & de Boer, ).…”

Section: Effector Functionmentioning

confidence: 99%

Towards multiscale modeling of the CD8⁺T cell response to viral infections

Baral

Raja

Sen

et al. 2019

WIREs Mechanisms of Disease

Self Cite

View full text Add to dashboard Cite

The CD8 + T cell response is critical to the control of viral infections. Yet, defining the CD8 + T cell response to viral infections quantitatively has been a challenge. Following antigen recognition, which triggers an intracellular signaling cascade, CD8 + T cells can differentiate into effector cells, which proliferate rapidly and destroy infected cells. When the infection is cleared, they leave behind memory cells for quick recall following a second challenge. If the infection persists, the cells may become exhausted, retaining minimal control of the infection while preventing severe immunopathology. These activation, proliferation and differentiation processes as well as the mounting of the effector response are intrinsically multiscale and collective phenomena. Remarkable experimental advances in the recent years, especially at the single cell level, have enabled a quantitative characterization of several underlying processes. Simultaneously, sophisticated mathematical models have begun to be constructed that describe these multiscale phenomena, bringing us closer to a comprehensive description of the CD8 + T cell response to viral infections. Here, we review the advances made and summarize the challenges and opportunities ahead. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Cell Fates Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models

show abstract

Models of Viral Population Dynamics

Cited by 9 publications

References 161 publications

Mathematical modeling of N-803 treatment in SIV-infected non-human primates

Mathematical modeling of N-803 treatment in SIV-infected non-human primates

Viral Decay Dynamics and Mathematical Modeling of Treatment Response: Evidence of Lower in vivo Fitness of HIV-1 Subtype C

Towards multiscale modeling of the CD8⁺T cell response to viral infections

Contact Info

Product

Resources

About

Models of Viral Population Dynamics

Cited by 9 publications

References 161 publications

Mathematical modeling of N-803 treatment in SIV-infected non-human primates

Mathematical modeling of N-803 treatment in SIV-infected non-human primates

Viral Decay Dynamics and Mathematical Modeling of Treatment Response: Evidence of Lower in vivo Fitness of HIV-1 Subtype C

Towards multiscale modeling of the CD8+T cell response to viral infections

Contact Info

Product

Resources

About

Towards multiscale modeling of the CD8⁺T cell response to viral infections