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

Abstract

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.

Mathematical modeling indicates that regulatory inhibition of CD8+T cell cytotoxicity can limit efficacy of IL-15 immunotherapy in cases of high pre-treatment SIV viral load

“…Both this current work and our previous work [21] theoretically demonstrate how immune regulatory mechanisms could be responsible for the lack viral suppression by N-803. Since N-803 seems to be effectively expanding cytolytic SIV-specific cells in both cohorts (Fig 4B), direct reduction of the per-cell killing rate of cytotoxic cells (Fig 4C) is necessary to preclude viral suppression in the mathematical model.…”

“…Here, we adapted and expanded our previous mechanistic mathematical model [21] to replicate two distinct responses to an IL-15 agonist (N-803) observed in two SIV-infected NHP cohorts. Our simulations of the two cohorts assumed the same model parameter values for both cohorts but allowed different pre-treatment steady-states.…”

“…This is a lumped model that can be considered to convolve the dynamics in the blood and lymph. In this work, we updated our previous model of SIV infection and N-803 treatment [21] by separating the CD8 + T cell pool according to activation and SIV-specificity. This change allows the level of CD8 + T cell activation and regulatory inhibition to depend on both viral load and N-803, and it provides closer comparison to SIV-specific CD8 + T cell cytotoxic marker expression as a validation [9].…”

“…Viral growth is controlled by SIV-specific and non-specific targeting of infected cells by active CD8 + T cells (2 nd order rate constants g S , g N , respectively). Note that this simplified infection model can be obtained from a model with healthy cells and infected cells by assuming constant healthy cells and a quasi-steady-state for virions [21, 45, 46]. We did not separately model latently infected cells.…”

“…Proliferation stimulation factor ( ρ ) is limited according to a maximum drug-induced expansion rate for the SIV-naive case ( p · p for this model), which is assumed to be less than the CD8 + T cell clonal expansion rate in rhesus macaques (≈1/day) [15]. Other pharmacokinetic and pharmacodynamic parameters ( k a , k e , v d /F, C 50 ) are carried over from our previous work [16]. The normalized parameters ( μ S , μ N , ψ ) are defined in the Parameter Calculation section. Figures S1 shows the distributions resulting from Bayesian MCMC for the parameters of Eq.…”