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HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics.

ABSTRACT: Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3-5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients.

SUBMITTER: Luo R

PROVIDER: S-EPMC3397989 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:UnlabelledHIV-1-specific immune responses induced by a dendritic cell (DC)-based therapeutic vaccine might have some effect on the viral reservoir. Patients on combination antiretroviral therapy (cART) were randomized to receive DCs pulsed with autologous HIV-1 (n = 24) (DC-HIV-1) or nonpulsed DCs (n = 12) (DC-control). We measured the levels of total and integrated HIV-1 DNA in CD4 T cells isolated from these patients at 6 time points: before any cART; before the first cART interruption, which was at 56 weeks before the first immunization to isolate virus for pulsing DCs; before and after vaccinations (VAC1 and VAC2); and at weeks 12 and 48 after the second cART interruption. The vaccinations did not influence HIV-1 DNA levels in vaccinated subjects. After the cART interruption at week 12 postvaccination, while total HIV-1 DNA increased significantly in both arms, integrated HIV-1 DNA did not change in vaccinees (mean of 1.8 log10 to 1.9 copies/10(6) CD4 T cells, P = 0.22) and did increase in controls (mean of 1.8 log10 to 2.1 copies/10(6) CD4 T cells, P = 0.02) (P = 0.03 for the difference between groups). However, this lack of increase of integrated HIV-1 DNA observed in the DC-HIV-1 group was transient, and at week 48 after cART interruption, no differences were observed between the groups. The HIV-1-specific T cell responses at the VAC2 time point were inversely correlated with the total and integrated HIV-1 DNA levels after cART interruption in vaccinees (r [Pearson's correlation coefficient] = -0.69, P = 0.002, and r = -0.82, P < 0.0001, respectively). No correlations were found in controls. HIV-1-specific T cell immune responses elicited by DC therapeutic vaccines drive changes in HIV-1 DNA after vaccination and cART interruption. (This study has been registered at ClinicalTrials.gov under registration no. NCT00402142.)ImportanceThere is an intense interest in developing strategies to target HIV-1 reservoirs as they create barriers to curing the disease. The development of therapeutic vaccines aimed at enhancing immune-mediated clearance of virus-producing cells is of high priority. Few therapeutic vaccine clinical trials have investigated the role of therapeutic vaccines as a strategy to safely eliminate or control viral reservoirs. We recently reported that a dendritic cell-based therapeutic vaccine was able to significantly decrease the viral set point in vaccinated patients, with a concomitant increase in HIV-1-specific T cell responses. The HIV-1-specific T cell immune responses elicited by this therapeutic dendritic cell vaccine drove changes in the viral reservoir after vaccinations and significantly delayed the replenishment of integrated HIV-1 DNA after cART interruption. These data help in understanding how an immunization could shift the virus-host balance and are instrumental for better design of strategies to reach a functional cure of HIV-1 infection.

Project description:Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART) interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients-between 40 and 150-will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two "Boston patients", recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV+ cells in the recipient versus newly infected cells from the donor made to the residual reservoir that eventually caused rebound. Together, these tools will aid HIV researchers in the evaluating new potentially-curative strategies that target the latent reservoir.

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HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics.

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