INFLUENCE OF DELAYED VIRAL PRODUCTION ON VIRAL DYNAMICS IN HIV-1-INFECTED PATIENTS

We present and analyze a model for the interaction of human immunodefi ciency virus type 1 (HIV-1) with target cells that includes a time del ay between initial infection and the formation of productively infecte d cells. Assuming that the variation among cells with respect to this 'intracellular' delay can be approximated by a gamma distribution, a h igh flexible distribution that can mimic a variety of biologically pla usible delays, we provide analytical solutions for the expected declin e in plasma virus concentration after the initiation of antiretroviral therapy with one or more protease inhibitors. We then use the model t o investigate whether the parameters that characterize viral dynamics can be identified from biological data. Using non-linear least-squares regression to fit the model to simulated data in which the delays con form to a gamma distribution, we show that good estimates for free vir al clearance rates, infected cell death rates, and parameters characte rizing the gamma distribution can be obtained. For simulated data sets in which the delays were generated using other biologically plausible distributions, reasonably good estimates for viral clearance rates, i nfected cell death rates, and mean delay times can be obtained using t he gamma-delay model. For simulated data sets that include added simul ated noise, viral clearance rate estimates are not as reliable. If the mean intracellular delay is known, however, we show that reasonable e stimates for the viral clearance rate can be obtained by taking the ha rmonic mean of viral clearance rate estimates from a group of patients . These results demonstrate that it is possible to incorporate distrib uted intracellular delays into existing models for HIV dynamics and to use these refined models to estimate the half-life of free virus from data on the decline in HIV-1 RNA following treatment. (C) 1998 Elsevi er Science Inc. All rights reserved.