HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viral generation time

Science

Volumn 271, Issue 5255, 1996, Pages 1582-1586

  Perelson, Alan S ^a   Neumann, Avidan U ^a   Markowitz, Martin ^b   Leonard, John M ^c   Ho, David D ^b  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

^b AARON DIAMOND AIDS RESEARCH CENTER   (United States)

^c ABBOTT LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEINASE; RITONAVIR;

ARTICLE; CELL SURVIVAL; CLINICAL ARTICLE; HUMAN; HUMAN CELL; HUMAN IMMUNODEFICIENCY VIRUS 1; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; LIFE CYCLE; MATHEMATICAL MODEL; ORAL DRUG ADMINISTRATION; PATHOGENESIS; PRIORITY JOURNAL; VIRION; VIROGENESIS; VIRUS PARTICLE;

HUMAN IMMUNODEFICIENCY VIRUS; HUMAN IMMUNODEFICIENCY VIRUS 1;

EID: 0029967721     PISSN: 00368075     EISSN: None     Source Type: Journal    
DOI: 10.1126/science.271.5255.1582     Document Type: Article

References (22)

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9. o must balance the virion clearance at rate c.
10. c/(c-δ)][c exp(-δt) - δ exp(-ct)], the equation introduced by Wei et al. (2) for analysis of the effects of drug treatment on viral load. Their analysis was based on Eqs. 1 and 2 and the assumption that no new infections occur after drug treatment (k = 0 after treatment). Equation 6 is a new model appropriate for protease inhibitors, which do not prevent infections ansing from preexisting mature infectious virions. Because of the symmetry between c and δ in the Wei et al equation, the virion clearance rate cannot be distinguished from the infected cell death rate by data fitting
11. Because our parameter estimates are based on the assumption of complete inhibition of the production of new infectious virions and no increase in target cells, we expect our parameter estimates to be minimal estimates. Generalizing our model to relax these two assumptions, we can show that 5 is always a minimal estimate and that, with target cell growth, c is typically a minimal estimate We tested how the estimates of c and δ depend on the assumption that ritonavir is 100% effective as follows: We generated viral load data assuming different drug effectivenesses with c = 3 and δ = 0 5. With these "data," we used our fitting procedure to estimate c and δ under the assumption that the drug is 100% effective For data generated with η = 1.0, 0 99, 0 95, and 0.90, we estimated c = 3 000, 3.003, 3.015, and 3.028, respectively, and δ = 0.500, 0.494, 0.470, and 0.441, respectively. Thus, our estimate of c remains essentially unchanged, whereas that of δ is a slight underestimate (for example, for η = 0 95, δ = 0.47 rather than the true 0 5). Consequently, if a drug is not completely effective, cell life-spans may be somewhat less than we estimate. If the target cells are allowed to increase by the maximum factor observed In the five patients (that is, fivefold), we find that the derived values of c and δ are minimal estimates. Thus, for example, for data generated with η = 1, with c = 3.00 and δ = 0.500, we find that our fitting procedure yields estimates of c = 2.76 and δ = 0.499.
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15. p rather than infected cells T' are to be tracked, Eq 1 can be replaced by equation presented Models of this type can also be solved explicitly when ω(t′) is given by a gamma function. M. Nowak and A Herz (personal communication) have solved this model for the case where w(t′) is a delta function, in which case the delay simply adds to the pharmacologie delay and Eq 6 is regained after this combined delay Analysis of current data by nonlinear least squares estimation has so far not allowed accurate simultaneous estimation of c, δ, and the intracellular delay. However, the qualitative effect of including the delay in the model is to increase the estimate of c, which is consistent with our claim that the values of c in Table 1 are minimal estimates. Higher values of c (hence lower values of 1/c) will lead to increased estimates of the intracellular delay, S - (1/c). Thus our estimate of the duration of the intracellular phase, as derived above and given in Table 2, is still a minimal estimate.
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22. We thank the patients for participation; A. Hurley, Y. Cao, and scientists at Chiron for assistance; B, Goldstein for the use of his nonlinear least squares fitting package; and G. Bell, T. Kepler, C. Macken, E. Schwartz, and B. Sulzer for helpful discussions and calculations. Portions of this work were performed under the auspices of the U.S. Department of Energy. Supported by Abbott Laboratories, grants from NIH (NO1 Al45218 and RR06555) and from the New York University Center for AIDS Research (Al27742) and General Clinical Research Center (MO1 RR00096), the Aaron Diamond Foundation, the Joseph P. Sullivan and Jeanne M. Sullivan Foundation, and the Los Alamos National Laboratory Directed Research and Development program