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<p>Chronic human immunodeficiency virus (HIV) infection continues to pose a major global health challenge, with an estimated 39.9&#xa0;M cases and 1.3&#xa0;M new infections per year. Up to 75%, of people with HIV (PWH) are currently being treated with antiretroviral therapy. The development of effective treatments for HIV requires a detailed understanding of the virus-host interaction. Often, mathematical models are used to inform this understanding as well as to characterize therapeutic response. This work aims to develop a single and fully identifiable population semi-mechanistic pharmacokinetic/pharmacodynamic (popPKPD) model integrating data (drug levels, CD4 + T cells and viral RNA) of five different antiretroviral (ARV) drugs administered in monotherapy: lenacapavir, bictegravir, tenofovir alafenamide, emtricitabine and elvitegravir. Data were obtained from six phase 1 clinical studies and model development was performed using NONMEM 7.5.1. The viral dynamics were best described by expanding the “basic” viral dynamics model with two more populations of infected cells: chronically and latently infected. Obtained death rates values of infected cells &amp; virus were consistent with literature values. Population baseline HIV-RNA was estimated to be 43,460 copies/mL, with an IIV of 141%, the estimated baseline concentrations of CD4 + cells varied largely across the different cell types in the model: 410, 20, 7 and 7 cells/mL for uninfected, infected, chronic and latently infected cells, respectively. The popPKPD model was able to capture key aspects of viral dynamics, drug behaviour, and treatment response. The models developed will serve as a useful tool for further development and optimization of these HIV therapies, especially when evaluating multiple ARVs to be administered in a novel combination setting.</p> Graphical Abstract <p></p>

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Integrated Population Pharmacokinetic-pharmacodynamic Modeling of HIV Virus-host Infection Dynamics in Patients Undergoing Antiretroviral Monotherapy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月13日

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  • Alberto Vegas Rodriguez,
  • Nieves Velez de Mendizábal,
  • Yanan Zheng,
  • Jason T. Hindman,
  • Ramesh Palaparthy,
  • John Ling,
  • Iñaki F. Trocóniz,
  • Ana Ruíz-Garcia,
  • Justin S. Feigelman

摘要

Chronic human immunodeficiency virus (HIV) infection continues to pose a major global health challenge, with an estimated 39.9 M cases and 1.3 M new infections per year. Up to 75%, of people with HIV (PWH) are currently being treated with antiretroviral therapy. The development of effective treatments for HIV requires a detailed understanding of the virus-host interaction. Often, mathematical models are used to inform this understanding as well as to characterize therapeutic response. This work aims to develop a single and fully identifiable population semi-mechanistic pharmacokinetic/pharmacodynamic (popPKPD) model integrating data (drug levels, CD4 + T cells and viral RNA) of five different antiretroviral (ARV) drugs administered in monotherapy: lenacapavir, bictegravir, tenofovir alafenamide, emtricitabine and elvitegravir. Data were obtained from six phase 1 clinical studies and model development was performed using NONMEM 7.5.1. The viral dynamics were best described by expanding the “basic” viral dynamics model with two more populations of infected cells: chronically and latently infected. Obtained death rates values of infected cells & virus were consistent with literature values. Population baseline HIV-RNA was estimated to be 43,460 copies/mL, with an IIV of 141%, the estimated baseline concentrations of CD4 + cells varied largely across the different cell types in the model: 410, 20, 7 and 7 cells/mL for uninfected, infected, chronic and latently infected cells, respectively. The popPKPD model was able to capture key aspects of viral dynamics, drug behaviour, and treatment response. The models developed will serve as a useful tool for further development and optimization of these HIV therapies, especially when evaluating multiple ARVs to be administered in a novel combination setting.

Graphical Abstract