Drug-Class Specific Impact of Antivirals on the Reproductive Capacity of HIV

Abstract

Predictive markers linking drug efficacy to clinical outcome are a key component in the drug discovery and development process. In HIV infection, two different measures, viral load decay and phenotypic assays, are used to assess drug efficacy in vivo and in vitro. For the newly introduced class of integrase inhibitors, a huge discrepancy between these two measures of efficacy was observed. Hence, a thorough understanding of the relation between these two measures of drug efficacy is imperative for guiding future drug discovery and development activities in HIV. In this article, we developed a novel viral dynamics model, which allows for a mechanistic integration of the mode of action of all approved drugs and drugs in late clinical trials. Subsequently, we established a link between in vivo and in vitro measures of drug efficacy, and extract important determinants of drug efficacy in vivo. The analysis is based on a new quantity—the reproductive capacity—that represents in mathematical terms the in vivo analog of the read-out of a phenotypic assay. Our results suggest a drug-class specific impact of antivirals on the total amount of viral replication. Moreover, we showed that the (drug-)target half life, dominated by immune-system related clearance processes, is a key characteristic that affects both the emergence of resistance as well as the in vitro–in vivo correlation of efficacy measures in HIV treatment. We found that protease- and maturation inhibitors, due to their target half-life, decrease the total amount of viral replication and the emergence of resistance most efficiently.

Integration of Reaction Kinetics Theory and Gene Expression Programming to Infer Reaction Mechanism

“…There is a substantive literature pertaining to development of models describing HIV-1 (Aviran et al 2010, Bonhoeffer et al 2000, Burg et al 2009, Herz et al 1996, Liang et al 2010, Nowak and May 2000, Perelson et al 1996, Perelson 2002, Prosperi et al 2009, von Kleist et al 2010, Wu and Zhang 2010, Zeng and Yang 2010. The HIV-1 dynamic model of Perelson and Nelson (Perelson and Nelson 1999) shown in Figure 4.1 was selected as the basis for this work because it Table 4.2.…”

“…The technology also permits verification against experimental results. Ideally, the resulting model may be used to predict progression of the disease (Bogojeska et al 2010, Burg et al 2009, Castiglione and Paci 2010, Degon et al 2008, de Sousa et al 2010, Guedj et al 2010, Hoffmann et al 2002, Itakura 2010, Perelson et al 1996, Smith and Ribeiro 2010, Srivastava et al 2002, von Kleist et al 2010, Wendelsdorf et al 2010, Yang et al 2007. It is also possible to identify, develop, and optimize treatment strategies in a mathematically rigorous fashion.…”

“…Mechanistic models describing chemical kinetic data sets are often defined by making assumptions as to some model structure. Modeling of viral systems such as HIV-1, hepatitis B, and others has been of great interest in the hopes of developing treatment strategies based upon those models (Aviran et al 2010, Burg et al 2009, de Sousa and Cunha 2010, Guedj and Neumann 2010, Herz et al 1996, Krishnan and Dixit 2011, Nowak and May 2000, Perelson 2002, Prosperi et al 2009, Ribeiro and Bonhoeffer 2000, Srivastava et al 2002, von Kleist et al 2010, Wu and Zhang 2010, Zeng and Yang 2010) . Many models of various sizes and structures have been proposed for these systems taking into account a wide range of biochemical species.…”

“…Human immunodeficiency virus type 1 (HIV-1) is an important disease that has received significant interest from the modeling community (Aviran et al 2010, Burg et al 2009, Herz et al 1996, Nowak and May 2000, Perelson et al 1996, Perelson 2002, Prosperi et al 2009, Ribeiro and Bonhoeffer 2000, von Kleist et al 2010, Wu and Zhang 2010, Zeng and Yang 2010. In recent years, HIV-1 treatments have significantly reduced AIDS-related mortalities and have enhanced long-term disease control (Dybul et al 2001, Fagard et al 2003, Powderly 2002, Ruiz et al 2001.…”

Quantifying the Impact of Nevirapine-Based Prophylaxis Strategies To Prevent Mother-to-Child Transmission of HIV-1: a Combined Pharmacokinetic, Pharmacodynamic, and Viral Dynamic Analysis To Predict Clinical Outcomes

“…In order to quantify the impact of NVP prophylaxis on virus transmission, we adapted the virus dynamics model presented previously (55) by discarding the longer-lived cell types (representing macrophages and latently infected T cells), as they do not impact the observed viral dynamics after short-course maternal NVP administration. The utilized model of HIV-1 dynamics and mother-to-child transmission is depicted in Fig.…”