Antiretroviral Treatment of Adult HIV Infection

Thompson, Melanie; Aberg, Judith A.; Cahn, Pedro; Montaner, Julio S. G.; Rizzardini, Giuliano; Telenti, Amalio; Gatell, José M.; Günthard, Huldrych F.; Hammer, Scott M.; Hirsch, Martin S.; Jacobsen, Donna M.; Reiss, Peter; Richman, Douglas D.; Volberding, Paul A.; Yéni, Patrick; Schooley, Robert T.

doi:10.1001/jama.2010.1004

Cited by 715 publications

(298 citation statements)

References 54 publications

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“…Among the HIV PI that have been approved, lopinavir, atazanavir, darunavir and fosamprenavir are most frequently prescribed. 5,6 HIV PI are extensively metabolized by CYP3A enzymes 7,8 and their biliary excretion is mediated by the efflux transporters P-gp (ABCB1) and MRP2 (ABCC2). 8,9 In addition, it has been shown that some HIV PI (or their metabolites) are excreted via the feces for more than 75 %.…”

Section: Introductionmentioning

confidence: 99%

Clearance Prediction of HIV Protease Inhibitors in Man: Role of Hepatic Uptake

Bruyn

Stieger

Augustijns

et al. 2016

Journal of Pharmaceutical Sciences

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The aim of this work was to explore the contribution of the organic anion transporting polypeptide-1B (OATP1B) drug transporters in the hepatic clearance (Cl) of all marketed HIV protease inhibitors (PI) in humans. HIV PI uptake rates in OATP1B1/1B3-transfected Chinese hamster ovary cells were converted to uptake Cl values in human hepatocytes via a relative activity factor, which was determined by comparing uptake of known substrates between OATP1B1/3-transfected cells and human hepatocytes. Metabolic Cl values were determined in human liver microsomes. In vivo hepatic Cl values were calculated either by combining drug uptake and metabolism or based on one of these individual Cl processes and compared with published in vivo hepatic Cl values. Excellent in vitro-in vivo correlation (R(2) = 0.85) was observed when only uptake Cl values were used, but not when only metabolic Cl was used (R(2) = 0.40). The correlation did not improve when both processes were taken into account (R(2) = 0.85). PBPK models confirmed the remarkable sensitivity of predicted exposure to hepatic drug uptake, indicating a key role for OATP1B1/3 in hepatic disposition of several HIV PI in man. This may contribute to the interindividual variability in systemic and hepatic exposure to these drugs in the clinic.

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Section: Introductionmentioning

confidence: 99%

Clearance Prediction of HIV Protease Inhibitors in Man: Role of Hepatic Uptake

Bruyn

Stieger

Augustijns

et al. 2016

Journal of Pharmaceutical Sciences

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“…2 Interpretation of this genotype can be complex and is usually performed using rules-based software that relates point mutations to viral susceptibility to single drugs. 4 However, different systems provide different interpretations and it is difficult to relate the results for individual drugs to the likely responses to potential drug combinations.…”

Section: Introductionmentioning

confidence: 99%

The use of computational models to predict response to HIV therapy for clinical cases in Romania

Revell¹,

Ene²,

Duiculescu³

et al. 2012

GERMS

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Introduction A major challenge in Romania is the optimisation of antiretroviral therapy for the many HIV-infected adults with, on average, a decade of treatment experience. The RDI has developed computational models that predict virological response to therapy but these require a genotype, which is not routinely available in Romania. Moreover the models, which were trained without any Romanian data, have proved most accurate for patients from the healthcare settings that contributed the training data. Here we develop and test a novel model that does not require a genotype, with test data from Romania.Methods A random forest (RF) model was developed to predict the probability of the HIV viral load (VL) being reduced to <50 copies/ml following therapy change. The input variables were baseline VL, CD4 count, treatment history and time to follow-up. The model was developed with 3188 treatment changes episodes (TCEs) from North America, Western Europe and Australia. The model's predictions for 100 independent TCEs from the RDI database were compared to those of a model trained with the same data plus genotypes and then tested using 39 TCEs from Romania in terms of the area under the ROC curve (AUC).Results When tested with the 100 independent RDI TCEs, the AUC values for the models with and without genotypes were 0.88 and 0.86 respectively. For the 39 Romanian TCEs the AUC was 0.60. However, when 14 cases with viral loads that may have been between 50 and 400 copies were removed, the AUC increased to 0.83. Discussion Despite having been trained without data from Romania, the model predicted treatment responses in treatment-experienced Romanian patients with clade F virus accurately without the need for a genotype. The results suggest that this approach might be generalisable and useful in helping design optimal salvage regimens for treatment-experienced patients in countries with limited resources where genotyping is not always available.

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“…With reference to some conservative evaluations, up to 10% of patients who are controlled by HAART show some types of genotypic drug resistance after two years of therapy. In this regard, reports indicate that up to 30% of patients experience viral failure with more than one major resistance mutation after less than six years of commencing HAART [27] . Therefore, the increasing prevalence of ARDR has become a growing concern, especially among developed countries with higher availability of ARV agents.…”

Section: History and Mechanisms Of Anti-retroviral Drug Resistance (Amentioning

confidence: 99%