Limited-Sampling Strategy for the Prediction of Boosted Hard-Gel Saquinavir Exposure at a Dosage of 1000/100 mg Twice Daily in Human Immunodeficiency Virus-Infected Individuals

Abstract

Area under the concentration time curve (AUC) over a dosing interval is considered to be the best estimate of drug exposure in a patient. However, determination of this parameter is costly and often impractical, requiring multiple samples and a great deal of time and resources. A limited-sampling strategy (LSS) may overcome some of these issues, making pharmacokinetic studies easier to perform, particularly in a limited-resource setting. The aim of this work was to develop and validate a pragmatic LSS for the accurate and precise prediction of boosted saquinavir AUC0-12 (AUC over the 12-hour dosing interval) at a dosage of 1000/100 mg twice daily. Pharmacokinetic data were obtained from 34 human immunodeficiency virus (HIV)-infected individuals stable on saquinavir/ritonavir-containing therapy, randomly split into two sets (n = 17 per set). One set was used to construct prediction models using univariate and multivariate analysis (development set), and the second was used to determine the predictive performance of the models (validation set). For single samples, 6- and 10-hour concentrations correlated best with saquinavir AUC0-12 (r2: 0.913 and 0.911, respectively), yet all single samples failed to produce precise and unbiased predictions. However, combinations at 2, 6; 0, 2, 6; 0, 4, 10; 0, 4, 12; and 2, 4, 6 hours achieved good predictive performances, and both precise [root mean squared relative prediction error (%RMSE): 6.4% to 11.9%] and unbiased [mean relative prediction error (%MPE), 95% CI: -2.7%, (-0.8)-2.7 to 1.6%, (-1.8)-4.7] estimations of saquinavir AUC0-12. Of these models, concentrations obtained at 0, 2, 6 and 2, 4, 6 hours are more practical in a clinical setting and are therefore the LSS with most potential. Provided that the technique is validated in specific patient populations, an LSS approach is a potentially useful tool to evaluate the AUC0-12 of saquinavir in resource-limited settings, reducing both costs and volumes of blood taken. It may also aid the choice of sampling times for population analysis.