ritonavir and Latent-Tuberculosis

Isoniazid preventive therapy is recommended in patients on antiretroviral treatment (ART) with latent tuberculous infection to prevent progression to active tuberculosis disease. Isoniazid (INH) inhibits cytochrome (CY) P3A4, which metabolises lopinavir (LPV). The administration of INH may cause higher LPV concentrations, which may increase LPV toxicity. LPV bioavailability is increased by co-formulated ritonavir (r), which may enhance the interaction of INH on LPV. We studied the effect of INH on LPV concentrations by administering INH for 7 days and performing intensive pharmacokinetic sampling in 16 human immunodeficiency virus infected patients established on LPV/r-based ART. INH did not significantly increase steady-state LPV area under the plasma concentration-time curve calculated for the 12 h-dosing interval.

Topics: Adult; Anti-HIV Agents; Antitubercular Agents; Area Under Curve; Biological Availability; Disease Progression; Drug Combinations; Drug Interactions; Female; HIV Infections; Humans; Isoniazid; Latent Tuberculosis; Lopinavir; Male; Ritonavir; South Africa

Physiologically based pharmacokinetic (PBPK) models have gained in popularity in the last decade in both drug development and regulatory science. PBPK models differ from classical pharmacokinetic models in that they include specific compartments for tissues involved in exposure, toxicity, biotransformation, and clearance processes connected by blood flow. This study aimed to address the gaps between the mathematics and pharmacology framework observed in the literature. These gaps included nonconserved systems of equations and compartment concentration that were not biologically relatable to the tissues of interest. The resulting system of nonlinear differential equations is solved numerically with various methods for benchmarking and comparison. Furthermore, a sensitivity analysis of all parameters were conducted to elucidate the critical parameters of the model. The resulting model was fit to clinical data as a performance benchmark. The clinical data captured the second line of antiretroviral treatment, lopinavir and ritonavir. The model and clinical data correlate well for coadministration of lopinavir/ritonavir with rifampin. Drug-drug interaction was captured between lopinavir and rifampin. This article provides conclusions about the suitability of physiologically based pharmacokinetic models for the prediction of drug-drug interaction and antiretroviral and anti-TB pharmacokinetics.

Topics: Anti-Retroviral Agents; HIV; HIV Infections; Humans; Latent Tuberculosis; Lopinavir; Models, Biological; Rifampin; Ritonavir; Tuberculosis