Aurélie Barrail-Tran

Drug-drug interactions between HMG-CoA reductase inhibitors (statins) and antiviral protease inhibitors.

The HMG-CoA reductase inhibitors are a class of drugs also known as statins. These drugs are effective and widely prescribed for the treatment of hypercholesterolemia and prevention of cardiovascular morbidity and mortality. Seven statins are currently available: atorvastatin, fluvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin and simvastatin. Although these drugs are generally well tolerated, skeletal muscle abnormalities from myalgia to severe lethal rhabdomyolysis can occur. Factors that increase statin concentrations such as drug–drug interactions can increase the risk of these adverse events. Drug–drug interactions are dependent on statins’ pharmacokinetic profile: simvastatin, lovastatin and atorvastatin are metabolized through cytochrome P450 (CYP) 3A, while the metabolism of the other statins is independent of this CYP. All statins are substrate of organic anion transporter polypeptide 1B1, an uptake transporter expressed in hepatocyte membrane that may also explain some drug–drug interactions. Many HIV-infected patients have dyslipidemia and comorbidities that may require statin treatment. HIV-protease inhibitors (HIV PIs) are part of recommended antiretroviral treatment in combination with two reverse transcriptase inhibitors. All HIV PIs except nelfinavir are coadministered with a low dose of ritonavir, a potent CYP3A inhibitor to improve their pharmacokinetic properties. Cobicistat is a new potent CYP3A inhibitor that is combined with elvitegravir and will be combined with HIV-PIs in the future. The HCV-PIs boceprevir and telaprevir are both, to different extents, inhibitors of CYP3A. This review summarizes the pharmacokinetic properties of statins and PIs with emphasis on their metabolic pathways explaining clinically important drug–drug interactions. Simvastatin and lovastatin metabolized through CYP3A have the highest potency for drug–drug interaction with potent CYP3A inhibitors such as ritonavir- or cobicistat-boosted HIV-PI or the hepatitis C virus (HCV) PI, telaprevir or boceprevir, and therefore their coadministration is contraindicated. Atorvastatin is also a CYP3A substrate, but less potent drug–drug interactions have been reported with CYP3A inhibitors. Non-CYP3A-dependent statin concentrations are also affected although to a lesser extent when coadministered with HIV or HCV PIs, mainly through interaction with OATP1B1, and treatment should start with the lowest available statin dose. Effectiveness and occurrence of adverse effects should be monitored at regular time intervals.

Emerging integrase inhibitor resistance mutations in raltegravir-treated HIV-1-infected patients with low-level viremia.

Background:The emergence of integrase strand-transfer inhibitor (INSTI) resistance-associated mutations was examined in patients with low-level viremia after switching from enfuvirtide to raltegravir in the ANRS 138-Easier trial. Methods:Integrase genes of plasma virus from raltegravir-treated patients in the Easier trial with low-level viremia (50–500 copies/ml) were sequenced to determine INSTI resistance-associated mutations. Baseline viral load, baseline and nadir CD4 cell count, antiretroviral treatment, genotypic susceptibility score, level of viremia and degree of treatment adherence during the study period were also analyzed. Results:Forty-nine patients experienced at least one episode of low-level viremia while receiving raltegravir; integrase genotyping was successful in samples from 39 individuals (80%). Among them, three [7.7%, 95% confidence interval (CI) 1.6–20.9%] had significant INSTI resistance mutations consisting of N155H in two and P145S in one. Absence of these mutations from proviral DNA at baseline suggested selection of INSTI resistance during episodes of low-level viremia. No specific factors significantly associated with emergence of INSTI resistance mutations during low-level viremia were identified. Conclusion:Emergence of INSTI resistance mutations can occur during episodes of low-level viremia in patients receiving raltegravir-containing regimens.

Pharmacokinetics of etravirine, raltegravir and darunavir/ritonavir in treatment experienced patients.

Etravirine is an enzyme inducer and could lower the concentration of combined drugs. Ten HIV-1-infected patients with multiple treatment failure received raltegravir (400 mg, twice daily) and darunavir/ritonavir (600/100 mg, twice daily). Addition of etravirine (200 mg, twice daily) leads to a significant increase in raltegravir and darunavir trough concentrations (405 vs. 118 and 3837 vs. 2241 ng/ml) and darunavir area under the curve (AUC12h) (50 083 vs. 36 277 ng h/ml). All pharmacokinetic parameters appeared to be highly variable regardless to the addition of etravirine.

Randomised Pharmacokinetic Trial of Rifabutin with Lopinavir/Ritonavir-Antiretroviral Therapy in Patients with HIV-Associated Tuberculosis in Vietnam

Background Rifampicin and protease inhibitors are difficult to use concomitantly in patients with HIV-associated tuberculosis because of drug-drug interactions. Rifabutin has been proposed as an alternative rifamycin, but there is concern that the current recommended dose is suboptimal. The principal aim of this study was to compare bioavailability of two doses of rifabutin (150 mg three times per week and 150 mg daily) in patients with HIV-associated tuberculosis who initiated lopinavir/ritonavir-based antiretroviral therapy in Vietnam. Concentrations of lopinavir/ritonavir were also measured. Methods This was a randomized, open-label, multi-dose, two-arm, cross-over trial, conducted in Vietnamese adults with HIV-associated tuberculosis in Ho Chi Minh City (Clinical trial registry number NCT00651066). Rifabutin pharmacokinetics were evaluated before and after the introduction of lopinavir/ritonavir -based antiretroviral therapy using patient randomization lists. Serial rifabutin and 25-O-desacetyl rifabutin concentrations were measured during a dose interval after 2 weeks of rifabutin 300 mg daily, after 3 weeks of rifabutin 150 mg daily with lopinavir/ritonavir and after 3 weeks of rifabutin 150 mg three times per week with lopinavir/ritonavir. Results Sixteen and seventeen patients were respectively randomized to the two arms, and pharmacokinetic analysis carried out in 12 and 13 respectively. Rifabutin 150 mg daily with lopinavir/ritonavir was associated with a 32% mean increase in rifabutin average steady state concentration compared with rifabutin 300 mg alone. In contrast, the rifabutin average steady state concentration decreased by 44% when rifabutin was given at 150 mg three times per week with lopinavir/ritonavir. With both dosing regimens, 2 – 5 fold increases of the 25-O-desacetyl- rifabutin metabolite were observed when rifabutin was given with lopinavir/ritonavir compared with rifabutin alone. The different doses of rifabutin had no significant effect on lopinavir/ritonavir plasma concentrations. Conclusions Based on these findings, rifabutin 150 mg daily may be preferred when co-administered with lopinavir/ritonavir in patients with HIV-associated tuberculosis. Trial Registration ClinicalTrials.gov NCT00651066

Pharmacokinetics of Phase I Nevirapine Metabolites following a Single Dose and at Steady State

ABSTRACT Nevirapine is one of the most extensively prescribed antiretrovirals worldwide. The present analyses used data and specimens from two prior studies to characterize and compare plasma nevirapine phase I metabolite profiles following a single 200-mg oral dose of nevirapine in 10 HIV-negative African Americans and a steady-state 200-mg twice-daily dose in 10 HIV-infected Cambodians. Nevirapine was assayed by high-performance liquid chromatography (HPLC). The 2-, 3-, 8- and 12-hydroxy and 4-carboxy metabolites of nevirapine were assayed by liquid chromatography-tandem mass spectrometry (LC/MS/MS). Pharmacokinetic parameters were calculated by noncompartmental analysis. The metabolic index for each metabolite was defined as the ratio of the metabolite area under the concentration-time curve (AUC) to the nevirapine AUC. Every metabolite concentration was much less than the corresponding nevirapine concentration. The predominant metabolite after single dose and at steady state was 12-hydroxynevirapine. From single dose to steady state, the metabolic index increased for 3-hydroxynevirapine (P < 0.01) but decreased for 2-hydroxynevirapine (P < 0.001). The 3-hydroxynevirapine metabolic index was correlated with nevirapine apparent clearance (P < 0.001). These findings are consistent with induction of CYP2B6 (3-hydroxy metabolite) and a possible inhibition of CYP3A (2-hydroxy metabolite), although these are preliminary data. There were no such changes in metabolic indexes for 12-hydroxynevirapine or 4-carboxynevirapine. Two subjects with the CYP2B6 *6*6 genetic polymorphism had metabolic indexes in the same range as other subjects. These results suggest that nevirapine metabolite profiles change over time under the influence of enzyme induction, enzyme inhibition, and host genetics. Further work is warranted to elucidate nevirapine biotransformation pathways and implications for drug efficacy and toxicity.

Switch from Enfuvirtide to Raltegravir Lowers Plasma Concentrations of Darunavir and Tipranavir: a Pharmacokinetic Substudy of the EASIER-ANRS 138 Trial

ABSTRACT We compared tipranavir and darunavir concentrations measured at steady state in 20 human immunodeficiency virus (HIV)-infected patients enrolled in the EASIER-ANRS 138 clinical trial who switched from enfuvirtide to raltegravir while maintaining the same background regimen. The geometric mean ratios of the observed predose concentration (Ctrough), maximum concentration of drug observed in plasma (Cmax), and area under the plasma concentration-time curve (AUC) before (day 0) and after (week 24) the switch were 0.49, 0.76, and 0.67 and 0.82, 0.68, and 0.64 for tipranavir and darunavir, respectively. The virologic consequences of these drug interactions have yet to be determined.

Population pharmacokinetics of mycophenolic acid and dose optimization with limited sampling strategy in liver transplant children

AIMS The aims were to estimate the mycophenolic acid (MPA) population pharmacokinetic parameters in paediatric liver transplant recipients, to identify the factors affecting MPA pharmacokinetics and to develop a limited sampling strategy to estimate individual MPA AUC(0,12 h). METHODS Twenty-eight children, 1.1 to 18.0 years old, received oral mycophenolate mofetil (MMF) therapy combined with either tacrolimus (n= 23) or ciclosporin (n= 5). The population parameters were estimated from a model-building set of 16 intensive pharmacokinetic datasets obtained from 16 children. The data were analyzed by nonlinear mixed effect modelling, using a one compartment model with first order absorption and first order elimination and random effects on the absorption rate (k(a)), the apparent volume of distribution (V/F) and apparent clearance (CL/F). RESULTS Two covariates, time since transplantation (≤ and >6 months) and age affected MPA pharmacokinetics. k(a), estimated at 1.7 h(-1) at age 8.7 years, exhibited large interindividual variability (308%). V/F, estimated at 64.7 l, increased about 2.3 times in children during the immediate post transplantation period. This increase was due to the increase in the unbound MPA fraction caused by the low albumin concentration. CL/F was estimated at 12.7 l h(-1). To estimate individual AUC(0,12 h), the pharmacokinetic parameters obtained with the final model, including covariates, were coded in Adapt II(®) software, using the Bayesian approach. The AUC(0,12 h) estimated from concentrations measured 0, 1 and 4 h after administration of MMF did not differ from reference values. CONCLUSIONS This study allowed the estimation of the population pharmacokinetic MPA parameters. A simple sampling procedure is suggested to help to optimize pediatric patient care.

Optimization of the dosing regimen of mycophenolate mofetil in pediatric liver transplant recipients.

Mycophenolate mofetil (MMF) is now commonly used in pediatric liver transplant recipients, but no clear recommendations about the dosing regimen have been made for this population. The aim of this study was to determine the MMF dosage required for pediatric liver transplant recipients to achieve an area under the plasma concentration–time curve from 0 to 12 hours (AUC0‐12) for mycophenolic acid (MPA) greater than 30 mg hour/L. A pharmacokinetic study of 15 children (median age = 8.3 years, range = 1.1‐15.2 years) was performed at a median of 11.0 months (range = 0.5‐88.0 months) after liver transplantation. MMF was initially introduced at a median starting dose of 300 mg/m2 twice a day (range = 186‐554 mg/m2 twice a day). Thirteen of the 15 patients had an MPA AUC0‐12 value less than 30 mg hour/L. The MMF dosage had to be increased in all patients except 1. The MMF dosage required to reach an MPA AUC0‐12 value greater than the defined target of 30 mg hour/L ranged from 371 to 1014 mg/m2/day. For 2 patients who received rifampin in addition to MMF, the MPA AUC0‐12 value remained low despite a 2‐fold increase in the MMF dosage. In conclusion, an initial MMF dose of 600 mg/m2 twice a day led to MPA AUC0‐12 values greater than the 30 mg hour/L threshold except when rifampin was coadministered. Because of the important interindividual variability of MPA pharmacokinetics, therapeutic drug monitoring is recommended for optimizing the daily MMF dosage. Furthermore, these results suggest that the coadministration of MPA with rifampin should be avoided. Liver Transpl 17:1152–1158, 2011.

Quantification of raltegravir (MK0518) in human plasma by high-performance liquid chromatography with photodiode array detection

A precise and accurate high-performance liquid chromatography (HPLC) method with photodiode array detection has been developed and validated for raltegravir, a human immunodeficiency virus integrase strand transfer inhibitor (HIV-1 INSTI). Plasma (300 microL) was extracted with dichloromethane/hexane 50:50 (v/v) after addition of the internal standard, 6,7-dimethyl-2,3-di(2-pyridyl) quinoxaline. The compounds were separated using a dC18 column and detected with ultraviolet detection at 320 nm. The limit of quantification was 10 ng/mL for raltegravir. The method was linear and validated over a concentration range of 0-10,000 ng/mL. The intra-day precision ranged from 3.1 to 12.3%, while the intra-day accuracy ranged from -15.0 to -0.5%, the inter-day precision and accuracy were less than 7%. The mean recovery was 76.8%. Application to clinical samples taken from patients treated with raltegravir indicated that the method is suitable for measuring plasma concentrations of raltegravir in pharmacokinetic studies of clinical trials.

Predictive Values of the Human Immunodeficiency Virus Phenotype and Genotype and of Amprenavir and Lopinavir Inhibitory Quotients in Heavily Pretreated Patients on a Ritonavir-Boosted Dual-Protease-Inhibitor Regimen

ABSTRACT The inhibitory quotient (IQ) of human immunodeficiency virus (HIV) protease inhibitors (PIs), which is the ratio of drug concentration to viral susceptibility, is considered to be predictive of the virological response. We used several approaches to calculate the IQs of amprenavir and lopinavir in a subset of heavily pretreated patients participating in the French National Agency for AIDS Research (ANRS) 104 trial and then compared their potentials for predicting changes in the plasma HIV RNA level. Thirty-seven patients were randomly assigned to receive either amprenavir (600 mg twice a day [BID]) or lopinavir (400 mg BID) plus ritonavir (100 or 200 mg BID) for 2 weeks before combining the two PIs. The 90% inhibitory concentration (IC90) was measured using a recombinant assay without or with additional human serum (IC90+serum). Total and unbound PI concentrations in plasma were measured. Univariate linear regression was used to estimate the relation between the change in viral load and the IC90 or IQ values. The amprenavir phenotypic IQ values were very similar when measured with the standard and protein binding-adjusted IC90s. No relationship was found between the viral load decline and the lopinavir IQ. During combination therapy, the amprenavir and lopinavir genotypic IQ values were predictive of the viral response at week 6 (P = 0.03). The number of protease mutations (<5 or ≥5) was related to the virological response throughout the study. These findings suggest that the combined genotypic IQ and the number of protease mutations are the best predictors of virological response. High amprenavir and lopinavir concentrations in these patients might explain why plasma concentrations and the phenotypic IQ have poor predictive value.