Biomedical subjects

Susan L Rosenkranz

Publications and source records attributed to Susan L Rosenkranz.

10 recordsLinked to original sources

PubMed2006

The impact of sex and contraceptive therapy on the plasma and intracellular pharmacokinetics of zidovudine.

OBJECTIVES: Zidovudine remains part of combination antiretroviral therapy. Pharmacological studies rely on quantitation of active triphosphates in peripheral blood mononuclear cells. This study evaluated the impact of female sex and contraceptive therapy on zidovudine plasma and intracellular pharmacokinetics and the impact of contraceptive therapy on HIV viral load. METHODS: Serial plasma and intracellular zidovudine pharmacokinetics following oral and intravenous dosing were determined in 18 men and 20 women treated with zidovudine. Women could repeat pharmacokinetics assessment following 2 months oral or injectable contraceptive therapy. Zidovudine plasma and intracellular mono-, di- and triphosphate concentrations were determined by liquid chromatography tandem mass spectrometry. Plasma and cervical viral loads were determined preceding and following 2 months of contraceptive therapy in women. RESULTS: Men exhibited higher area under the concentration versus time curve for intracellular zidovudine and zidovudine-monophosphate following oral and intravenous dosing and higher zidovudine triphosphate following oral dosing. There was no difference between men and women in plasma zidovudine parameters. Furthermore, contraceptive therapy had no effect on zidovudine plasma or intracellular pharmacokinetics or on plasma or cervical HIV-1 RNA levels. CONCLUSIONS: Using an optimized pharmacokinetic design, this study indicated men exhibit significantly higher zidovudine-monophosphate and zidovudine-triphosphate exposure following zidovudine oral administration, having implications for drug toxicity and overall tolerance of zidovudine therapy. The lack of an effect of contraceptive therapy on zidovudine pharmacokinetics is surprising in light of previous pharmacokinetic studies for drugs eliminated primarily through glucuronidation. Contraceptive therapy had no effect on plasma or cervical viral load, results consistent with previous findings.

Administration, Oral↗

PubMed2006

Pharmacodynamics of antiretroviral agents in HIV-1 infected patients: using viral dynamic models that incorporate drug susceptibility and adherence.

We developed a novel HIV-1 dynamic model with consideration of pharmacokinetics, drug adherence and drug susceptibility to link plasma drug concentration to the long-term changes in HIV-1 RNA observation after initiation of therapy. A Bayesian approach is proposed to fit this model to clinical data from ACTG A5055, a study of two dosage regimens of indinavir (IDV) with ritonavir (RTV) in subjects failing their first protease inhibitor treatment. The HIV RNA testing was completed at days 0, 7, 14, 28, 56, 84, 112, 140, and 168. An intensive pharmacokinetic (PK) evaluation was performed on day 14 and multiple trough concentrations were subsequently collected. Pill counts were used to monitor adherence. IC(50) for IDV and RTV were determined at baseline and at virologic failure. Viral dynamic model fitting residuals were used to assess the significance of covariate effects on long-term virologic response. As univariate predictors, none of the four PK parameters C(trough), C(12 hour), C(max), and AUC was significantly related to virologic response (p > 0.05). By including drug susceptibility (IC(50)), or IC(50) and adherence measured by pill counts together, C(trough), C(12 hour), C(max) and AUC were each significantly correlated to long-term virologic response (p = 0.0055,0.0002,0.0136,0.0002 with IC(50) and adherence measured by pill counts considered). The IC(50) and adherence measured by pill counts alone were not related to the virologic response. In predicting virologic response adherence measured by pill counts did not provide any additional information to PK parameters (p = 0.064), to drug susceptibility IC(50) (p = 0.086), and to their combination (p = 0.22). Simple regression approaches did not detect any significant pharmacodynamic (PD) relationships. Any single factor of PK, adherence measured by pill counts and drug susceptibility did not contribute to long-term virologic response. But their combinations in viral dynamic modeling significantly predicted virologic response. The HIV dynamic modeling can appropriately capture complicated nonlinear relationships and interactions among multiple covariates.

Algorithms↗

PubMed2006

Pharmacokinetic interaction between nelfinavir and pravastatin in HIV-seronegative volunteers: ACTG Study A5108.

BACKGROUND: Nelfinavir, an HIV protease inhibitor with numerous drug-drug interactions, is associated with dyslipidemia. Pravastatin is the preferred statin prescribed for HIV-associated dyslipidemia. OBJECTIVE: To examine the effect of nelfinavir on pravastatin pharmacokinetics. DESIGN: Open-label study in healthy HIV-seronegative adults conducted at the AIDS Clinical Trials Group sites in the United States. METHODS: Subjects received pravastatin 40 mg daily and underwent intensive sampling for pharmacokinetics on day 3. Subjects took only nelfinavir 1250 mg twice daily on days 4-12. On days 13-15, subjects continued nelfinavir and reinitiated pravastatin. Plasma samples were collected over 24 h for the calculation of pravastatin area under the concentration-time curve for 0-24 h on days 3 and 16. RESULTS: Data from 14 subjects with complete pharmacokinetic samples were available for analysis. The median within-subject percentage change in pravastatin AUC was a decrease of 46.5%. Pravastatin maximum plasma concentrations were also lower when pravastatin was administered with nelfinavir. Median values for the maximum plasma concentrations were 27.9 and 12.4 ng/ml for days 3 and 16, respectively, and the median within-subject decrease was 40.1%. CONCLUSIONS: Coadministration of pravastatin and nelfinavir led to a substantial reduction in pravastatin plasma concentrations. Higher doses of pravastatin may need to be prescribed in order to achieve optimal lipid-lowering activity.

Adult↗

PubMed2005

Modeling long-term HIV dynamics and antiretroviral response: effects of drug potency, pharmacokinetics, adherence, and drug resistance.

We propose a long-term HIV-1 dynamic model by considering drug potency, drug exposure, and drug susceptibility. Using a Bayesian approach, HIV-1 dynamic parameters were estimated by fitting the model to viral load data from a phase 1/2 randomized clinical study of 2 indinavir (IDV)/ritonavir (RTV)-containing highly active antiretroviral (ARV) therapy regimens in HIV-infected subjects who had previously failed protease inhibitor-containing ARV therapies. A large between-subject variation in estimated viral dynamic parameters was observed, even after accounting for variations in drug exposure and drug susceptibility, suggesting that characteristics of HIV-1 dynamics are host dependent. Significant correlations of baseline factors such as HIV-1 RNA levels and CD4 cell counts with viral dynamic parameters were found. These correlations coincide with biologic interaction mechanisms between HIV and the host immune system and also provide an explanation for the correlations between the baseline viral load and phase 1 viral decay rate, for which inconsistent results have been reported in the literature. The relations between viral dynamic parameters and virologic response were established, and these results suggest that viral dynamic parameters may play an important role in determining treatment success or failure. In particular, we estimated a drug efficacy threshold for each patient that can be used to assess whether an ARV regimen is potent enough to suppress HIV viruses in the individual patient. Our findings indicate that it is necessary to individualize the ARV regimen to treat HIV-1-infected patients. The proposed mathematic models and statistical techniques may provide a framework to simulate and predict antiviral response for individual patients.

Anti-HIV Agents↗

PubMed2005

Effect of efavirenz on the pharmacokinetics of simvastatin, atorvastatin, and pravastatin: results of AIDS Clinical Trials Group 5108 Study.

Efavirenz (EFV) is associated with hyperlipidemia when used in combination with other antiretroviral drugs. EFV is a mixed inducer/inhibitor of cytochrome P450 (CYP) 3A4 isozyme and may interact with hydroxymethylglutaryl coenzyme A (HMG-CoA) reductase inhibitors that are primarily metabolized via CYP3A4. To assess the drug-drug interaction of EFV used in combination with simvastatin (SIM), atorvastatin (ATR), or pravastatin (PRA), an open-label trial was conducted in 52 healthy adult HIV-seronegative subjects across AIDS Clinical Trials Group sites in the United States. Subjects received 40 mg of SIM, 10 mg of ATR, or 40 mg of PRA daily on days 0 through 3 and days 15 through 18. EFV was administered daily at a dose of 600 mg on days 4 through 18. SIM, ATR, and PRA concentrations were determined before and after EFV, and EFV concentrations were determined before and after statins. EFV reduced SIM acid exposure (area under the curve at 0 to 24 hours [AUC0-24 h]) by 58% (Wilcoxon signed rank test, P=0.003) and active HMG-CoA reductase inhibitory activity by 60% (P<0.001). EFV reduced ATR exposure by 43% (P<0.001) and the total active ATR exposure by 34% (P=0.005). EFV administration resulted in a 40% decrease in PRA exposure (P=0.005). SIM, ATR, and PRA had no effect on non-steady-state EFV concentrations. In conclusion, EFV, when administered with SIM, ATR, or PRA, can result in significant induction of statin metabolism. The reduced inhibition of HMG-CoA reductase activity during coadministration of EFV may result in diminished antilipid efficacy at usual doses of SIM, ATR, and PRA.

Adult↗

PubMed2003

Effect of simultaneous versus staggered dosing on pharmacokinetic interactions of protease inhibitors.

OBJECTIVE: The aim of this study was to determine whether pharmacokinetic interactions between the protease inhibitors saquinavir soft gel, nelfinavir, and ritonavir are affected by the timing of administration. STUDY DESIGN: We used an open-label, 6-period, incomplete Latin square crossover study in 18 human immunodeficiency virus-negative subjects. Each received single oral doses of 2 of the 3 protease inhibitors during each of 6 periods. Single doses were given either simultaneously or separated by 4 hours. The order of the periods was balanced, and periods were separated by 2 days. We measured protease inhibitor concentrations over a 24-hour period by HPLC and estimated pharmacokinetic parameters by noncompartmental methods. RESULTS: Median saquinavir area under the curve (AUC) increased by 62-fold when ritonavir was coadministered, by 50-fold when ritonavir was given 4 hours earlier, and by 16-fold when saquinavir preceded ritonavir by 4 hours. Saquinavir AUC increased by 7-fold when nelfinavir was coadministered. Nelfinavir AUC increased by 2.5-fold with coadministration of ritonavir and by 1.8- and 2.1-fold when ritonavir was administered before nelfinavir and after nelfinavir, respectively. Ritonavir AUCs were unaffected by coadministration of the other drugs. The effect of ritonavir on the kinetics of saquinavir persisted for at least 48 hours after a single dose of ritonavir, suggesting the possibility of metabolic intermediates that form inhibitory complexes. CONCLUSION: Except for saquinavir followed by ritonavir, there is little difference in protease inhibitor exposure for simultaneous or staggered doses. The persistent effect of ritonavir suggests the possibility that lower doses and longer dosing intervals might be effective when ritonavir is used to boost concentrations of other protease inhibitors.

Adult↗

PubMed2003

Modeling HIV dynamics and antiviral response with consideration of time-varying drug exposures, adherence and phenotypic sensitivity.

Highly active antiretroviral therapies consisting of reverse transcriptase inhibitor drugs and protease inhibitor drugs, which can rapidly suppress HIV below the limit of detection, are currently the most effective treatment for HIV infected patients. In spite of this, many patients fail to achieve viral suppression, probably due to existing or developing drug resistance, poor adherence, pharmacokinetic problems and other clinical factors. In this paper, we develop a viral dynamic model to evaluate how time-varying drug exposure and drug susceptibility affect antiviral response. Plasma concentrations, in turn, are modeled using a standard pharmacokinetic (PK) one-compartment open model with first order absorption and elimination as a function of fixed individual PK parameters and dose times. Imperfect adherence is considered as missed doses in PK models. We discuss the analytic properties of the viral dynamic model and study how time-varying treatment efficacies affect antiviral responses, specifically viral load and T cell counts. The relationship between actual failure time (the time at which the viral growth rate changes from negative to positive) and detectable failure time (the time at which viral load rebounds to above the limit of detection) is investigated. We find that an approximately linear relationship can be used to estimate the actual rebound failure time from the detectable rebound failure time. In addition, the effect of adherence on antiviral response is studied. In particular, we examine how different patterns of adherence affect antiviral response. Results suggest that longer sequences of missed doses increase the chance of treatment failure and accelerate the failure. Simulation experiments are presented to illustrate the relationship between antiviral response and pharmacokinetics, time-varying adherence and drug resistance. The proposed models and methods may be useful in AIDS clinical trial simulations.

Anti-HIV Agents↗

PubMed2002

Pharmacokinetic interactions between protease inhibitors and statins in HIV seronegative volunteers: ACTG Study A5047.

OBJECTIVE: Lipid lowering therapy is used increasingly in persons with HIV infection in the absence of safety data or information on drug interactions with antiretroviral agents. The primary objectives of this study were to examine the effects of ritonavir (RTV) plus saquinavir soft-gel (SQVsgc) capsules on the pharmacokinetics of pravastatin, simvastatin, and atorvastatin, and the effect of pravastatin on the pharmacokinetics of nelfinavir (NFV) in order to determine clinically important drug-drug interactions. DESIGN: Randomized, open-label study in healthy, HIV seronegative adults at AIDS Clinical Trials Units across the USA. METHODS: Three groups of subjects (arms 1, 2, and 3) received pravastatin, simvastatin or atorvastatin (40 mg daily each) from days 1-4 and 15-18. In these groups, RTV 400 mg and SQVsgc 400 mg twice daily were given from days 4-18. A fourth group (arm 4) received NFV 1250 mg twice daily from days 1-14 with pravastatin 40 mg daily added from days 15-18. Statin and NFV levels were measured by liquid chromatography/tandem mass spectrometry. RESULTS: Fifty-six subjects completed both pharmacokinetic study days. In arms 1-3, the median estimated area under the curves (AUC)(0-24) for the statins were: pravastatin (arm 1, n = 13), 151 and 75 ng.h/ml on days 4 and 18 (decline of 50% in presence of RTV/SQVsgc), respectively (P = 0.005); simvastatin (arm 2, n = 14), 17 and 548 ng.h/ml on days 4 and 18 (increase of 3059% in the presence of RTV/SQVsgc), respectively (P < 0.001); and total active atorvastatin (arm 3, n = 14), 167 and 289 ng.h/ml on days 4 and 18 (increase of 79% in the presence of RTV/SQVsgc), respectively (P < 0.001). In arm 4, the median estimated AUC(0-8) for NFV (24 319 versus 26 760 ng.h/ml; P = 0.58) and its active M8 metabolite (15 565 versus 14 571 ng.h/m; P = 0.63) were not statistically different from day 14 to day 18 (without or with pravastatin). CONCLUSIONS: Simvastatin should be avoided and atorvastatin may be used with caution in persons taking RTV and SQVsgc. Dose adjustment of pravastatin may be necessary with concomitant use of RTV and SQVsgc. Pravastatin does not alter the NFV pharmacokinetics, and thus appears to be safe for concomitant use.

Adult↗

PubMed2002

Model-based analysis of the pharmacokinetic interactions between ritonavir, nelfinavir, and saquinavir after simultaneous and staggered oral administration.

Eighteen healthy human immunodeficiency virus-negative subjects participated in an open-label, six-period, incomplete Latin-square crossover pharmacokinetic study. Each subject received two of the three possible pair-wise combinations of single-dose oral ritonavir (R) (400 mg), nelfinavir (N) (750 mg), and saquinavir (S) (800 mg), each pair on three occasions (simultaneous or staggered administration), each occasion at least 2 days after the last. A model-based analysis reveals the following major drug interactions under the conditions of this study: 1). R given simultaneously with S decreases S hepatic intrinsic clearance almost 50-fold relative to that predicted for S given alone and increases its gut bioavailability 90% (but decreases its rate of absorption 40%) relative to when N is given simultaneously; 2). N given simultaneously with S decreases S hepatic intrinsic clearance 10-fold relative to that predicted for S given alone; and 3) R inhibits S hepatic intrinsic clearance even after R plasma levels have become undetectable (>48 h after dosing), implying that R, when used as a pharmacokinetic enhancer, can be dosed less frequently than might be predicted from the duration of detectable systemic concentrations.

Administration, Oral↗

PubMedDate not supplied

Tutorial reduces protocol deviations in multicenter ACTG trials with pharmacology endpoints.

PURPOSE: The AIDS Clinical Trials Group (ACTG) pharmacology quality assurance program requires clinical research staff to demonstrate minimum competencies in clinical pharmacology research. To achieve this goal, a tutorial was designed to improve the accuracy and completeness of data collected in ACTG pharmacology protocols. METHOD: Clinical research staff at AIDS Clinical Trials Units (ACTUs) access the tutorial through the network's Website. The tutorial presents pharmacokinetic study concepts by contrasting poor with perfect study conduct to illustrate the influence of data quality on conclusions. Case report forms and laboratory data were audited retrospectively to examine the pre- and posttutorial incidence of targeted errors. RESULTS: During a 2-year period, 236 study nurses at 64 main and subunit ACTUs completed the tutorial. The percentage of visits with dosing and/or sampling errors dropped from 13% to 4%. The percentage of samples with errors decreased from 6% to 3%. Sample-time errors (blood drawn outside of the 15-minute target time) decreased slightly, from 2.9% to 2.4%, but the discrepancies found in the recording of sample times decreased from 3% to <1%. CONCLUSION: The ACTG clinical pharmacology tutorial program improved accuracy of both protocol conduct and data collection for pharmacology objectives.

Acquired Immunodeficiency Syndrome↗