Geometric Mean Ratios Of Cmax Research Articles

Does gender, food or grapefruit juice alter the pharmacokinetics of primaquine in healthy subjects?

To evaluate the effects of gender, food and grapefruit juice on the pharmacokinetics of primaquine in healthy subjects. In a randomized, two-phase cross-over study, 10 male and 10 female healthy Vietnamese subjects were administered 30 mg primaquine in the fasting state or with food, followed by administration of primaquine with grapefruit juice. The pharmacokinetics of primaquine were comparable between male and female subjects, with geometric mean ratios of Cmax = 0.89 [95% confidence interval (CI) 0.65, 1.22] and AUC = 0.80 (95% CI 0.56, 1.15). The mean CL/F of primaquine was slightly higher in males than in females [0.52 l h(-1) kg(-1)vs. 0.43 l h(-1) kg(-1), mean difference of 0.09 (95% CI -0.10, 0.28), P = 0.32]. When compared with fasting state values, food increased the geometric mean Cmax of primaquine by 26% (95% CI 12, 40) and the AUC by 14% (95% CI 3, 27). Similarly, grapefruit juice increased the geometric mean Cmax by 23% (95% CI 4, 45) and the AUC by 19% (95% CI 4, 37). The disposition of primaquine was comparable between genders, suggesting no need to modify the dose of primaquine for malaria treatment or prophylaxis. Food increased the oral bioavailability of primaquine, which may lead to higher antimalarial efficacy. Grapefruit juice increased the bioavailability of primaquine, with marked interindividual differences suggesting that people should not take primaquine with grapefruit juice.

PIII-80Bioequivalence study comparing carvedilol formulation from (tablet 25 mg) with a marketed reference (tablet 25 mg) in healthy volunteers

METHODS Thirty six healthy volunteers as assessed by clinical and laboratory test evaluations, were enrolled in the study. The study was a single dose, two-way randomized crossover design comparing Carvedilol tablet formulations. Plasma samples for determination of Carvedilol were obtained pre-dose and at frequent intervals for up to 36h post-dose. Carvedilol plasma concentrations were quantified by a validated method employing LC-MS-MS. The subjects were monitored throughout the study. Systolic and diastolic blood pressure and pulse rate measurement were taken pre-dose and at intervals up to 36h. Tolerance of both products was good. RESULTS The (Cmax), the (AUClast), the (AUC0–36h) and (AUCinf(observed)) were compared. Carvedilol 25 mg test tablet Cmax geometric mean ratio was 97.22%, AUClast geometric mean ratio was 95.18%, AUC0–36h geometric mean ratio was 95.25%, AUCinf geometric mean ratio was 95.13%. Carvedilol 25mg reference tablet Cmax geometric mean ratio was 97.22%, AUClast geometric mean ratio was 94.77%, AUC0–36h geometric mean ratio was 94.79%, AUCinf geometric mean ratio was 94.74%. CONCLUSION Since the 90% CI for Cmax and AUClast ratios were inside the 80–125% interval proposed by the FDA, it is concluded Carvedilol 25 mg tablet test formulation is bioequivalent to Coreg® 25 mg tablet formulation for both the rate and the extent of absorption. Clinical Pharmacology & Therapeutics (2005) 79, P81–P81; doi: 10.1016/j.clpt.2005.12.288

Impact of rosiglitazone treatment on the bioavailability of antiretroviral compounds in HIV-positive patients

The insulin-sensitizer rosiglitazone is under investigation for therapy of HIV-associated lipodystrophy syndrome (LDS). Little is known about pharmacological interactions with antiretroviral (ARV) drugs. Therapeutic drug monitoring (TDM) of ARV drugs was performed in a prospective study before and at day 28 after start of treatment with 4 mg of rosiglitazone for combined LDS. Drug levels were measured in the morning fasting, and 0.5, 1, 2, 4, 6 and 8 h after standardized drug intake. Values were log-transformed for analysis. Twelve males and six females were assessed; mean age was 50.7 years and mean CD4 cell count was 496 cells/mm(3). All patients had a viral load below 50 copies/mL, and backbone ARV therapy consisted of two or three nucleoside reverse transcriptase inhibitors in all cases. After administration of rosiglitazone, no significant differences in Cmax, Cmin and AUC were found in cases treated with efavirenz (n = 10) and lopinavir (n = 4). Mean Cmax of nevirapine (n = 4) was reduced significantly [-0.44; 95% confidence interval (CI) -0.86 to -0.01]. Furthermore, there was a consistent trend to a reduction in the geometric mean ratio (GMR) of Cmax, Cmin and AUC (GMR of Cmax 0.95; 95% CI 0.9-1.0; GMR of Cmin 0.89; 95% CI 0.65-1.13; GMR of AUC 0.96; 95% CI 0.91-1.01). Treatment with 4 mg of rosiglitazone for HIV-associated LDS is likely to reduce the bioavailability of nevirapine. Thus, routine TDM is recommended for patients treated with rosiglitazone and nevirapine. A therapy consisting of efavirenz or lopinavir seems to be without negative impact. Further studies on the interaction of rosiglitazone with ARV drugs are necessary.

Exposure measures applied to the bioequivalence of two sustained release formulations of bupropion

To examine the effect of the exposure measures C(max) (peak exposure), AUC(E) (early exposure) and AUC (total exposure) on the bioequivalence of two sustained release formulations of bupropion (i) in the fasted state and (ii), after a high fat meal. The ratio C(max)/AUC (sensitive to rate of absorption) was also evaluated. A two-formulation, two-sequence, four-period replicate design study was performed in 29 healthy men and women after an overnight fast. Similarly, a two-period study was performed in 20 healthy men and women after ingestion of a high fat breakfast. Plasma concentrations of bupropion were measured by HPLC/MS/MS and the data were analyzed (SAS PROC MIXED) by the Schuirmann-Sattersthwaite procedure (four-period study) and by the two one-sided test procedure (SAS PROC GLM) (two-period study). Standard bioequivalence limits of 80 - 125% were applied to all measures including AUC(E) and C(max)/AUC. In the fasting study, the mean plasma concentration vs. time curves from (including over the first 24 hours) following the two administrations of each formulation were similar although there was a significant difference in median t(max) between formulations. This may have contributed to a low estimate of geometric mean ratio (GMR) for AUC(E) (69%) which was judged to have failed bioequivalence. There was also rather low GMRs for Cmax (88%) and C(max)/AUC (89%) but these measure passed because the within-subject variabilities (WSV) were relatively low (19.6% and 11.2%, respectively). Total exposure (AUC(last)) met standard bioequivalence limits of 80 - 125% easily. The raw data from the two-period fed also showed differences in the shapes of the plasma concentration vs. time curves around C(max) although there was no difference in median t(max). The WSV at median t(max) was high (34%) as was the GMR (117%) for AUCE which failed, as did C(max) (GMR 112%). The WSV was very high at early time points before settling into a "plateau" at about 11%. There was no "spike" in the plasma concentration vs. time profiles up to median t(max) or beyond and therefore there was no evidence of dose dumping of the test formulation in either fasted or fed states. No bioequivalence limits have been set for AUC(E) but the application of standard BE limits of 80 to 125% meant that the fed study was clearly underpowered given the high WSV at early time points. More research is needed on the interesting concept of early exposure. The WSV is often high at median t(max) which means that standard bioequivalence limits of 80 - 125% may be inappropriate. Despite the lack of dose dumping, application of AUC(E) to the fasting study, would have resulted in failure to declare bioequivalence since the GMR for this measure was only 69.5%. Application of a 90% confidence interval to AUC(E) to the fed study would have required powering to cope with the fact that this measure was highly variable.

No clinically significant interactions between the oral direct thrombin inhibitor ximelagatran and amiodarone, atorvastatin, or digoxin

Background The oral direct thrombin inhibitor ximelagatran has shown clinical benefit in patients with atrial fibrillation at risk of stroke. The potential for interaction of ximelagatran with amiodarone, atorvastatin, or digoxin, was assessed in 3 randomized studies in healthy volunteers. Methods: Study 1 was a placebo-controlled, parallel-group study (n=26) with ximelagatran (36mg) or placebo BID for 8 days and amiodarone (single 600mg oral dose) on Day 4. Study 2 was a crossover study (n=16) with atorvastatin (single 40mg oral dose) during one treatment period and ximelagatran (36mg BID for 5 days) plus a single dose of atorvastatin (40mg) on Day 4 during the other treatment period. Study 3 was a double-blind, crossover study (n=16) with ximelagatran (36mg) or placebo BID for 8 days and digoxin (single 0.5mg dose) on Day 4. Results: For melagatran, the active form of ximelagatran, AUC and Cmax geometric mean ratios (90% CI) for combined therapy relative to monotherapy with either drug were within or only slightly outside predefined bounds for no interaction. Similarly, no relevant changes were observed for the AUC and Cmax of amiodarone, atorvastatin, or digoxin. None of the coadministered drugs affected the concentration–effect relationship of melagatran on activated partial thromboplastin time. Conclusions: No clinically significant pharmacokinetic or pharmacodynamic interactions were observed when ximelagatran was administered with amiodarone, atorvastatin, or digoxin. Clinical Pharmacology & Therapeutics (2004) 75, P78–P78; doi: 10.1016/j.clpt.2003.11.294

Effect of erythromycin on the pharmacokinetics and pharmacodynamics of the oral direct thrombin inhibitor ximelagatran and its active form melagatran

Background Ximelagatran (Exanta™, AstraZeneca), an oral direct thrombin inhibitor for the prevention and treatment of thromboembolic disorders, is rapidly absorbed and bioconverted to its active form melagatran. The metabolism of ximelagatran is independent of CYP450 enzymes and hence it has a low potential for drug interactions. This study evaluated the effect of erythromycin on the pharmacokinetics (PK) and pharmacodynamics (PD) of melagatran. Methods: An open, sequential, single-centre study in healthy volunteers (n=16; mean age 24 years, range 20–32 years) with ximelagatran 36mg on Day 1, then erythromycin 500mg TID on Days 2–5 followed by ximelagatran 36 mg plus erythromycin on Day 6. Results: For melagatran, AUC and Cmax geometric mean ratios for combined therapy (Day 6) relative to monotherapy (Day 1) were 1.82 (90% CI, 1.64–2.01) and 1.74 (90% CI, 1.52–2.00), respectively, (n=15), falling outside of the predefined bounds for no interaction. Geometric mean ratios for tmax and t1/2 of melagatran were 1.14 and 0.93, respectively. The erythromycin-associated elevation in plasma melagatran concentrations increased the peak activated partial thromboplastin time (aPTT) prolongation from 41s to 44s. Ximelagatran was well tolerated alone, and in combination with erythromycin. Conclusions: This study showed evidence of a pharmacokinetic interaction between ximelagatran and erythromycin with respect to melagatran PK, which is being investigated, but only a small effect on aPTT. Clinical Pharmacology & Therapeutics (2004) 75, P78–P78; doi: 10.1016/j.clpt.2003.11.295

Comparison of MK-0767 pharmacokinetics in Japanese and non-Japanese subjects

An analysis was performed to compare preliminary pharmacokinetics (PK) of MK-0767, a dual PPARα/γ agonist, between Japanese and non-Japanese populations after single and multiple oral doses of MK-0767. The PK data from available MK-0767 Phase I studies in a non-Japanese population (5 studies) were pooled (single dose and multiple dose studies separately) and compared to that from Phase I studies in a Japanese population (2 studies). The analysis included single doses from 1- to 10-mg and multiple doses from 0.3- to 25–mg at steady state; all subjects included in this analysis were young healthy male volunteers. An analysis of covariance (ANCOVA) model was used with a factor for population and covariates age, weight, height, and log transformed dose level. To assess the magnitude of the difference between the two populations with respect to AUC and Cmax, the geometric mean ratio (GMR) (Japanese/non-Japanese) with 90% confidence intervals (CIs) were provided based on the above ANCOVA model. Following single doses, the dose-adjusted AUC(0-∞) GMR was 0.89 with a 90% CI of (0.78, 1.02) and the dose-adjusted Cmax GMR was 1.00 with a 90% CI of (0.89, 1.12). Following multiple doses at steady state, the dose-adjusted AUC(0-24hr) GMR was 1.18 with a 90% CI of (0.99, 1.40) and the dose-adjusted Cmax GMR was 1.13 with a 90% CI of (0.95, 1.33). Based on this analysis, pharmacokinetics of MK-0767 are similar in Japanese and non-Japanese subjects. Clinical Pharmacology & Therapeutics (2004) 75, P11–P11; doi: 10.1016/j.clpt.2003.11.040

Saquinavir pharmacokinetics alone and in combination with nelfinavir in HIV-infected patients

To investigate the pharmacokinetics of saquinavir (SQV) hard gel when administered alone and in combination with nelfinavir (NLF) to HIV-positive patients. Six patients receiving triple therapy (dual nucleoside plus SQV 600 mg three times daily) were studied. On the first study day blood samples were drawn for assay of SQV. Prior to the second study day, patients received their usual medication plus NLF 750 mg three times daily for 2 days. Blood samples were obtained at times 0, 1, 2, 4, 6 and 8 h after dosing on study days 1 and 2. Following centrifugation, separated plasma was heated at 58 degrees C for at least 30 min to inactivate HIV and stored at -80 degrees C until analysis using high performance liquid chromatography. The geometric mean Cmax and AUC0-8 h on the first study day were 253 ng/ml (range, < 25-1200 ng/ml) and 1106 ng/ml.h (range, < 100-3479 ng/ml.h), respectively, and on the second study day were 1204 ng/ml (range, 379-2755 ng/ml) and 5472 ng/ml.h (range, 1434-12,538 ng/ml.h), respectively. The geometric mean ratio for Cmax was 4.75 and for AUC0-8 h was 4.94. NLF increases the oral bioavailability of SQV (hard gel) approximately fivefold. For some patients the addition of NLF to SQV will increase the drug levels from subtherapeutic to the therapeutic range. In one of our patients the addition of NLF resulted in SQV levels that were much higher than previous work suggests are necessary for maximum antiviral effect. The variability in SQV concentrations both at baseline and following addition of NLF suggest that dosing may best be adjusted by individual therapeutic drug monitoring.