Estimation of the area under the curve for mycophenolic acid in adult renal transplant patients with concomitant tacrolimus using a limited sampling strategy

Objectives: The aim of this study was to develop a limited sampling strategy (LSS) for monitoring the use of mycophenolic acid (MPA) in maintenance therapy with tacrolimus (TCL) in renal transplant patients. Methods: Eighteen adult patients receiving a first transplant were investigated. All patients were treated with a combination of TCL, steroid and mycophenolate mofetil (MMF). Besides the predose trough concentration (C₀), whole blood samples were taken for measurement of the MPA concentration at 0·5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12 h for a 14‐point 12‐h pharmacokinetic (PK) profile. Using stepwise linear regression analysis, an abbreviated area under the concentration time curve (AUC) was calculated using all 14, and any combination of sampling points to give an estimating equation with up to three predictors. Results: The equation derived from C₂, C₇ and C_12, for AUC estimation: AUC = (2·05 × C₂) + (8·51 ×C₇) + (2·29 × C₁₂) + 4·24. was found to be optimal. Using this formula, there was an excellent correlation between the estimated 3‐point AUC and AUC_{0–12 h}. To assess the agreement between the abbreviated methods and the full PK profile, we plotted the average AUC of the abbreviated estimates and the full PK profile. This Bland‐Altman analysis indicated good agreement to within ±2 SD and a prediction variability of 7·56 μg × h/mL. Conclusion: Our proposed three‐sampling‐point estimate of AUCs is clinically acceptable. However, the sampling times are inconvenient for outpatients, and is recommended only for monitoring MMF treatment of inpatients with suspected toxicity or at high risk of organ rejection.     

No pharmacokinetic interactions between mycophenolic acid and tacrolimus in renal transplant recipients

Objective:  The aim of this study was to investigate drug interactions between mycophenolic acid (MPA), the active metabolite of mycophenolate mofetil (MMF) and tacrolimus, as well as the impact of CYP3A5 and UGT2B7 genetic polymorphisms on these drug interactions in 71 Japanese renal transplant recipients. Methods:  Recipients received combination immunosuppressive therapy consisting of tacrolimus and MMF. On day 28 after transplantation, the concentrations of MPA and tacrolimus were measured by high‐performance liquid chromatography and microparticle enzyme immunoassay respectively. Results:  Acute rejection was over twice more common in recipients with a total area under the observed plasma concentration‐time curve (AUC_0–12) of MPA <70 μg·h/mL than in those with higher values AUC_0–12 values (17% vs. 7%).Using this cut‐off AUC value, sensitivity was 70·6% and specificity 55·6% for acute rejection (AR). There was no change in AUC_0–12, maximum plasma concentration, trough plasma concentration, or oral clearance of tacrolimus with variation in dosage or AUC of MPA. There were also no significant differences in the MPA pharmacokinetic parameters among three tacrolimus C₀ groups: 5 ≤ C₀ < 10, 10 ≤ C₀ < 15 and 15 ≤C₀ < 20 ng/mL. Furthermore, there were no significant differences in MPA pharmacokinetic parameters between the UGT2B7*1/*1 and *1/*2 genotype groups having the CYP3A5*1 allele or the CYP3A5*3/*3 genotype. Conclusion:  Therapeutic dosages of MMF, do not significantly influence tacrolimus pharmacokinetics, and vice versa. Consequently, MPA and tacrolimus can be safely combined; however, it is necessary to monitor the plasma concentrations of each immunosuppressive agent to minimize acute rejection.     

Effect of telmisartan, valsartan and candesartan on mycophenolate mofetil pharmacokinetics in Japanese renal transplant recipients

Objective: The aim of this study was to elucidate the effect of the peroxisome proliferator‐activated receptor‐γ (PPAR‐γ) activating angiotensin receptor blocker (ARB) telmisartan and the non‐PPAR‐γ activating ARB valsartan and candesartan on mycophenolic acid (MPA) pharmacokinetics in renal transplant recipients. Methods: Recipients (n = 10 each group) were randomly given either 40 mg of telmisartan, 80 mg of valsartan or 8 mg of candesartan cilexetil for at least 6 months, and no ARB. Blood was sampled a year after transplantation. Results: Dose‐adjusted maximum and trough plasma concentration of MPA co‐administered with telmisartan were the lowest in all groups. The mean dose‐adjusted area under the concentration curve from 0 to 12 h (AUC_0–12) and AUC_0–6 of MPA co‐administered with telmisartan were significantly lower than that without ARB (98 vs. 138 ng·h/mL/mg, P = 0·0353 and 63 vs. 96 ng·h/mL/mg, P = 0·0305). Coadministration of valsartan and candesartan did not alter MPA pharmacokinetics. The AUC ratio of MPA glucuronide (MPAG)/MPA co‐administered with telmisartan was higher than that without ARBs, but not significantly (14·2 vs. 9·1). The mean maximum and minimum plasma concentrations of telmisartan (40 mg) after oral administration were 84 and 15 ng/mL, respectively, and that of valsartan (80 mg) 2220 and 441 ng/mL, respectively. Plasma concentrations of candesartan in most transplant patients were not observed 19 h after oral administration of candesartan cilexeil (8 mg). Conclusions: The degree of drug interaction between MPA and telmisartan was significantly greater than that between MPA and valsartan or candesartan. Uridine diphosphate‐glucuronosyltransferase (UGT) 1A9 has been identified as a PPAR‐γ target gene. UGT induction by telmisartan might stimulate MPA glucuronidation. A combination of telmisartan and mycophenolate mofetil might require periodic monitoring of MPA.     

Pharmacokinetics and Tolerability of Budesonide/Glycopyrronium/Formoterol Fumarate Dihydrate and Glycopyrronium/Formoterol Fumarate Dihydrate Metered Dose Inhalers in Healthy Chinese Adults: A Randomized,Double-blind,Parallel-group Study

PurposeThe objective of this study was to assess pharmacokinetic (PK) and safety profiles of 2 fixed-dose combinations in development for the treatment of chronic obstructive pulmonary disease (COPD): budesonide/glycopyrronium/formoterol fumarate dihydrate metered-dose inhaler (BGF MDI; triple combination) and glycopyrronium/formoterol fumarate dihydrate (GFF MDI; dual combination). The PK and safety profiles of BGF MDI and GFF MDI were assessed for the first time in healthy Chinese adults after single and repeated (7-day) dosing.MethodsThis Phase I, randomized, double-blind, parallel-group study was conducted at a single site in Shanghai, China. Male or female Chinese subjects, 18–45 years of age and in good general health, were randomized 1:1:1 to receive BGF MDI 320/14.4/10 μg, BGF MDI 160/14.4/10 μg, or GFF MDI 14.4/10 μg. PK parameters were assessed after a single dose (day 1) and at steady state (day 8), and included AUC_0–12, C_max, and T_max. Tolerability was assessed using physical examination findings, adverse events reporting, 12-lead ECG, vital signs, and clinical laboratory values.FindingsNinety-six subjects (mean age, 25.6 years; 83.3% male) were randomized and received treatment. All randomized subjects were included in the safety and PK populations. After single and repeated dosing, budesonide AUC_0–12 and C_max were increased dose proportionally from BGF MDI 160/14.4/10 μg to BGF MDI 320/14.4/10 μg, respectively (single dose: AUC_0–12, 811.8 vs 1748 h · pg/mL; C_max, 224.3 vs 459.3 pg/mL; repeated dosing: AUC_0–12, 1250 vs 2510 h · pg/mL; C_max, 315.4 vs 626.4 pg/mL). After single and repeated dosing, glycopyrronium AUC_0–12 and C_max were similar across all treatments (single dose: AUC_0–12, 27.20–29.40 h · pg/mL; C_max, 4.884–5.674 pg/mL; repeated dosing: AUC_0–12, 69.49–77.08 h · pg/mL; C_max, 11.30–13.12 pg/mL) and formoterol (single dose: AUC_0–12, 46.49–53.58 h · pg/mL; C_max 9.651–10.62 pg/mL; repeated dosing: AUC_0–12, 81.94–85.32 h · pg/mL; C_max, 16.13–17.71 pg/mL), suggesting that the addition of budesonide did not appreciably alter the PK properties of GFF MDI. All treatment-emergent adverse events were mild in severity and rates were similar across groups (range, 50.0%–56.3%). There were no new or unexpected findings on tolerability.ImplicationsOverall, all treatments were well tolerated and PK parameters were generally comparable to those previously reported in Western and Japanese healthy subjects, suggesting that the doses of BGF MDI and GFF MDI in development globally for COPD are also appropriate for Chinese patients with COPD. ClinicalTrials.gov identifier: NCT03075267.     

Pharmacogenetic determinants for interindividual difference of tacrolimus pharmacokinetics 1 year after renal transplantation

What is known and objective: Tacrolimus, a widely used immunosuppressive agent in organ transplantation, has a narrow therapeutic window. It has been suggested that its interaction with lansoprazole could be dependent on polymorphisms of CYP3A5 and CYP2C19. The objective of this study was to investigate how, 1 year after renal transplantation, CYP3A5 and CYP2C19 polymorphisms, biochemical parameters and coadministration with lansoprazole, influenced tacrolimus pharmacokinetics. Methods: The pharmacokinetics of tacrolimus was studied 1 year after renal transplantation, in 75 recipients who were all receiving continuation treatment with 12‐hourly oral tacrolimus, and 30 mg lansoprazole daily (Group 1; n = 20) or, 10 mg rabeprazole daily or no proton pump inhibitor (Group 2; n = 55). Results: There were no significant differences in the dose‐adjusted area under the plasma concentration–time curve (AUC_0–12) and maximum plasma concentration (C_max) of tacrolimus between CYP2C19 genotype groups, but there were significant differences between CYP3A5 genotypes groups (*1/*1 + *1/*3 vs. *3/*3 = 45·2 ± 20·0 vs. 71·0 ± 34·1 ng·h/mL/mg, P < 0·0001 and 6·3 ± 2·6 vs. 9·3 ± 7·0 ng/mL/mg, P = 0·0017, respectively) and between co‐administration with and without lansoprazole (74·5 ± 34·0 vs. 52·4 ± 27·4 ng·h/mL/mg, P = 0·0054 and 10·9 ± 8·8 vs. 6·7 ± 3·0 ng/mL/mg, P = 0·0024, respectively). In a multiple regression analysis, the dose‐adjusted AUC_0–12 and C_max of tacrolimus were associated with CYP3A5*3/*3 and co‐administration with lansoprazole. What is new and conclusion: CYP2C19 does not seem to contribute to the interaction between tacrolimus and lansoprazole. The long‐term combination of tacrolimus and lansoprazole requires careful monitoring of patients with the CYP3A5*3/*3 genotype.     

Pharmacokinetics and pharmacodynamics profiles of enteric‐coated mycophenolate sodium in female patients with difficult‐to‐treat lupus nephritis

Relapsed or resistant lupus nephritis (LN) is considered a difficult‐to‐treat type of LN, and enteric‐coated mycophenolate sodium (EC‐MPS) has been used in this condition. Therapeutic drug monitoring using the area under the plasma mycophenolic acid concentration from 0 to 12 h postdose (MPA‐AUC_0–12h) ≥45 μg.h/ml is a useful approach to achieve the highest efficiency. This study assessed EC‐MPS’s pharmacokinetic (PK) and pharmacodynamic (PD) profiles and investigated an optimal level of the single time point of plasma MPA concentration. Nineteen biopsy‐proven patients with class III/IV LN received 1440 mg/day of EC‐MPS for 24 weeks. PK (maximum plasma MPA concentration [C _max], time to C _max, and MPA‐AUC_0–12h) and PD (activity of inosine‐5′‐monophosphate dehydrogenase [IMPDH]) parameters were measured at weeks 2, 8, 16, and 24. We found that IMPDH activity decreased from baseline by 31–42% within 2–4 h after dosing, coinciding with the increased plasma MPA concentration. MPA‐AUC_0–12h ≥45 μg.h/ml was best predicted by a single time point MPA concentration at C0.5, C2, C3, C4, and C8 (r ² = 0.516, 0.514, 0.540, 0.611, and 0.719, respectively), independent of dose, albumin, urine protein/creatinine ratio, and urinalysis. The MPA‐C0.5 cutoff of 2.03 g/ml yielded the highest overall sensitivity of 85% and specificity of 88.2% in predicting MPA‐AUC_0–12h ≥45 μg.h/ml. A single timepoint of plasma MPA‐C0.5 ≥2.03 μg/ml may help guide EC‐MPS adjustment to achieve adequate drug exposure. Further study of EC‐MPS used to validate this cutoff is warranted.

Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? Therapeutic drug monitoring (TDM) is crucial in lupus nephritis (LN) treated with mycophenolic acid (MPA), especially mycophenolate mofetil. The area under the plasma concentration‐time curve of MPA from time 0 to 12 h (MPA‐AUC_0–12h) ≥ 45 μg.h/ml or a single plasma MPA concentration (C0 or C1) are used as tools to enhance the highest treatment efficacy. In addition, enteric‐coated mycophenolate sodium (EC‐MPS) was also used to treat relapsed or resistant LN. However, little is known regarding the TDM of EC‐MPS. WHAT QUESTION DID THIS STUDY ADDRESS? This study assessed EC‐MPS’s pharmacokinetics (PKs) and pharmacodynamics (PDs) in adult patients with relapsed or resistant LN and investigated a surrogate single timepoint of plasma MPA concentration with optimum plasma level cutoff as an alternative for MPA‐AUC. WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? This study provided EC‐MPS’s PK and PD profiles and suggested a surrogate single timepoint of plasma MPA concentration with optimum plasma level cutoff as potential alternatives for MPA‐AUC_0–12 ≥45 μg.h/ml to be applied in TDM. HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE? This study supports the role of TDM in relapsed or resistant LN treated with EC‐MPS. In addition, a single timepoint of plasma MPA concentration at C0.5 with the proposed cutoff at ≥2.03 μg/ml is a TDM tool that can be easily applied in clinical practice. However, a more significant number of study patients is required.     

Pharmacokinetics of duloxetine hydrochloride enteric-coated tablets in healthy Chinese volunteers: A randomized,open-label,single- and multiple-dose study

Background: Duloxetine hydrochloride is a balanced selective serotonin and norepinephrine reuptake inhibitor. Despite being widely used for the treatment of major depressive disorder in China, little information is available on the pharmacokinetic (PK) properties of duloxetine in Chinese subjects.Objectives: This study was designed to determine the concentration of duloxetine in human plasma and to compare the PK properties of duloxetine after administration of single and multiple doses of duloxetine in healthy Chinese volunteers.Methods: A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for determining the concentration of duloxetine in human plasma was developed and applied to this single-center, open-label, single- and multiple-dose PK study. Subjects were randomized to receive a single dose of 30, 60, or 90 mg of duloxetine. Those who received the 30-mg dose continued on to the multiple-dose phase and received 30 mg twice daily for 7 days. In the single-dose phase, sequential blood samples were collected from 0 to 60 hours after drug administration. In the multiple-dose phase, samples were obtained before drug administration on days 4, 5, 6, and 7 to determine the Cssmin of duloxetine; on day 7, samples were collected from 0 to 60 hours after drug administration. The PK parameters that were calculated included C_max, T_max, t_1/2, AUC_0?t AUC_0?∞, CL, V_d, C_ssmax, C_ssmin, C_ssav, AUC_ss, AUC_ss(0?t), and C_max:C_min ratio. All values were expressed as mean (SD). Tolerability was assessed throughout the study.Results: The LC-MS/MS method was developed and validated. The standard calibration curve was linear in the concentration range from 0.89 to 106.8 ng/mL; the correlation coefficient was >0.995. The methodo-logic recovery and extraction recovery ranged from 87.22% to 113.75% and 72.81% to 89.96%, respectively. Both the intraday and interday relative SDs were <11%. Thirty Chinese subjects (3 groups of 10 subjects [5 men, 5 women] each) were enrolled in the single-dose phase of the PK study. The mean (SD) age of the subjects was 23.2 (1.8) years (range, 21–25 years); their mean (SD) weight was 61.0 (7.7) kg (range, 52–80 kg) and height was 169.0 (7.1) cm (range, 155–180 cm). The main PK parameters for duloxetine after administration of a single oral dose of 30, 60, and 90 mg were as follows: C_max = 22.46 (15.15), 44.40 (17.18), and 60.78 (27.84) ng/mL, respectively; AUC_0–60 = 328.64 (203.64), 696.04 (337.82), and 1219.33 (598.29) ng/mL · h^?1; AUC_0?∞) = 359.68 (201.01), 733.82 (343.40), and 1280.51 (644.81) ng/mL · h^?1; T_max = 6.83 (1.99), 6.10 (1.29), and 6.60 (1.58) hours; t1/2 = 12.95 (3.64), 12.81 (2.31), and 11.66 (2.06) hours; CL = 107.90 (53.05), 98.41 (41.98), and 109.58 (52.74) L/hour; and V_d = 2518.88 (1707.71), 1879.74 (999.09), and 1858.47 (1203.69) L. The 10 subjects who received the 30-mg dose in the single-dose phase continued on to the multiple-dose phase and received 30 mg of duloxetine twice daily for 7 days. Mean (SD) values for the main PK parameters for duloxetine after administration of multiple doses were as follows: C_ssmax = 47.33 (16.95) ng/mL; C_ssmm = 27.92 (9.46) ng/mL; AUC_ss(0?t) = 407.25 (125.94) ng/mL · h^?1; C_ssav = 33.94 (13.00) ng/mL; T_max = 6.36 (0.92) hours; t_1/2 = 11.19 (1.98) hours; CL = 83.12 (28.75) L/hour; and V_d = 1359.01 (590.06) L.Conclusions: In these healthy Chinese subjects, AUC and Cmax increased proportionally with the dose, whereas t_1/2 was independent of the dose. Linear PK properties were found at doses of 30 to 90 mg. No statistically significant differences were observed between the PK parameters for the subjects in the multiple-dose phase (t_1/2, CL, V_d) and those for subjects in the single-dose phase. The AUC and C_max were greater after administration of multiple doses than after administration of a single dose, suggesting du-loxetine accumulation with multiple-dose administration of 30 mg.     

Pharmacodynamic comparison of two formulations of Acarbose 100-mg tablets

What is known and Objective: Acarbose, an α‐glycosidase inhibitor, is used to treat diabetic patients. Pharmacokinetic evaluation of acarbose is difficult because <2% is absorbed systemically. The current investigation evaluated the bioequivalence of two formulations of acarbose through pharmacodynamic comparison. Methods: This investigation consisted of a pilot study and a main study. The pilot study had an open, single‐dose, single‐sequence design. Subjects received placebo and then two tablets of reference formulation (Glucobay^® 100 mg tablet; Bayer Healthcare) on two consecutive days with sucrose. The main study was an open, randomized, two‐period, two‐sequence crossover study. Subjects randomly received placebo and two tablets of either test formulation (generic acarbose 100‐mg tablet) or reference formulation with sucrose on two consecutive days in the first period. In the second period, placebo and alternative formulation were administered. Serial blood samples for pharmacodynamic assessment were taken after each administration. The maximum serum glucose concentration (G_max) and the area under the serum glucose concentration–time profile (AUC_gluc) were determined and compared. Results and Discussion: Five subjects completed the pilot study. The AUC_gluc from dosing until 1 h post‐dose (AUC_{gluc,1 h}) was significantly different between the placebo and acarbose. A total of 33 subjects completed the main study. The mean differences in G_max (ΔG_max) and AUC_{gluc,1 h} (ΔAUC_{gluc,1 h}) for the reference formulation compared with placebo were 22·0 ± 18·3 mg/dL and 928·2 ± 756·0 mg min/dL, respectively. The corresponding values for the test formulation were 23·3 ± 21·2 mg/dL and 923·0 ± 991·4 0 mg min/dL, respectively. The geometric mean ratios (GMRs) of the test formulation to the reference formulation for ΔG_max and ΔAUC_{gluc,1 h} were 1·06 and 1·00, respectively, and the 90% confidence intervals (CIs) corresponding values were 0·79–1·39 and 0·64–1·36, respectively. What is new and Conclusion: The 90% CIs of GMRs for the pharmacodynamic parameters chosen for bioequivalence evaluation of two formulations of acarbose did not meet the commonly accepted regulatory criteria for bioequivalence (0·80–1·25).     

Two sampling time profiles for the abbreviated estimation of mycophenolic acid area under the curve in adult renal transplant recipients treated with mycophenolate mofetil and concomitant tacrolimus

Objective: Various studies have revealed that mycophenolic acid (MPA) area under the time‐concentration curve (AUC) may have clinical value in mycophenolate mofetil dose adjustment. As the full AUC measurement is impractical in clinical practice, several abbreviated AUC profiles using pre‐dose, and two or three post‐dose samples have been proposed; however, the possible use of lower sampling time profiles has an unquestionable practical interest, and the aim of our study was the evaluation of several two‐points algorithms using only one post‐dose sample. Patients and methods: In 60 MPA concentration‐time profiles from 37 adult renal transplant patients treated with mycophenolate mofetil and concomitant tacrolimus, the MPA AUC values were estimated using the three sampling time algorithm (pre‐dose, one‐half and 2 h post‐dose) of Pawinski et al. (Clinical Chemistry 48, 2002, 1497), trapezoidal extrapolated procedure according to Hale et al. (Clinical Pharmacology Therapeutics 64, 1998, 672), and two‐points algorithm (pre‐dose and 2 h post‐dose) proposed by David‐Neto et al. (Clinical Transplantation 19, 2005,19). Results: The AUC values estimated using the algorithm of Pawinski et al. had a very high correlation (r = 0·997, P < 0·001) with the trapezoidal extrapolated AUC results. The estimated AUC values obtained using the two‐points algorithm of David‐Neto et al. present a high correlation (r = 0·930, P < 0·001), acceptable mean prediction error (+3·3 ± 1·8%), and a diagnostic efficiency of 94% in the classification of subtherapeutic, therapeutic, and supratherapeutic values, with respect to the three‐points algorithm of Pawinski et al. Conclusion: The two sampling time algorithm of David‐Neto gave similar results to those of the three‐sampling time algorithm of Pawinski, and both, with sampling over 2 h, may be useful for routine MPA AUC estimation in renal transplant recipients with concomitant tacrolimus. Both are unsuitable when unusually unpredictable pharmacokinetics are expected such as with enteric‐coated formulations.     

Lack of significant food effect on the pharmacokinetics of ticagrelor in healthy volunteers

What is known and Objective: Ticagrelor is the first reversibly binding oral P2Y₁₂ receptor antagonist and has been approved in the European Union and the USA for the reduction of clinical thrombotic events in patients with acute coronary syndromes. This study aimed to assess the effect of food on ticagrelor pharmacokinetics. Methods: The study was an open‐label, randomized, 2‐period crossover single‐centre trial; 26 healthy volunteers received a single 270 mg (3 × 90 mg tablets) ticagrelor dose orally following: (i) a 10‐h overnight fast; and (ii) after a standard high‐fat, high‐calorie breakfast. Ticagrelor and AR‐C124910XX (a major pharmacologically active metabolite) plasma concentrations were quantified for pharmacokinetic analysis. Results: Ticagrelor median time to maximum concentration (t_max; 2·5 h vs. 1·5 h) was slightly delayed in the fed vs. fasting state. Maximum concentration of ticagrelor (C_max) was comparable between the two states with 95% confidence intervals (CI) of the geometric least‐squares (GLS) mean ratio (0·85–1·03) being within no‐effect limits (0·80–1·25). Ticagrelor exposure was slightly higher with food intake; area under the plasma concentration–time curve from zero to infinity (AUC) was 21% higher compared with fasting state (95% CI of GLS mean ratio = 1·13–1·30). For AR‐C124910XX, AUC (95% CI of GLS mean ratio = 0·93–1·07) was unaffected by food consumption. Median t_max of the metabolite was slightly longer in the fed than fasting state (3·5 h vs. 1·5 h). Mean C_max for AR‐C124910XX was slightly lower (22%) with food intake vs. fasting (95% CI of GLS mean ratio 0·69–0·88). What is new and Conclusion: Food effects on ticagrelor AUC and AR‐C124910XX C_max were small and are considered to be of minimal clinical significance. Thus, ticagrelor can be administered with or without food.     

Smoking behaviour modulates pharmacokinetics of orally administered clopidogrel

Background and objectives: Clopidogrel is an important antiplatelet drug that is effective in preventing thrombotic events, especially for patients undergoing percutaneous coronary intervention. The therapeutic usefulness of clopidogrel has been limited by documented inter‐individual heterogeneity in platelet inhibition, which may be attributable to known clopidogrel pharmacokinetic variability. The objective of this study was to assess the influence of smoking cigarettes and abnormal body weight on the pharmacokinetics of clopidogrel. Methods: Seventy‐six healthy adult male volunteers were selected randomly. Each subject received a single 75 mg oral dose of clopidogrel after overnight fast. Clopidogrel carboxylate plasma levels were measured and non‐compartmental analysis was used to determine peak plasma concentration (C_max), time to peak plasma concentration (T_max), elimination half‐life (t_1/2e), and area under the curve (AUC_0→∞). Results: One‐third of volunteers were smokers (n = 27) and one‐half had abnormal body weight (n = 39). Smokers had lower AUC_0→∞ (smokers: 6·24 ± 2·32 μg/h/mL vs. non‐smokers: 8·93 ± 3·80 μg/h/mL, P < 0·001) and shorter half‐life (smokers: 5·46 ± 2·99 vs. non‐smokers: 8·43 ± 4·26, P = 0·001). Smoking behaviour had no influence on C_max (P = 0·3) and T_max (P = 0·7). There was no statistically significant difference in C_max, AUC_0→∞, T_max and t_1/2e between volunteers with abnormal body weight and normal body weight. However the difference in body weight of the two groups was relatively narrow (mean ± SE; 26·93 ± 0·16 vs. 23·11 ± 0·27). In general, the pharmacokinetic parameters were characterized by considerable inter‐individual differences (C_max = 3·09 ± 0·99 μg/mL, CV = 32%), (T_max =0·76 ± 0·24 h, CV = 31·6%), (AUC_0→∞ = 7·98 ± 3·58 μg/h/mL, CV = 44·8%), and (t_1/2e = 7·38 ± 4·10 h, CV = 55·6%). Conclusion: Smoking is a significant factor affecting the pharmacokinetics of clopidogrel, following administration of a single 75 mg dose in healthy young volunteers. The study supports smoking‐cessation recommendations. Further studies are required to evaluate the influence of smoking and body weight on the pharmacokinetics of the active metabolite of clopidogrel and on the clinical effects of any differences observed.     

Pharmacokinetics and safety of bromotetrandrine (BrTet, W198) after single-dose intravenous administration in healthy Chinese volunteers

Objective: To investigate the safety and pharmacokinetics of bromotetrandrine (BrTet, W198), a novel inhibitor of P‐glycoprotein (P‐gp), after single‐dose i.v. infusion in healthy Chinese volunteers. Methods: We conducted a randomized, dose‐escalating, phase I clinical study for that purpose. Thirty healthy subjects received BrTet at the doses of 10, 20 or 30 mg/m² by i.v. infusion. Plasma and urine concentrations of bromotetrandrine were determined by using a liquid chromatography–tandem mass spectrometric (LC/MS/MS) method. AUC was calculated by the trapezoidal rule extrapolation method. C_max, T_max, t_1/2α, t_1/2β, Cl and V_d were compiled from the plasma concentration–time data. Results: Bromotetrandrine was generally well tolerated at all doses. No serious or severe adverse events were found in the study. The pharmacokinetic parameters of BrTet after single i.v. infusion doses of BrTet 10, 20 and 30 mg/m² were as follows: T_max were 1·5 h in three groups, C_max were 24·79, 39·59 and 64·31 μg/L, t_1/2α were 0·37, 0·29 and 0·30 h, t_1/2β were 62·88, 56·45 and 52·20 h. AUC_0–194h were 345·83, 688·15 and 1096·28 μg h/L, Cl were 23·68, 25·69 and 25·66 L h/m², V_d were 157·73,156·96 and 140·73 L/m². In urine, the total eliminate rate of originate compound was 0·61 ± 0·19%. Conclusions: This study suggested that bromotetrandrine was well tolerated in healthy volunteers within the dose range evaluated. The pharmacokinetics parameters of bromotetrandrine indicated that the compound was rapidly distributed and accumulated in the tissues, and slowly cleared from plasma, which supported the use of BrTet for a once or twice dosing per chemotherapy cycle.     

Cyclosporine alters correlation between free and total mycophenolic acid in kidney transplant recipients in the initial phase

What is known and Objective: The factors affecting the pharmacokinetics of free mycophenolic acid (MPA) and its phenolic glucuronide (MPAG) are still unclear. The aim of this study was to evaluate the influence of cyclosporine on the pharmacokinetics of free MPA and MPAG. Methods: Seventy‐seven kidney transplant recipients (23 were in an initial phase and 54 in a stable phase; 41 were treated with cyclosporine and 36 with tacrolimus) were enrolled. Free and total MPA and MPAG were determined using HPLC. The correlations between free and total predose concentrations (C₀) of MPA or MPAG were evaluated separately in patients receiving calcineurin inhibitor medications. Results and Discussion: Serum concentration of albumin was lower in the initial phase than in the stable phase. A higher ratio of free MPAG C₀ to free MPA C₀ was observed in cyclosporine‐treated than tacrolimus‐treated kidney transplant recipients. Free MPA C₀ correlated weakly with total MPA C₀ in kidney transplant recipients treated with cyclosporine in the initial phase (ρ = 0·53, P = 0·06). What is new and Conclusion: Cyclosporine increased the ratio of free MPAG C₀ to free MPA C₀ and varied the free fraction of MPA in the hypoalbuminaemic kidney transplant recipients in the initial phase.     

A pharmacokinetic comparison of single doses of once-daily cyclobenzaprine extended-release 15 mg and 30 mg: A randomized,double-blind,two-period crossover study in healthy volunteers

Objective: The purpose of this study was to compare the pharmacokinetics and tolerability of single oral doses of cyclobenzaprine extended-release (CER) 15- and 30-mg capsules.Methods: This was a randomized, double-blind, 2-period crossover study in healthy adults aged 18 to 40 years. Subjects were assigned to receive a single dose of either CER 15 mg or 30 mg on days 1 and 15, separated by a 14-day washout. Study comparisons included the plasma cyclobenzaprine AUC to 168 hours after dosing (AUC_0–168), AUC_0–∞, and C_max. Plasma cyclobenzaprine T_max, terminal elimination t_1/2, and adverse events (AEs) were also assessed.Results: Sixteen subjects (9 women, 7 men) were randomized to receive cyclobenzaprine 15 mg or 30 mg; 13 (81.3%) were white and 3 (18.8%) were black. Mean age and weight were 30.2 years and 70.7 kg, respectively. The shapes of the pharmacokinetic profiles for CER 15 and 30 mg were parallel. Mean observed values for dose-dependent pharmacokinetic parameters of CER 15 and 30 mg were as follows: AUC_0–168, 318.3 and 736.6 ng · h/mL, respectively; AUC_0–∞), 354.1 and 779.9 ng · h/mL; and C_max, 8.3 and 19.9 ng/mL. Dose-independent parameters were comparable across doses. Median observed Tmax was 6.0 hours for both CER doses; mean t_1/2 was 33.4 hours for CER 15 mg and 32.0 hours for CER 30 mg. The bioavailability of the 2 doses, as indicated by the least squares mean AUC_0–∞, was 330.3 ng · h/mL for CER 15 mg and 755.1 ng · h/mL for CER 30 mg. During the CER 15-mg treatment sequence, 5 subjects experienced 5 AEs (headache, dizziness, musculoskeletal pain, dermatitis, and glossodynia); during the CER 30-mg treatment sequence, 2 subjects experienced 2 AEs (somnolence and dysmenorrhea). All AEs were mild in intensity. No serious AEs occurred during the study.Conclusions: Once-daily CER 15 and 30 mg exhibited similarly shaped pharmacokinetic profiles. AUC_0–168, AUC_0–∞), and C_max values for the 30-mg dose were approximately double those for the 15-mg dose, a result consistent with previously reported data on the dose proportionality of cyclobenzaprine immediate release.     

Differences in immunogenicity associated with non-product related variability: insights from two pharmacokinetic studies using GP2017, an adalimumab biosimilar

ABSTRACT

Introduction: Antidrug antibody (ADA) development is known to occur with adalimumab treatment and impacts adalimumab exposure. Here, we compare the impact of immunogenicity on pharmacokinetics (PK) across two randomized PK studies of GP2017, an approved biosimilar adalimumab, in healthy subjects.

Methods: Healthy male subjects (N= 107 in study GP17-104; N= 90 in study GP17-103) received a single 40 mg subcutaneous injection of the same GP2017 drug product batch. Cross-study PK comparison was performed for log-transformed C_max, AUC_0–360h, AUC_0–last, and AUC_0–inf, using an ANCOVA model.

Results: The proportion of ADA-positive subjects was higher in GP17-103 (in total 71.1%) vs. GP17-104 (57.9%). Comparison of GP2017 PK between studies showed that the exposure was lower in GP17-103 vs GP17-104, with 90% confidence intervals (CIs) for geometric mean ratios of AUC_0–last and AUC_0–inf being outside the range of 0.80–1.25. A subgroup analysis showed that in ADA-negative subjects 90% CIs for all PK parameters were within range, with geometric mean ratios close to 1.00.

Conclusion: The differences in GP2017 PK between the two groups are not considered to be product-related, but may be due to currently unknown factors related to differences between the two study populations.     

The comparative pharmacokinetics of modified‐release and immediate‐release paracetamol in a simulated overdose model

Background: Panadol Extend (PEx) is an over‐the‐counter, modified‐release formulation of paracetamol. Each 665 mg tablet contains 69% slow‐release and 31% immediate‐release paracetamol. In simulated human overdose, PEx exhibits lower and later peak serum concentrations and a lower area‐under‐the‐curve (AUC) than comparable doses of immediate‐release paracetamol (APAP‐IR). The lower AUC might result from incomplete absorption of paracetamol or simultaneous metabolism with absorption. Objective: Do differences in pharmacokinetics (PK) between PEx and APAP‐IR result from incomplete absorption or simultaneous absorption and metabolism of paracetamol? Methods: Cross‐over study of 80 mg/kg of PEx or APAP‐IR in nine volunteers. Serial plasma paracetamol, glucuronide, sulphate and cysteine metabolite estimates performed over 24 h. Peak plasma concentration (Cmax), AUC_(0–∞), time to peak concentration (Tmax) and elimination half‐life (t_1/2) were compared. Results: PEx exhibited significantly lower paracetamol Cmax (252.33 µmol/L vs 565.56 µmol/L, P= 0.0421), AUC_(0–∞) (2133 µmol/h/L vs 2637 µmol/h/L, P= 0.0004) and delayed Tmax (2.889 h vs 1.389 h, P= 0.0189) than APAP‐IR. Sulphate metabolite PK parameters for both preparations, PEx vs APAP‐IR, showed similar AUC_(0–∞) (1369 µmol/h/L vs 1089 µmol/h/L), Tmax (3.889 h vs 4.444 h), Cmax (95.889 µmol/L vs 95.889 µmol/L) and t_1/2 (3.895 h vs 3.810 h). Glucuronide metabolite concentrations revealed that PEx produced a lower Cmax (257.44 µmol/L vs 335.22 µmol/L, P= 0.0239) than APAP‐IR. All other pharmacokinetic parameters were similar. Cysteine metabolite was not detected. Conclusion: There were minor differences between the PK parameters of the two major paracetamol metabolites of these two preparations in simulated overdose. The variability in paracetamol AUC seen between the two preparations in moderate overdose might be explained by concurrent metabolism of paracetamol during slower absorption with PEx.     

Pharmacokinetics and pharmacodynamics of prasugrel in subjects with moderate liver disease

Background and Objective: Prasugrel is a thienopyridine antiplatelet agent under investigation for the prevention of atherothrombotic events in patients with acute coronary syndrome who undergo percutaneous coronary intervention. Patients with chronic liver disease are among those in the target population for prasugrel. As hepatic enzymes play a key role in formation of prasugrel’s active metabolite, hepatic impairment could affect the safety and/or efficacy of prasugrel in such patients. Methods: This was a parallel‐design, open‐label, multiple dose study of 30 subjects, 10 with moderate hepatic impairment (Child‐Pugh Class B) and 20 with normal hepatic function. Prasugrel was administered orally as a 60‐mg loading dose (LD) and daily 10‐mg maintenance doses (MDs) for 5 days. Pharmacokinetic parameters (AUC_0–t, C_max and t_max) and maximal platelet aggregation (MPA) by light transmission aggregometry were assessed after the LD and final MD. Results and Discussion: Exposure to prasugrel’s active metabolite was comparable between healthy subjects and those with moderate hepatic impairment. Point estimates for the ratios of geometric least square means for AUC_0–t and C_max after the LD and last MD ranged from 0·91 to 1·14. MPA to 20 μm ADP was similar between subjects with moderate hepatic impairment and healthy subjects for both the LD and MD. Prasugrel was well tolerated by all subjects, and adverse events were mild in severity. Conclusion: Moderate hepatic impairment appears to have no effect on exposure to prasugrel’s active metabolite. Furthermore, MPA results suggest that moderate hepatic impairment has little or no effect on platelet aggregation relative to healthy controls. Overall, these results suggest that a dose adjustment would not be required in moderately hepatically impaired patients taking prasugrel.     

Determination of glycyrrhetic acid in human plasma by HPLC-MS method and investigation of its pharmacokinetics

Objective: To develop a high performance liquid chromatography mass spectrometry (HPLC‐MS) method for the determination of the glycyrrhetic acid (GA) in human plasma and for the investigation of its pharmacokinetics after the oral administration of 150 mg diammonium glycyrrhizinate test and reference capsule formulations. Methods: The GA in plasma was extracted with ethyl acetate, separated on a C₁₈ column with a mobile phase of methanol (5 mmol/L ammonium acetate)–water (85 : 15, V/V) and analysed using a MS detector. Ursolic acid (UA) was used as internal standard. The target ions were m/z 469·5 for GA and m/z 455·6 for UA, the fragment voltages were 200 V and 100 V for GA and UA respectively. Results: The calibration curve was linear over the range of 0·5–200 ng/mL (r = 0·9974). The limit of quantification for GA in plasma was 0·5 ng/mL, the recovery was 76·0–80·0%, and the inter‐ and intra‐day relative standard deviations (RSD) were <12%. The pharmacokinetic parameters of GA after a single dose of 150 mg diammonium glycyrrhizinate test and reference were as follows: the half life (t_1/2) 9·65 ± 3·54 h and 9·46 ± 2·85 h, the time to peak concentration (T_max) 10·95 ± 1·32 h and 11·00 ± 1·30 h, the peak concentration (C_max) 95·57 ± 43·06 ng/mL and 103·89 ± 49·24 ng/mL; the area under time‐concentration curve (AUC_0–48 and AUC_0–∞) 1281·84 ± 527·11 ng·h/mL and 1367·74 ± 563·27 ng·h/mL, 1314·32 ± 566·40 ng·h/mL and 1396·97 ± 630·06 ng·h/mL. The relative bioavailability of diammonium glycyrrhizinate capsule was 98·88 ± 12·98%. Conclusion: The assay was sensitive, accurate and convenient, and can be used for the determination of GA in human plasma. Comparison of the bioavailability and pharmacokinetic profile of GA indicated that the test and reference capsules were bioequivalent.     

The effects of food on the pharmacokinetics of mitiglinide tablets in healthy volunteers and a novel mass-spectrometric (UPLC-MS/MS) method for such studies

What is known and Objective: Mitiglinide (MGN) is a new insulinotropic agent of the glinide class with rapid onset. The effects of food intake on the pharmacokinetic (PK) profile of mitiglinide tablets after single oral administration have not yet been reported in healthy adults. We aimed to assess the effects of food intake on the PK properties of mitiglinide (MGN) tablets, using a novel analytical method, after single escalating oral doses in healthy Chinese volunteers. Methods: In this open‐label, randomized, single‐dose (three distinct doses), two‐way crossover PK study, three doses of MGN 5, 10 or 20 mg were administered to healthy adult volunteers after an overnight fast (fasted condition) or low‐fat breakfast (fed condition) (period 1). After 7 days, the participants received the same dose under the opposite fed/fasted condition (period 2). Serial blood samples were obtained before and through 8 h after study drug administration. Concentrations of MGN in plasma were determined using UPLC‐MS/MS. Adverse events (AEs) were monitored and recorded on each in‐clinic day. Results and Discussion: Twenty‐four Chinese volunteers (eight [four men, four women] volunteers per group) were enrolled in the study. The extent of absorption of MGN was similar in both fed and fasted conditions at single doses in the range 5–20 mg. Food intake was associated with decreases in C_max by 60·4% to 65·2% in the three dose groups and greatly delayed T_max [0·36(Standard deviation 0·16) vs. 1·75(0·92) hours with 5 mg, 0·29(0·19) vs. 1·97(0·81) hours with 10 mg and 0·30(0·10) vs. 1·18(0·68) hours with 20 mg; all, P < 0·05]. t_1/2, CL/F and V/F (P > 0·05) were unaffected. MRT_0–8 at the 5 and 10‐mg doses, but not at the 20‐mg dose, were markedly lower in fasted volunteers than fed volunteers (P < 0·05). What is new and Conclusions: Using a novel UPLC‐MS/MS method, we showed that food intake affected the rate but not the extent of absorption of MGN within the 5‐ to 20‐mg dose range. Gender did not appear to affect the PK properties of MGN in either fasted or fed states. MGN should be preferably taken before food.     

Effect of cytochrome P450 3A4 inhibitor ketoconazole on risperidone pharmacokinetics in healthy volunteers

What is known and objective: Risperidone is an atypical antipsychotic agent used for the treatment of schizophrenia. It is mainly metabolized by human cytochrome P450 CYP2D6 and partly by CYP3A4 to 9‐hydroxyrisperidone. Ketoconazole is used as a CYP3A4 inhibitor probe for studying drug–drug interactions. We aim to investigate the effect of ketoconazole on the pharmacokinetics of risperidone in healthy male volunteers. Methods: An open‐label, randomized, two‐phase crossover design with a 2‐week washout period was performed in 10 healthy male volunteers. The volunteers received a single oral dose of 2 mg of risperidone alone or in combination with 200 mg of ketoconazole, once daily for 3 days. Serial blood samples were collected at specific periods after ingestion of risperidone for a period of 96 h. Plasma concentrations of risperidone and 9‐hydroxyrisperidone were determined using a validated HPLC–tandem mass spectrometry method. Results and discussion: After pretreatment with ketoconazole, the clearance of risperidone decreased significantly by 34·81 ± 15·10% and the T_1/2 of risperidone increased significantly by 28·03 ± 40·60%. The AUC_0–96 and AUC_0–∞ of risperidone increased significantly by 66·61 ± 43·03% and 66·54 ± 39·76%, respectively. The Vd/f of risperidone increased significantly by 39·79 ± 53·59%. However, the C_max and T_max of risperidone were not significantly changed, indicating that ketoconazole had minimal effect on the absorption of risperidone. The C_max, T_max and T_1/2 of 9‐hydroxyrisperidone did not decrease significantly. However, the Cl/f of 9‐hydroxyrisperidone increased significantly by 135·07 ± 124·68%, and the Vd/f of 9‐hydroxyrisperidone decreased significantly by 29·47 ± 54·64%. These changes led to a corresponding significant decrease in the AUC_0–96 and AUC_0–∞ of 9‐hydroxyrisperidone by 47·76 ± 22·39% and 48·49 ± 20·03%, respectively. Ketoconazole significantly inhibited the metabolism of risperidone through the inhibition of hepatic CYP3A4. Our results suggest that besides CYP2D6, CYP3A4 contributes significantly to the metabolism of risperidone. What is new and Conclusion: The pharmacokinetics of risperidone was affected by the concomitant administration of ketoconazole. If a CYP3A4 inhibitor is used concomitantly with risperidone, it is necessary for the clinicians to monitor their patients for signs of adverse drug reactions.