European Journal of Drug Metabolism and Pharmacokinetics最新文献

Background and objectives: The commonly used antiseizure medication lamotrigine is a substrate to ATP binding cassette subfamily G member 2 (ABCG2) transporter. The objective of this study was to evaluate the effect of the common loss-of-function polymorphism ABCG2 c.421C>A (rs2231142) on the lamotrigine trough concentrations at steady state in adults with epilepsy.

Methods: In two consecutive studies (Study 1, Study 2) in patients on lamotrigine monotherapy, carriers of the variant ABCG2 c.421C>A allele (CA/AA) were considered exposed, and wild-type homozygotes (CC) were considered controls. They were mutually balanced on covariates (age, sex, body weight, several polymorphisms in genes encoding other transporter proteins and lamotrigine-metabolizing enzymes that have been suggested to affect exposure to lamotrigine) to estimate the exposure effect (geometric means ratios, GMRs) in each study separately and overall (individual patient data meta-analysis). The overall estimate was evaluated for sensitivity to residual confounding.

Results: In both studies (exposed n = 28 vs. controls n = 103; exposed n = 44 vs. controls n = 153, in Study 1 and Study 2, respectively) and overall (exposed n = 72 vs. controls n = 256), dose-corrected lamotrigine trough concentrations were moderately lower in the exposed patients: frequentist GMR [95% CI] = 0.82 [0.63-1.08]; GMR = 0.69 [0.60-0.81] and GMR = 0.72 [0.63-0.83] in Study 1, Study 2 and overall, respectively; Bayes GMR [95% CrI] = 0.83 [0.68-1.00]; GMR = 0.69 [0.58-0.83] and GMR = 0.75 [0.65-0.86] in Study 1, Study 2 and overall, respectively. Estimates appeared resistant to unmeasured confounding-the E-values for the pooled point estimates were high, and estimates corrected for a strong hypothetical bias were GMR = 0.78 [0.68-0.90] frequentist and GMR = 0.81 [0.70-0.93] Bayes.

Conclusion: Polymorphism ABCG2 c.421C>A moderately reduces lamotrigine concentrations in adults with epilepsy.

Caffeine consumption is regarded as a widespread phenomenon, and its usage has continued to increase. In addition, the growing usage of antidepressants worldwide and increase in mental health disorders were shown in recent statistical analyses conducted by the World Health Organisation. The coadministration of caffeine and antidepressants remains a concern due to potential interactions that can alter a patient's response to therapy. This review investigates the pharmacokinetic and pharmacodynamic interactions between caffeine and the five main classes of antidepressants: selective serotonin reuptake inhibitors (SSRIs), tricyclic antidepressants (TCAs), serotonin and norepinephrine reuptake inhibitors (SNRIs), monoamine oxidase inhibitors (MAOIs), and other antidepressants not categorised by class, which we have categorised as 'miscellaneous'. The interaction between fluvoxamine and caffeine resulted in increased concentrations of caffeine in the body and lowered the renal clearance of fluvoxamine. Other SSRIs such as fluoxetine and escitalopram had augmented antidepressant effects by decreasing their renal clearance and prolonging their effects in the body when coadministered with caffeine. Caffeine may also increase the concentration of paroxetine, potentially affecting its pharmacodynamic effects. TCAs such as clomipramine, imipramine, desipramine, and sertraline, were found to reduce the metabolism of caffeine. However, studies suggest caffeine had no significant effect on the concentration of these medications in blood or brain tissue. The inhibition of caffeine at high doses when used with MAOIs such as tranylcypromine and phenelzine was found to lead to a higher likelihood of experiencing hypertension. Coadministration of caffeine with venlafaxine (SNRIs) suggests minimal interactions between the two substances and the pharmacodynamic effects of venlafaxine were unlikely to be impacted by caffeine consumption. Miscellaneous antidepressants (reboxetine, mianserin, agomelatine, maprotiline, and mirtazapine) displayed varying pharmacodynamic interactions with caffeine, resulting in increased antidepressant effects where vortioxetine, maprotiline, and mirtazapine failed to demonstrate any interactions. In conclusion, caffeine demonstrated varying effects on the pharmacokinetic and pharmacodynamic properties of each class of antidepressants, with several classes of antidepressants demonstrating a similar effect on caffeine.

BACKGROUND AND OBJECTIVE: Currently, there is no available method for the prediction of first-in-human (FIH) dose for chimeric antigen receptor-T (CAR-T) cells. The objective of this work was to predict the FIH dose of CAR-T cells from different doses given to mice.

Methods: In this study, six scaling methods were evaluated for the prediction of FIH dose for CAR-T cells. The methods were body weight-based fixed exponents such as 1.0 and 0.75, human equivalent dose (HED) using exponents 0.33, two modified HED methods such as using total animal dose (in place of per kg basis) and body surface area in place of body weight using total animal dose with exponent 0.33 and a physiological factor derived from physiological parameters. The FIH doses of six CAR-T cells were predicted in this study. The predicted human doses were compared with the recommended human dose by the US-FDA for four CAR-T cell products, and the literature data were used for the remaining two CAR-T cells.

Results: The results indicated that the two modified HED methods and physiological factor are the best and reliable methods for the prediction of FIH dose for CAR-T cells.

Conclusions: The proposed methods are simple and accurate in their predictive power and can be used on a spreadsheet.

Background and objective: For neonates and infants receiving intermittent vancomycin infusions, the area under the concentration-time curve during 24 h (AUC24) is often estimated with Bayesian forecasting using one or more measured vancomycin concentrations. When practical peak and trough concentrations are measured at steady state, AUC24 can also be calculated with first-order steady-state equations for a one-compartment model (Sawchuk-Zaske method), but previously this method has been applied only for adults. The objective of this study was to compare AUC24 values obtained with the Sawchuk-Zaske method and two Bayesian models.

Methods: AUC24 values were estimated retrospectively for 18 neonates and infants with steady-state peak and trough concentrations using traditional compartmental analysis with a one-compartment model (reference method), the Sawchuk-Zaske method, and Bayesian forecasting with two previously published models. In Bayesian forecasting, both original and modified residual error models were used. In the modified models, the residual error was reduced by setting the additive residual error to zero and the proportional error to 15%.

Results: AUC24 estimates obtained with the Sawchuk-Zaske method differed - 2.7 to 0.9% from the reference method. When both peak and trough concentrations were used in Bayesian forecasting, 61% and 33% of AUC24 estimates obtained with two original models differed less than 15% from the reference method, and these fractions increased to 83% and 72% with the modified models, respectively.

Conclusion: When practical peak and trough concentrations are measured at steady state, the simple Sawchuk-Zaske method is very useful for AUC24 estimation in neonates and infants. In Bayesian forecasting, the reduced residual error model can be used to improve the model fit.

Background and objectives: A pharmacokinetic model has been developed to quantify the drug-drug interactions of tacrolimus with concentration-dependent inhibition of cytochrome P450 (CYP) 3A4 from voriconazole and clarithromycin based on the CYP3A5 and CYP2C19 genotypes.

Methods: This retrospective study recruited unrelated bone marrow transplant recipients receiving oral tacrolimus concomitantly with voriconazole and clarithromycin. The published population pharmacokinetic model that implemented genotypes of CYP3A5 (tacrolimus) and CYP2C19 (voriconazole) was integrated. The tested CYP3A4 inhibition models (Sigmoid efficacy maximum [E_max], E_max, log-linear, and linear) were a function of competitive inhibition of voriconazole and mechanism-based inhibition of clarithromycin in a virtual enzyme compartment.

Results: The total tacrolimus trough concentrations were 119 points, with a median of 4.3 (range: 2.0-9.9) ng/mL (n = 3). The final model comprised the Sigmoid E_max model for voriconazole and clarithromycin, which depicted time-course alterations in tacrolimus concentration and clearance when given voriconazole and clarithromycin.

Conclusions: These findings could facilitate the model-informed precision dosing of tacrolimus after unrelated bone marrow transplant.

Background: The pharmacokinetics of immunosuppressant drugs may change with advancing age, potentially affecting patient outcomes.

Objective: To characterise the effects of age on the pharmacokinetic and exposure parameters of tacrolimus, mycophenolate, and prednisolone.

Methods: Pharmacokinetic profiling, involving whole blood tacrolimus, total and free plasma mycophenolic acid (MPA), total plasma mycophenolic acid glucuronide (MPAG), and total and free plasma prednisolone, was performed in an older and younger adult cohort. Thirteen samples were drawn on a single occasion, pre-oral dose and then at 0.25, 0.5, 0.75, 1, 1.25, 1.5, 2, 3, 4, 6, 9, and 12 h post-dose. Non-compartmental analysis was conducted using the PKNCA package, and pharmacokinetic and exposure parameters were compared between age groups using a Mann-Whitney test. A regression analysis was conducted for free MPA and MPAG using significant variables of interest.

Results: This exploratory study included 21 older and 18 younger adults. Dose-adjusted tacrolimus, total MPA and free prednisolone pharmacokinetic parameters were not different between age groups; however, for free MPA and MPAG, older recipients had significantly greater minimum and maximum concentrations, trough concentrations, and half-life. There was a two-fold increase in free MPA exposure in older adults (median dose-adjusted AUC_0-12: 1284 vs. 684 μg h/L, p < 0.0001); MPAG exposure similarly increased. Age was significantly associated with free MPA and MPAG exposure, and free MPA exposure was associated with haematocrit (p < 0.05).

Conclusion: Differences in MPA were found with advancing age and may be due to altered kidney function, haematocrit, plasma protein binding and/or drug absorption. Future research should explore specific covariate contributions to this further.

Background and objectives: Finerenone, a novel selective non-steroidal mineralocorticoid receptor antagonist, has been indicated in chronic kidney disease associated with type 2 diabetes mellitus. Considering the potential complications of diabetes, finerenone can be co-administered with various drugs, including fluconazole, diltiazem, and ritonavir. Given that finerenone is a substrate of cytochrome P450 (CYP) 3A4, the concurrent administration of finerenone with CYP3A4 inhibitors (diltiazem or fluconazole or ritonavir) could potentially lead to drug interactions, which may cause adverse events such as hyperkalemia. No studies have investigated interactions between finerenone and diltiazem or fluconazole or ritonavir. Therefore, this study aims to investigate the pharmacokinetic interaction of finerenone with diltiazem or fluconazole or ritonavir and to evaluate the impact of fluconazole on the pharmacodynamics of finerenone.

Methods: The pharmacokinetic study included four rat groups (n = 8 rats/group), including a control group (finerenone alone) and test groups (finerenone pretreated with diltiazem or fluconazole or ritonavir) using both non-compartment analysis (NCA) and population pharmacokinetic (pop-PK) modeling. The pop-PK model was developed using non-linear mixed-effects modeling in NONMEM^® (version 7.5.0). In the pharmacodynamic study, serum potassium (K⁺) levels were measured to assess the effects of fluconazole on finerenone-induced hyperkalemia.

Results: The NCA results indicated that the area under the plasma concentration-time curve (AUC) of finerenone increased by 1.86- and 1.95-fold when coadministered with fluconazole and ritonavir, respectively. In contrast, diltiazem did not affect the pharmacokinetics of finerenone. The pharmacokinetic profiles of finerenone were best described by a one-compartment disposition with first-order elimination and dual first-order absorption kinetics. The pop-PK modeling results demonstrated that the apparent clearance of finerenone decreased by 50.3% and 49.2% owing to the effects of fluconazole and ritonavir, respectively. Additionally, the slow absorption rate, which represents the absorption in the distal intestinal tract of finerenone, increased by 55.7% due to the effect of ritonavir. Simultaneously, a pharmacodynamic study revealed that finerenone in the presence of fluconazole caused a significant increase in K⁺ levels compared with finerenone alone.

Conclusions: Coadministration of finerenone with fluconazole or ritonavir increased finerenone exposure in rats. Additionally, the administration of finerenone in the presence of fluconazole resulted in elevated K⁺ levels in rats. Further clinical studies are required to validate these findings.

Background and objective: Heated tobacco products (HTPs) are a class of non-combustible, inhaled tobacco products with the potential to reduce the harm associated with cigarette smoking due to reduced cigarette smoke toxicant exposure. Subjective and nicotine pharmacokinetics measures taken over the course of product use provide a framework for abuse liability (AL) assessment of tobacco and nicotine products as well as information on adoption potential for a new tobacco product, which are important aspects for premarket tobacco product authorization by the US Food and Drug Administration. This study aimed to assess the AL of glo HTPs, operated in either Standard or Boost Modes, compared with high- and low-AL comparators (subjects' usual brand cigarettes and nicotine gum, respectively).

Methods: Nicotine uptake and pharmacodynamics measures (including subjective and physiological measures) were assessed in a clinical study of 75 healthy adult non-menthol or menthol smokers using an open-label, randomized crossover study design. Comparisons were made between glo HTPs (Standard or Boost Modes) and each of usual brand (UB) cigarettes and nicotine gum to evaluate nicotine exposure and subjective effects measures.

Results: Nicotine uptake, as reflected in the area under the curve (AUC) at 15 and 240 min after product use (AUC_0-15 and AUC_0-240, respectively) and maximum nicotine concentration (C_max) were significantly lower for all glo HTPs compared to UB cigarettes, regardless of the glo device mode. AUC_0-15 values for glo HTPs ranged from 41.26 to 75.71 ng × min/mL, versus 158.04 to 165.53 ng × min/mL for UB cigarettes. Similarly, AUC_0-240 values for glo HTPs ranged from 379 to 596 ng × min/mL, compared to 1123.73 and 1283.37 ng × min/mL for UB cigarettes. The C_max for glo HTPs ranged from 5.46 to 9.00 ng/mL, whereas UB cigarettes had C_max values of 16.29 to 16.76 ng/mL. The time to reach maximum nicotine concentration (T_max) was significantly shorter for glo HTPs (4-5 min) compared to UB cigarettes (6-7 min), except for one variant of glo HTP in Standard Mode. Nicotine gum exhibited a slower nicotine absorption profile, with a T_max of 45 min and C_max of 4.60 ng/mL. AUC_0-15 and AUC_0-240 values for nicotine gum were 6.18 and 5.22 ng × min/mL, and 647.80 and 687.68 ng × min/mL for non-menthol and menthol groups, respectively. Subjective measures indicated that glo HTPs were rated significantly lower than UB cigarettes in terms of product liking, smoking urge reduction, product effects, and intent to use again, but were comparable to nicotine gum.

Conclusion: glo HTPs demonstrated lower AL than combustible cigarettes while delivering sufficient nicotine to support product adoption among current smokers. This positions glo HTPs as a poten

Background and objectives: Fimasartan, an angiotensin II receptor antagonist, exhibits low bioavailability due to its poor solubility; consequently, using solubilization technologies is essential to improve its bioavailability. In this study, novel fimasartan fluidized solid dispersion (FFSD) was developed using a fluid bed granulator to enhance the drug solubility and oral bioavailability.

Methods: An appropriate FFSD was prepared in 50% ethanol using a fluid bed granulator, and its drug dissolution, morphology, and crystallinity were evaluated in comparison to the powdered drug. Moreover, the dissolution in various pH conditions and pharmacokinetics of the FFSD tablet in beagle dogs were investigated compared to the commercial fimasartan tablet.

Results: Among the hydrophilic polymers tested, hydroxypropyl methylcellulose (HPMC) showed the highest solubility. The FFSD, composed of fimasartan, HPMC, and microcrystalline cellulose at the weight ratio of 20:10:25, gave a granular aggregation of several particles with a smooth surface. The drug in this FFSD existed as an amorphous state, leading to a greatly increased drug dissolution. The FFSD tablet was prepared by compressing a mixture of FFSD, mannitol, croscarmellose sodium, and magnesium stearate at the weight ratio of 55:40:5:1. The FFSD tablet gave significantly higher drug dissolution, plasma concentrations, maximum plasma concentration (C_max) and area under the whole blood concentration-time curve (AUC) values than did the commercial fimasartan tablet. In the beagle dogs, the FFSD tablet (140.39 ± 27.40 ng·h/ml) had about a 1.7-fold higher AUC than the commercial fimasartan tablet (80.58 ± 22.18 ng·h/ml), indicating an enhancement in the bioavailability.

Conclusions: This novel FFSD tablet could be a potential oral pharmaceutical product with the improved oral bioavailability of fimasartan.