European Journal of Drug Metabolism and Pharmacokinetics最新文献

Background and objectives: Hypertensive nephropathy (HN) has become one of the main causes of end-stage renal disease. Drug combination therapy is a common clinical treatment for HN. However, the impact of HN on drug-metabolizing enzymes and transporters, which may lead to drug-drug interactions (DDIs) and even trigger toxic side effects, remains unclear. The aim of this study was to investigate changes in major drug-metabolizing enzymes and transporters in the liver and kidney of HN rats to improve the scientific foundations for the clinical treatment of HN.

Methods: Spontaneously hypertensive rats (SHRs) were used as an animal HN model because their hypertension is similar to that of humans. Wistar-Kyoto rats (WKYs) were used as the control group. Body weight, blood pressure, hematoxylin-eosin (HE) staining and biochemical analysis were performed to evaluate whether the HN model was successfully constructed. Quantitative real-time polymerase chain reaction (PCR) and western blotting were used to evaluate the mRNA and protein expression of drug-metabolizing enzymes, transporters and related nuclear transcription factors.

Results: In HN rats, the mRNA expression of the drug-metabolizing enzymes cytochrome P450 (Cyp) 2b1, Cyp2c11, Cyp3a1 and Cyp7a1 was significantly upregulated. The protein level of CYP3A1 was consistent with its mRNA expression. Interestingly, the mRNA expression of the hepatic transporters organic cation transporter (Oct) 1, Oct2, organic anion transporter (Oat) 1, Oat2, multidrug resistant protein (Mrp) 2, multidrug resistance (Mdr) 1, organic anion transporting polypeptide (Oatp) 1b2 and na+/taurocholate cotransporting polypeptide (Ntcp) was also markedly upregulated. This may be directly influenced by the upregulation of the expression of the nuclear receptors farnesoid X receptor (Fxr), pregnane X receptor (Pxr), liver X-activated receptor (Lxr) and constitutive androstane receptor (Car). In the kidney of HN rats, the mRNA level of the drug-metabolizing enzyme Cyp2b1 significantly increased, while levels of Cyp1a1, Cyp2c11, Cyp3a1 and Cyp3a2 did not significantly change. The mRNA expression of the transporters multidrug and toxin extrusion (Mate) 1 and Mrp2 was obviously increased but was markedly depressed for peptide transporters (Pept) 1 and Pept2. These changes may be related to the cross effects of Pxr, Fxr and Car in kidney.

Conclusion: HN pathological status can alter the expression of drug-metabolizing enzymes and transporters in the liver and kidney to varying degrees, thus affecting the disposition of substrate drugs in vivo. This suggests that to avoid potential risks, caution should be exercised when administering combination therapy for HN treatment.

Background and objective: Neonatal pharmacotherapy has gained attention from clinicians and regulatory agencies for optimizing the dosage of the drug which improves therapeutic outcomes in this special population. Piperacillin-tazobactam antibiotic is commonly used as a therapeutic option for treatment of severe infection in neonatal intensive care units. There are few population pharmacokinetic (PopPK) studies of piperacillin and tazobactam published for this specific population and which were not validated in other study settings. The aim of this study was to externally evaluate the published population pharmacokinetic models for piperacillin-tazobactam.

Methods: A systematic review was conducted through Scopus, PubMed, and Embase databases to identify PopPK models. Clinical data collected in neonates treated with piperacillin-tazobactam were used for evaluation of these models. Various prediction-based metrics were used for assessing the bias and precision of PopPK models using individual predictions.

Results: Three PopPK models were identified for external evaluation. A total of 53 plasma samples were collected from 46 neonates admitted in the neonatal intensive care unit. The PopPK models reported by Cohen-Wolkowiez et al. for piperacillin and Li et al. for tazobactam were able to predict well for our clinical data.

Conclusion: The PopPK models by Cohen-Wolkowiez et al. and Li et al. predicted our data well for piperacillin and tazobactam with the lower relative median absolute predictive error (rMAPE) of 8.61% and 16.48% and relative root mean square error (rRMSE) of 0.01 and 0.03, respectively. External evaluation of the published PopPK models of piperacillin and tazobactam resulted in enhancing their credibility to be implemented in clinical practice.

Background and objective: Cyclosporin A (CsA) exhibits a narrow therapeutic index and large inter-individual variation in pharmacokinetics. Two intermittent and 24-h continuous infusions (CI) are both commonly used regimens in hematopoietic stem cell transplantation (HSCT), with no universal consensus. The objective of this study was to assess whether CsA as a 2-h, twice-daily intravenous infusion (2 h/12 h) is non-inferior to 22 h CI every 24 h (22 h-CI/24 h) in terms of acute graft-versus-host disease (aGVHD) incidence and adverse events in allogeneic HSCT adult patients.

Methods: An open-label randomized trial recruited 31 allogeneic HSCT patients to receive the 2 h/12 h or 22 h-CI/24 h regimen. The primary outcomes were the incidence of aGVHD and CsA-related adverse events. The secondary outcomes included the correlation between the time concentration and area under the concentration-time curve (AUC) of 2 h/12 h versus 22 h-CI/24 h regimens.

Results: Six (19.4%) patients developed aGVHD. There was no statistically significant difference between the two groups concerning the incidence of aGVHD (13.3% in 2 h/12 h vs. 25% in 22 h-CI/24 h; p = 0.359). The distribution of different aGVHD types (p = 0.20) and mortality (p = 0.9) were not significantly different between the two groups. The two groups did not differ at any time with respect to AUCs, nephrotoxicity, hepatotoxicity, or electrolyte disturbance.

Conclusion: The study suggested that the 2 h/12 h regimen is non-inferior to the conventional regimen (22 h CI/24 h) in terms of aGVHD incidence and adverse events. Further research is necessary to validate these findings and to guide practice, considering the small sample size of this study.

Trial registration: ClinicalTrials.gov identifier NCT04575779 with initial release on 19 September 2020-Retrospectively registered, https://clinicaltrials.gov/study/NCT04575779 .

Background: Elinzanetant is a dual neurokinin-1,3 receptor antagonist in development for the treatment of menopausal vasomotor symptoms. The objectives of these studies were to characterize the mass balance and biotransformation of elinzanetant.

Methods: In the clinical evaluation, whole blood, plasma, urine, and feces were collected from healthy fasted male volunteers (n = 6) following a single dose of 120 mg [¹⁴C]-elinzanetant oral suspension for analysis of total radioactivity and metabolite profiling. In vitro reaction phenotyping and kinetics experiments on enzymes involved in elinzanetant metabolism were performed.

Results: On average, 90.8% of the total radioactivity administered was recovered in excreta over 480 h, mostly via the fecal route (feces 90.4%; urine 0.4%). Elinzanetant was rapidly absorbed and extensively metabolized but remained the main circulating species in plasma, accounting for 39.1% of total radioactivity. Known principal and active metabolites M27, M30/34, and M18/21 accounted for 7.6%, 13.7%, and 4.9% of total radioactivity in plasma, respectively. All other radiolabeled plasma components were each < 3.5%, revealing the oxidation product M30/34 as the only metabolite with relevant exposure (> 10% of total radioactivity). In feces, metabolites resulting from oxidative biotransformation accounted, in sum, for ~ 40% of the dose, while elinzanetant remained the primary drug-related moiety. Results of in vitro experiments indicated that metabolism of elinzanetant was primarily mediated by cytochrome P450 3A4, with minor contribution from uridine 5'-diphospho-glucuronosyltransferase.

Conclusions: Elinzanetant is metabolized mainly via oxidative biotransformation mediated by cytochrome P450 3A4, and primarily excreted in feces. The primary oxidation product M30/34 is a major human metabolite of elinzanetant.

Trial registration number: NCT04654897.

Background and objectives: Trofinetide, the first approved treatment for Rett syndrome (RTT), is primarily excreted unchanged in the urine; therefore, it is important to assess the extent to which the exposure is affected in patients with renal impairment. Pharmacokinetic modeling overcomes the challenge of dose finding in phase 1 studies that include special populations where there is the potential for increased exposure to study drug. The objectives of this phase 1 study were to evaluate trofinetide pharmacokinetics, safety, and tolerability in a population with moderate renal impairment and normal renal function. The observed pharmacokinetic profiles were used to validate the dosing adjustments in moderate renal impairment that were previously predicted using a physiologically-based pharmacokinetic (PBPK) model.

Methods: The PBPK model was first used to predict dose adjustments that are necessary to achieve similar exposure in the four stages of renal impairment (mild, moderate, severe, end stage renal disease) as in healthy controls. The predicted dose adjustment from 12 to 6 g for the moderate renal impairment category was then applied to the phase 1 clinical study. Subsequent validation of the PBPK model was achieved by comparing the model-predicted and clinically observed exposures in subjects with moderate renal impairment. In a phase 1, open-label study, trofinetide exposure was assessed in healthy (n = 10) and moderate renal impairment (n = 10) participants receiving single oral doses of 12 g or 6 g, respectively. Observed exposures [area under the blood concentration-time curve from time 0 to infinity (AUC_inf) and maximum concentration (C_max)] were compared with predicted exposures from simulations in virtual healthy and moderate renal impairment populations (n = 100) to validate a PBPK model of renal impairment that had previously predicted doses across renal impairment categories.

Results: Dose-normalized geometric mean ratios for C_max were comparable [1.02 (90% CI 0.69-1.50)] while AUC_inf was approximately two-fold higher [1.81 (90% CI 1.31-2.50)] in moderate renal impairment participants compared with healthy controls. These observed values closely aligned with predicted distributions. Treatment-emergent adverse events were reported in two (20.0%) participants with moderate renal impairment and four healthy participants (40.0%).

Conclusion: PBPK modeling of trofinetide in a virtual population with moderate renal impairment predicted a 50% dose reduction compared to individuals with normal renal function. Comparison of observed pharmacokinetic results from a phase 1 study in subjects with moderate renal impairment and matched healthy participants to the model-predicted exposures validated this dose reduction. No new safety concerns for trofinetide emerged.

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.