Journal of Clinical Pharmacology最新文献

Population pharmacokinetics (PK) and exposure-response (E-R) analyses were conducted to compare the PK and E-R relationships of golimumab between children and adults with ulcerative colitis. PK data following subcutaneous golimumab administration to children with ulcerative colitis (6-17 years) in the PURSUIT-PEDS-PK study, adults with ulcerative colitis in the PURSUIT study, and children with pediatric polyarticular juvenile idiopathic arthritis (2-17 years) in the GO-KIDS study, were included in the population PK analysis. E-R analysis was conducted using logistic regression to link serum golimumab concentration and Mayo score-based efficacy outcomes in pediatric and adult ulcerative colitis. Golimumab PK was adequately described by a 1-compartment model with first-order absorption and elimination. Golimumab apparent clearance and volume of distribution increased with body weight. Golimumab apparent clearance was higher in patients with lower serum albumin, no methotrexate use, and positive antibodies to golimumab; age was not an influential factor after accounting for body weight. Model-estimated terminal half-life (9.2 days in children; 9.5 days in adults) and other PK parameters suggest that golimumab PK properties are generally comparable between children and adults with ulcerative colitis. Simulations suggest that a higher induction dose than that tested in PURSUIT-PEDS-PK may be needed for children ≤45 kg to achieve exposures comparable to adults. Comparable E-R relationships between children and adults with ulcerative colitis were observed, although children appeared to be more responsive for the more stringent remission end point. The overall comparable PK and E-R relationships between children and adults support the extrapolation of golimumab efficacy from the adult to the pediatric ulcerative colitis population.

Although current quetiapine labeling recommends that its dosage should be lowered 6-fold when coadministered with strong cytochrome P450 (CYP)3A inhibitors, a reported case of coma in a patient receiving quetiapine with lopinavir and ritonavir prompted the reevaluation of labeling recommendations for the dosing of quetiapine when coadministered with human immunodeficiency virus (HIV) protease inhibitors. Literature and database (FDA Adverse Event Reporting System and United States Symphony Health Solutions' Integrated Dataverse Database) searches allowed us to identify cases of coma and related adverse events involving the coadministration of quetiapine and HIV protease inhibitors and to estimate the frequency of concomitant use. Literature review and physiologically based pharmacokinetic modeling allowed us to estimate the potential for CYP3A inhibition to contribute to adverse events related to HIV protease inhibitor-quetiapine coadministration. We identified excess sedation following coadministration of quetiapine and an HIV protease inhibitor in 3 reports without obvious confounders. In prescription claims data, 0.4% of quetiapine patients were dispensed a concurrent ritonavir prescription. The quetiapine dose was not reduced on ritonavir initiation in 90% of therapy episodes. Available data indicate to us that all HIV protease inhibitors combined with ritonavir are likely to be strong CYP3A inhibitors. We predicted that ritonavir would increase quetiapine exposure comparable to the strong CYP3A inhibitor ketoconazole. The current dosing recommendations for use of quetiapine with strong CYP3A inhibitors (ie, 6-fold lower quetiapine dose) are appropriate and should be followed when quetiapine is coadministered with HIV protease inhibitors.

Rolapitant (Varubi) is a neurokinin-1 receptor antagonist approved for the prevention of chemotherapy-induced nausea and vomiting. Rolapitant is primarily metabolized by the cytochrome P450 3A4 (CYP3A4) enzyme. Unlike other neurokinin-1 receptor antagonists, rolapitant is neither an inhibitor nor an inducer of CYP3A4 in vitro. The objective of this analysis was to examine the pharmacokinetics of rolapitant in healthy subjects and assess drug-drug interactions between rolapitant and midazolam (a CYP3A substrate), ketoconazole (a CYP3A inhibitor), or rifampin (a CYP3A4 inducer). Three phase 1, open-label, drug-drug interaction studies were conducted to examine the pharmacokinetic interactions of orally administered rolapitant with midazolam, rolapitant with ketoconazole, and rolapitant with rifampin. The pharmacokinetic profiles of midazolam and 1-hydroxy midazolam metabolites were essentially unchanged when coadministered with rolapitant, indicating the lack of a clinically relevant inhibition or induction of CYP3A by rolapitant. Coadministration of ketoconazole with rolapitant had no effects on rolapitant maximum concentration and resulted in an approximately 20% increase in the area under the concentration-time curve of rolapitant, suggesting that strong CYP3A inhibitors have minimal inhibitory effects on rolapitant exposure. Repeated administrations of rifampin appeared to reduce rolapitant exposure, resulting in a 33% decrease in maximum concentration and 87% decrease in area under the concentration-time curve from time zero to infinity. Coadministration of rolapitant did not affect the exposure of midazolam. Rifampin coadministration resulted in lower concentrations of rolapitant, and ketoconazole coadministration had no or minimal effects on rolapitant exposure. Rolapitant was safe and well tolerated when coadministered with ketoconazole, rifampin, or midazolam. No new safety signals were reported compared with previous studies of rolapitant.

NEPA is the first fixed-combination antiemetic composed of the neurokinin-1 receptor antagonist netupitant (netupitant; 300 mg) and the 5-hydroxytryptamine-3 receptor antagonist palonosetron (palonosetron; 0.50 mg). This study evaluated the pharmacokinetic profiles of netupitant and palonosetron. The pharmacokinetic profiles of both drugs were summarized using data from phase 1-3 clinical trials. netupitant and palonosetron have high absolute bioavailability (63%-87% and 97%, respectively). Their overall systemic exposures and maximum plasma concentrations are similar under fed and fasting conditions. netupitant binds to plasma proteins in a high degree (>99%), whereas palonosetron binds to a low extent (62%). Both drugs have large volumes of distribution (cancer patients: 1656-2257 L and 483-679 L, respectively). netupitant is metabolized by cytochrome P450 3A4 to 3 major pharmacologically active metabolites (M1, M2, and M3). palonosetron is metabolized by cytochrome P450 2D6 to 2 major substantially inactive metabolites (M4 and M9). Both drugs have similar intermediate-to-low systemic clearances and long half-lives (cancer patients: netupitant, 19.5-20.8 L/h and 56.0-93.8 hours; palonosetron: 7.0-11.3 L/h and 43.8-65.7 hours, respectively). netupitant and its metabolites are eliminated via the hepatic/biliary route (87% of the administered dose), whereas palonosetron and its metabolites are mainly eliminated via the kidneys (85%-93%). Altogether, these data explain the lack of pharmacokinetic interactions between netupitant and palonosetron at absorption, binding, metabolic, or excretory level, thus highlighting their compatibility as the oral fixed combination NEPA, with administration convenience that may reduce dosing mistakes and increase treatment compliance.

High-dose methotrexate (>0.5 g/m² ) is among the first-line chemotherapeutic agents used in treating acute lymphoblastic leukemia (ALL) and osteosarcoma in children. Despite rapid hydration, leucovorin rescue, and routine therapeutic drug monitoring, severe toxicity is not uncommon. This study aimed at developing population pharmacokinetic (popPK) models of high-dose methotrexate for ALL and osteosarcoma and demonstrating the possibility and convenience of popPK model-based individual dose optimization using R and shiny, which is more accessible, efficient, and clinician-friendly than NONMEM. The final data set consists of 36 ALL (354 observations) and 16 osteosarcoma (585 observations) patients. Covariate model building and parameter estimations were done using NONMEM and Perl-speaks-NONMEM. Diagnostic Plots and bootstrapping validated the models' performance and stability. The dose optimizer developed based on the validated models can obtain identical individual parameter estimates as NONMEM. Compared to calling a NONMEM execution and reading its output, estimating individual parameters within R reduces the execution time from 8.7-12.8 seconds to 0.4-1.0 second. For each subject, the dose optimizer can recommend (1) an individualized optimal dose and (2) an individualized range of doses. For osteosarcoma, recommended optimal doses by the optimizer resemble the final doses at which the subjects were eventually stabilized. The dose optimizers developed demonstrated the potential to inform dose adjustments using a model-based, convenient, and efficient tool for high-dose methotrexate. Although the dose optimizer is not meant to replace clinical judgment, it provides the clinician with the individual pharmacokinetics perspective by recommending the (range of) optimal dose.

Amitriptyline is a tricyclic antidepressant that is metabolized mainly by CYP2C19 and CYP2D6 enzymes. Higher plasma levels of amitriptyline and its active metabolite, nortriptyline, are associated with an increased risk of adverse events including anticholinergic effects. The aim of this study was to evaluate the effects of CYP2C19 and CYP2D6 genetic polymorphisms on amitriptyline and nortriptyline pharmacokinetics. Twenty-four Korean healthy adult male volunteers were enrolled in the study after stratification by their CYP2C19 and CYP2D6 genotypes. Serial blood draws for pharmacokinetic analysis were made after a single oral 25-mg dose of amitriptyline was administered. Plasma amitriptyline and nortriptyline concentrations were measured by a validated liquid chromatography with tandem mass spectrometry. Population pharmacokinetic modeling analysis was conducted using NONMEM, which evaluated the effects of CYP2C19 and CYP2D6 genotypes on amitriptyline and nortriptyline pharmacokinetics. The biotransformation of amitriptyline into nortriptyline was significantly different between subjects with the CYP2C19*2/*2, *2/*3, and *3/*3 genotypes and those with the other genotypes, with an estimated metabolic clearance of 17 and 61.5 L/h, respectively. Clearance of amitriptyline through pathways other than biotransformation into nortriptyline was estimated as 18.8 and 30.6 L/h for subjects with the CYP2D6*10/*10 and *10/*5 genotypes and those with the other genotypes, respectively. This study demonstrated a quantitative effect of the CYP2C19 and CYP2D6 genotypes on amitriptyline and nortriptyline pharmacokinetics. Production of nortriptyline from amitriptyline was associated with CYP2C19 genotypes, and clearance of amitriptyline through pathways other than biotransformation into nortriptyline was associated with CYP2D6 genotypes. These observations may be useful in developing individualized, optimal therapy with amitriptyline.

The combination regimen of daclatasvir, asunaprevir, and beclabuvir has been developed for the treatment of hepatitis C virus infection. The objectives of this analysis were to characterize the relationship between the exposures of the daclatasvir, asunaprevir, and beclabuvir regimen and liver-related laboratory elevations (Grade 3 or 4 alanine aminotransferase [ALT] and total bilirubin [Tbili]), and to evaluate the impact of selected covariates on the exposure-response relationships. The exposure-response analysis was performed with data from 1 phase 2 and 3 phase 3 studies in hepatitis C virus-infected subjects. The probability of liver-related laboratory elevations were modeled using linear logistic regression. Selected covariates were tested using a forward-addition and backward-elimination approach. The final model for ALT elevation included Asian race, body weight in non-Asian subjects, and asunaprevir exposure. The final model for Tbili elevation included Asian race, fibrosis score (F0-F3 or F4) and asupanprevir exposure. Asian subjects had greater the Grade 3 or 4 ALT and Tbili elevation rates than non-Asians. The Grade 3 or 4 ALT elevation rate increased with decreasing body weight in non-Asian subjects. Subjects with F4 fibrosis score had a higher rate of Grade 3 or 4 Tbili elevation compared to subjects with F0 to F3 fibrosis score. Higher asunaprevir exposure was associated with increases in Grade 3 or 4 ALT and Tbili elevation rates; however, the impact on the ALT elevation was not clinically relevant and the effect on Tbili elevation was smaller than the other significant covariates.

Extraparenchymal neurocysticercosis is the most severe form of cysticercosis, and response to treatment is suboptimal. We sought to determine how demographic and clinical characteristics and albendazole sulfoxide concentrations were related to cysticidal treatment response. We conducted a longitudinal study of 31 participants with extraparenchymal vesicular parasites who received the same treatment, albendazole 30 mg/kg/day for 10 days with dexamethasone 0.4 mg/kg/day for 13 days, followed by a prednisone taper. Response to treatment was determined by parasite volumes before and 6 months after treatment. Eight participants (25.8%) had a complete treatment response, 16 (51.6%) had a treatment response > 50% but < 100%, and 7 (22.6%) had a treatment response < 50%. Complete treatment response was significantly associated with higher concentrations of albendazole sulfoxide (P = .032), younger age (P = .032), fewer cysts (P = .049) and lower pretreatment parasite volume (P = .037). Higher number of previous cysticidal treatment courses was associated with a noncomplete treatment response (P = .023). Although the large proportion of participants with less than a complete response emphasizes the need to develop more efficacious pharmacologic regimens, the association of albendazole sulfoxide concentrations with treatment response highlights the importance of optimizing existing therapeutic regimens. In addition, the association of treatment response with parasite volume emphasizes the importance of early diagnosis.

The aim of the present study is to establish a population pharmacokinetic (PPK) model of mycophenolic acid (MPA) and limited sampling strategy models for the estimation of MPA exposure in Chinese adult renal allograft recipients following oral administration of enteric coated mycophenolate sodium (EC-MPS). A total of 74 sets of full pharmacokinetic profiles and 47 sets of MPA-sparing samples were collected from 102 renal transplant recipients who received oral EC-MPS. The MPA concentration was determined by an enzyme-multiplied immunoassay technique, and the pathophysiologic data were recorded. The PPK model was constructed using nonlinear mixed-effects modeling, and the limited sampling strategy models for MPA were established by using multiple regression analysis and the maximum a posteriori Bayesian assay based on 2 to 4 sampling time points following EC-MPS administration. The pharmacokinetics of MPA were best described by a 2-compartment model with a first-order absorption process and a lag time of absorption. The clearance of MPA was 12.3 ± 1.14 L/h. Comedicating with cyclosporine A was found to have a significant impact on the clearance/bioavailability of MPA (P < .01). Sampling strategies consisted of plasma concentration at 1.5, 2, 4 (C1.5-C2-C4) hours and 1.5, 2, 4, 6 (C1.5-C2-C4-C6) hours after EC-MPS administration were shown to be suitable for the estimation of the MPA area under the concentration-time curve in these patients. The PPK model was acceptable and can describe the pharmacokinetics of MPA in Chinese renal transplant recipients administered EC-MPS. The area under the concentration-time curve of MPA in Chinese renal transplant recipients could be estimated through a limited sampling strategy method, based on which individualized immunosuppressive regimens could be designed.

Upadacitinib is a novel selective oral Janus kinase 1 (JAK) inhibitor being developed for treatment of several inflammatory diseases. Oral contraceptives are anticipated to be a common concomitant medication in the target patient populations. This study was designed to evaluate the effect of multiple doses of upadacitinib on the pharmacokinetics of ethinylestradiol and levonorgestrel in healthy female subjects. This phase I, single-center, open-label, 2-period crossover study evaluated the effect of multiple doses of 30 mg once daily extended-release upadacitinib on the pharmacokinetics of a single oral dose of ethinylestradiol/levonorgestrel (0.03/0.15 mg; administered alone in period 1 and on day 12 of a 14-day regimen of upadacitinib in period 2) in 22 healthy female subjects. The ratios (90% confidence intervals) for maximum plasma concentration and area under the plasma drug concentration-time curve from time zero to infinity following administration of ethinylestradiol/levonorgestrel with upadacitinib compared with administration of ethinylestradiol/ levonorgestrel alone were 0.96 (0.89-1.02) and 1.1 (1.04-1.19), respectively, for ethinylestradiol, and 0.96 (0.87-1.06) and 0.96 (0.85-1.07), respectively, for levonorgestrel. The harmonic mean terminal half-life for ethinylestradiol (7.7 vs 7.0 hours) and levonorgestrel (37.1 vs 33.1 hours) was similar in the presence and absence of upadacitinib. Ethinylestradiol and levonorgestrel were bioequivalent in the presence and absence of upadacitinib. Therefore, upadacitinib can be administered concomitantly with oral contraceptives containing ethinylestradiol or levonorgestrel.