The validity of pharmacokinetic parameters estimated by the maximum a posteriori probability (MAP) Bayesian method was investigated by simulation studies. A 1-compartment model with bolus intravenous administration was used as a pharmacokinetic model, and the coefficients of variation for the parameters and residual error were set at 30% and 10%, respectively. The accuracy of the posterior modes of pharmacokinetic parameters estimated by the MAP Bayesian method was assessed by the difference between the true value and the estimated value. The results showed that the accuracy of the Bayesian estimation depended on sampling times and on the differences between the prior means and individual true parameter values. For assessing the reliability and accuracy of the Bayesian estimation, the authors suggest using the whole posterior distribution of the pharmacokinetic parameters to describe the 95th percentile range for predicted blood concentration profiles. The authors believe that the proposed procedures provide helpful information for evaluating the Bayesian estimation of pharmacokinetic profiles.
A study was conducted to clarify differences in the theophylline pharmacokinetics of two orally available products, theophylline alcohol and Apnecut, in premature neonates and infants using population pharmacokinetic analysis. Fifty-two patients with apnea hospitalized at the National Center for Child Health and Development were enrolled (total number of plasma concentration points=90). Population pharmacokinetic analysis under steady-state conditions was performed using NONMEM ver. V. The mean oral clearance was 0.0249 (l/h), and the inter- and intraindividual variation was 30.3% and 28.3%, respectively, in the basic model. The oral clearance was significantly affected by body weight, sex, and age. The final model obtained was expressed by the following equation: oral clearance (l/h)=0.0201 x (body weight (g)/1000)(1.08)x (1-0.282 x drug product), where theophylline alcohol is 0 and Apnecut is 1. The inter- and intraindividual variations in the final model were 15.0% and 15.3%, respectively. The oral clearance of the two oral formulations differed significantly, and this difference should be considered when adjusting the theophylline dose.
Tofacitinib is an oral Janus kinase inhibitor for the treatment of psoriatic arthritis (PsA). These post hoc exposure-response (E-R) analyses of pooled data from two Phase 3 studies (NCT01877668 and NCT01882439) characterized the relationships between tofacitinib exposure and efficacy (American College of Rheumatology [ACR] criteria), and changes in hemoglobin (Hgb) in patients with PsA. Efficacy data for the proportion of patients receiving tofacitinib 5 or 10 mg twice daily, or placebo, achieving ACR ≥20%, ≥50%, or ≥70% response criteria (ACR20, ACR50, and ACR70, respectively) at Month 3, were modeled jointly using a four-category ordered categorical exposure-response model (ACR20 non-responder, ACR20 responder but not ACR50 responder, ACR50 responder but not ACR70 responder, and ACR70 responder). A maximum drug effect (E
Tofacitinib is an oral, small molecule Janus kinase inhibitor for the treatment of ulcerative colitis (UC). We report a model-informed drug development approach for bridging efficacy from immediate-release (IR) to extended-release (XR) tofacitinib formulations in patients with UC. IR-XR efficacy bridging was supported by exposure-response analysis of phase 3 induction/maintenance studies of the IR formulation in UC to identify exposure metrics relevant for efficacy. Pharmacokinetic studies in healthy subjects were used to confirm similarity of relevant exposure metrics of tofacitinib IR 5 mg twice daily to XR 11 mg once daily, and tofacitinib IR 10 mg twice daily to XR 22 mg once daily, thereby bridging efficacy between IR and XR formulations. Food effect was evaluated at both XR formulation dose levels. Exposure-response analysis demonstrated that area under the plasma concentration-time curve (average plasma concentration) was a relevant predictor of efficacy. Pharmacokinetic studies demonstrated that area under the plasma concentration-time curve was equivalent between formulations under single-dose and steady-state conditions, and other exposure metrics were also similar. These results also supported bridging of safety data for IR-XR formulations. Food had no impact on tofacitinib XR exposure. These data support efficacy/safety bridging of IR-XR formulations in patients with UC.
Introduction: Serum albumin concentration was shown to be inversely related to drug clearance for biologic therapies for IBD [1-3]. Lower albumin levels may be linked to higher drug clearance rates and poorer clinical outcomes for some biologics [4]. Albumin levels as a predictor of efficacy in patients (pts) receiving tofacitinib is uncertain. Methods: Tofacitinib is an oral, small molecule JAK inhibitor for the treatment of ulcerative colitis (UC). We evaluated the effect of baseline albumin (BALB) on tofacitinib pharmacokinetics (PK) and efficacy. 4 randomized, placebo-controlled studies of tofacitinib in pts with moderate to severe UC were included in PK analyses: 1 Phase (P) 2 study (A3921063, NCT00787202) [5] and 3 P3 studies (OCTAVE Induction 1 & 2, NCT01465763 & NCT01458951; OCTAVE Sustain, NCT01458574) [6].The base PK model was 1-compartmental disposition with covariates for BALB, evaluated as a potential predictor for apparent oral clearance (CL/F). A multivariate analysis evaluated BALB related to efficacy endpoints in P3 induction/maintenance studies. Results: PK analysis comprised 1096 pts: 641 males, 455 females; median age 40 years; the majority (81.3%) were white. Mean (standard deviation) BALB was 4.18 g/dL (0.39); range 2.1-5.4 g/dL. In the population PK (popPK) model, BALB was evaluated as a predictor of individual CL/F. It showed no statistically significant correlation, and was therefore not included in the final popPK model. BALB concentration evaluated as a covariate in exposure-response (ER) efficacy analyses was non-significant in stepwise covariate modeling, and was not included in the final ER model. Multivariate ER analysis showed no statistically significant correlation between BALB and efficacy endpoints (based on central read) after accounting for other significant efficacy predictors, ie baseline Mayo score. Conclusion: In contrast to biologic therapies [1-3], tofacitinib clearance was not related to albumin concentration. Multivariate analysis showed that BALB had no effect on efficacy endpoints, so may not be informative to tofacitinib dosing decisions.
PK-PD model is one of the most effective tools for understanding relationship between drug concentration profile and pharmacological. effect. However PK-PD analysis needs different techniques from PK and statistical model analyses. In this article, I introduce several points to consider for conducting PK-PD analysis effectively.
Artificial intelligence (AI) has come to be used in various technological fields in recent years. However, there have been no reports of AI-designed clinical trials. In this study, we tried to develop study designs by a genetic algorithm (GA), which is an AI solution for combination optimization problems. Specifically, the computational design approach was applied to optimize the blood sampling schedule for a bioequivalence (BE) study in pediatrics and optimize the allocation of dose groups for a dose-finding study. The GA could reduce the number of blood collection points from 15 (typical standard) to seven points without meaningful impact on the accuracy and precision of the pharmacokinetic estimation for the pediatric BE study. For the dose-finding study, up to 10% reduction of the total number of required subjects from the standard design could be achieved. The GA also created a design that would lead to a drastic reduction of the required number of subjects in the placebo arm while keeping the total number of subjects at a minimum level. These results indicated the potential usefulness of the computational clinical study design approach for innovative drug development.
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