Semaglutide and Cardiovascular Outcomes in Obesity without Diabetes.

BACKGROUND: Semaglutide, a glucagon-like peptide-1 receptor agonist, has been shown to reduce the risk of adverse cardiovascular events in patients with diabetes. Whether semaglutide can reduce cardiovascular risk associated with overweight and obesity in the absence of diabetes is unknown. METHODS: In a multicenter, double-blind, randomized, placebo-controlled, event-driven superiority trial, we enrolled patients 45 years of age or older who had preexisting cardiovascular disease and a body-mass index (the weight in kilograms divided by the square of the height in meters) of 27 or greater but no history of diabetes. Patients were randomly assigned in a 1:1 ratio to receive once-weekly subcutaneous semaglutide at a dose of 2.4 mg or placebo. The primary cardiovascular end point was a composite of death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke in a time-to-first-event analysis. Safety was also assessed. RESULTS: A total of 17,604 patients were enrolled; 8803 were assigned to receive semaglutide and 8801 to receive placebo. The mean (±SD) duration of exposure to semaglutide or placebo was 34.2±13.7 months, and the mean duration of follow-up was 39.8±9.4 months. A primary cardiovascular end-point event occurred in 569 of the 8803 patients (6.5%) in the semaglutide group and in 701 of the 8801 patients (8.0%) in the placebo group (hazard ratio, 0.80; 95% confidence interval, 0.72 to 0.90; P<0.001). Adverse events leading to permanent discontinuation of the trial product occurred in 1461 patients (16.6%) in the semaglutide group and 718 patients (8.2%) in the placebo group (P<0.001). CONCLUSIONS: In patients with preexisting cardiovascular disease and overweight or obesity but without diabetes, weekly subcutaneous semaglutide at a dose of 2.4 mg was superior to placebo in reducing the incidence of death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke at a mean follow-up of 39.8 months. (Funded by Novo Nordisk; SELECT ClinicalTrials.gov number, NCT03574597.).

Esomeprazole FDA Approval in Children With GERD: Exposure-Matching and Exposure-Response.

OBJECTIVES: Food and Drug Administration approval of proton-pump inhibitors for infantile gastroesophageal reflux disease has been limited by intrapatient variability in the clinical assessment of gastroesophageal reflux disease. For children 1 to 17 years old, extrapolating efficacy from adults for IV esomeprazole was accepted. The oral formulation was previously approved in children. Exposure-response and exposure matching analyses were sought to identify approvable pediatric doses. METHODS: Intragastric pH biomarker comparisons between children and adults were conducted. Pediatric doses were selected to match exposures in adults and were based on population pharmacokinetic (PK) modeling and simulations with pediatric esomeprazole data. Observed IV or oral esomeprazole PK data were available from 50 and 117 children, between birth and 17 years, respectively, and from 65 adults, between 20 and 48 years. A population PK model developed using these data was used to simulate steady-state esomeprazole exposures for children at different doses to match the observed exposures in adults. RESULTS: Exposure-response relationships of intragastric pH measures were similar between children and adults. The PK simulations identified a dosing regimen for children that results in comparable steady-state area under the curve to that observed after 20 mg in adults. For IV esomeprazole, increasing the infusion duration to 10 to 30 minutes in children achieves matching Cmax values with adults. CONCLUSIONS: The exposure-matching analysis permitted approval of an esomeprazole regimen not studied directly in clinical trials. Exposure-response for intragastric pH-permitted approval for the treatment of gastroesophageal reflux disease in children in whom it was not possible to evaluate the adult primary endpoint, mucosal healing assessed by endoscopy.

Ethnic differences in insulin sensitivity, ß-cell function, and hepatic extraction between Japanese and Caucasians: a minimal model analysis.

CONTEXT: Ethnic differences have previously been reported for type 2 diabetes. OBJECTIVE: We aimed at assessing the potential differences between Caucasian and Japanese subjects ranging from normal glucose tolerance (NGT) to impaired glucose tolerance (IGT) and to type 2 diabetes. DESIGN: This was a cross-sectional study with oral glucose tolerance tests to assess ß-cell function, hepatic insulin extraction, and insulin sensitivity. PARTICIPANTS: PARTICIPANTS included 120 Japanese and 150 Caucasian subjects. MAIN OUTCOMES: Measures of ß-cell function, hepatic extraction, and insulin sensitivity were assessed using C-peptide, glucose, and insulin minimal models. RESULTS: Basal ß-cell function (Φ(b)) was lower in Japanese compared with Caucasians (P < .01). In subjects with IGT, estimates of the dynamic (Φ(d)) and static (Φ(s)) ß-cell responsiveness were significantly lower in the Japanese compared with Caucasians (P < .05). In contrast, values of insulin action showed higher sensitivity in the Japanese IGT subjects. Hepatic extraction was similar in NGT and IGT groups but higher in Japanese type 2 diabetic subjects (P < .01). Despite differences in insulin sensitivity, ß-cell function, and hepatic extraction, the disposition indices were similar between the 2 ethnic groups at all glucose tolerance states. Furthermore, the overall insulin sensitivity and ß-cell responsiveness for all glucose tolerance states were similar in Japanese and Caucasians after accounting for differences in body mass index. CONCLUSION: Our study provides evidence for a similar ability of Japanese and Caucasians to compensate for increased insulin resistance.

Dosing rationale for liraglutide in type 2 diabetes mellitus: a pharmacometric assessment.

The glucagon-like peptide-1 (GLP-1) receptor agonist liraglutide was approved in 2010 by the US Food and Drug Administration (FDA) as an adjunct treatment to diet and exercise to improve glycemic control in adults with type 2 diabetes mellitus. This article provides insights into the use of pharmacometric analyses for regulatory review with a focus on the dosing recommendations. The assessment was based on the totality of exploratory and confirmatory analysis of dose-finding and pivotal clinical data and was structured around a set of key questions in accordance with current FDA review practice. For the pharmacometric review of liraglutide, the key questions focused on exposure-response relationships for effects on fasting plasma glucose, hemoglobin A(1c), and calcitonin and on variability in exposure across demographic subgroups of patients. The importance of conducting exploratory exposure-response analysis and population pharmacokinetic studies in clinical drug development to support dosing recommendations is highlighted.

Population pharmacokinetic and concentration--QTc models for moxifloxacin: pooled analysis of 20 thorough QT studies.

To increase our understanding of important subject characteristics and design variables affecting the performance of oral moxifloxacin in thorough QT studies, population pharmacokinetic and concentration-QTc models were developed by pooling data from 20 studies. A 1-compartment model with first-order elimination described the pharmacokinetics. Absorption delay was modeled using 8 transit compartments. Mean (95% confidence interval) values for oral clearance, apparent volume of distribution, the first-order absorption rate constant, and mean transit time were 11.7 (11.5-11.9) L/h, 147 (144-150) L, 1.9 (1.7-2.1) 1/h, and 0.3 (0.28-0.34) hours, respectively. Overencapsulating the moxifloxacin tablet increased mean transit time by 138% and delayed time to maximum concentration by 0.5 hours but had a minimal effect on overall exposure. Administration with food decreased absorption rate constant by 27%. Women had higher moxifloxacin exposure compared with men, which was explained by lower body weights. A linear model described the concentration-QTc relationship with a mean slope of 3.1 (2.8-3.3) milliseconds per µg/mL moxifloxacin. Mean slopes for individual studies ranged from 1.6 to 4.8 milliseconds per µg/mL. Hysteresis between moxifloxacin plasma concentrations and QTc was modest, and incorporating this delay did not result in a different slope (3.3 milliseconds per µg/mL). There were no differences in slope estimates between men and women or among race categories.

Creation of a knowledge management system for QT analyses.

An increasing number of thorough QT (TQT) reports are being submitted to the US Food and Drug Administration's interdisciplinary review team for QT (IRT-QT), requiring time-intensive quantitative analyses by a multidisciplinary review team within 45 days. This calls for systematic learning to guide future trials and policies by standardizing and automating the QT analyses to improve review efficiency, provide consistent advice, and enable pooled data analyses to answer key regulatory questions. The QT interval represents the time from initiation of ventricular depolarization to completion of ventricular repolarization recorded by electrocardiograph (ECG) and is used in the proarrhythmic risk assessment. The developed QT knowledge management system is implemented in the R package "QT." Data from 11 crossover TQT studies including time-matched ECGs and pharmacokinetic measurements following single doses of 400 to 1200 mg moxifloxacin were used for the QT analysis example. The automated workflow was divided into 3 components (data management, analysis, and archival). The generated data sets, scripts, tables, and graphs are automatically stored in a queryable repository and summarized in an analysis report. More than 100 TQT studies have been analyzed using the system since 2007. This has dramatically reduced the time needed to review TQT studies and has made the IRT-QT reviews consistent across reviewers. Furthermore, the system enables leveraging prior knowledge through pooled data analyses to answer policy-related questions and to understand the various effects that influence study results.

Pharmacometrics-based dose selection of levofloxacin as a treatment for postexposure inhalational anthrax in children.

Levofloxacin was recently (May 2008) approved by the U.S. Food and Drug Administration as a treatment for children following inhalational exposure to anthrax. Given that no clinical trials to assess the efficacy of a chosen dose was conducted, the basis for the dose recommendation was based upon pharmacometric analyses. The objective of this paper is to describe the basis of the chosen pediatric dose recommended for the label. Pharmacokinetic (PK) data from 90 pediatric patients receiving 7 mg/kg of body weight levofloxacin and two studies of 47 healthy adults receiving 500 and 750 mg/kg levofloxacin were used for the pharmacometric analyses. Body weight was found to be a significant covariate for levofloxacin clearance and the volume of distribution. Consistently with developmental physiology, clearance also was found to be reduced in pediatric patients under 2 years of age due to immature renal function. Different dosing regimens were simulated to match adult exposure (area under the concentration-time curve from 0 to 24 h at steady state, maximum concentration of drug in serum at steady state, and minimum concentration of drug in serum at steady state) following the approved adult dose of 500 mg once a day. The recommended dose of 8 mg/kg twice a day was found to match the exposure of the dose approved for adults in a manner that permitted confidence that this dose in children would achieve efficacy comparable to that of adults.

Concentration-QT relationships play a key role in the evaluation of proarrhythmic risk during regulatory review.

The criterion for assessing whether a drug prolongs QT as described in the International Conference on Harmonization topic E14 guideline does not explicitly account for individual drug concentrations. The authors' experience with reviewing QT studies indicates that understanding the relationship, if any, between individual drug concentration and QT change provides important additional information to support regulatory decision making. Therefore, regulatory reviews of "thorough QT" studies routinely include a characterization of the concentration-QT relationship. The authors provide examples to illustrate how the concentration-QT relationship has been used to plan and interpret the thorough QT study, to evaluate QT risk for drugs that have no thorough QT studies, to assess QT risk in subpopulations, to make dose adjustments, and to write informative drug labels.

Optimising piperacillin/tazobactam dosing in paediatrics.

Piperacillin/tazobactam, an intravenous antibacterial combination product, has recently been approved for paediatric (age 2 months to 17 years) use in the USA. The purpose of this analysis is to describe the basis for the dosing recommendations in this age group. Pharmacokinetic (PK) parameters and demographic covariates from 53 children enrolled in two paediatric studies were used in the analysis. Individual drug clearance (CL) values calculated by non-compartmental methods were available. The influence of demographic covariates on CL was investigated by non-linear regression. The analysis identified CL to be dependent on body weight. CL was also found to be influenced by age in paediatric patientsor=9 months, a dose of 100/12.5 mg/kg every 8h showed exposures similar to adults; for paediatric patients aged 2-9 months, the dose of 100/12.5 mg/kg should be reduced by a factor of 0.8 (i.e. 80/10 mg/kg), likely due to immature renal function. Based upon this analysis, dosing recommendations for paediatric patients down to 2 months of age were incorporated in the labelling. No data were available to allow additional recommendations for paediatric patients<2 months of age to be made.

Population pharmacokinetic/pharmacodynamic (PK/PD) modelling of the hypothalamic-pituitary-gonadal axis following treatment with GnRH analogues.

AIMS: To develop a population pharmacokinetic/pharmacodynamic (PK/PD) model of the hypothalamic-pituitary-gonadal (HPG) axis describing the changes in luteinizing hormone (LH) and testosterone concentrations following treatment with the gonadotropin-releasing hormone (GnRH) agonist triptorelin and the GnRH receptor blocker degarelix. METHODS: Fifty-eight healthy subjects received single subcutaneous or intramuscular injections of 3.75 mg of triptorelin and 170 prostate cancer patients received multiple subcutaneous doses of degarelix of between 120 and 320 mg. All subjects were pooled for the population PK/PD data analysis. A systematic population PK/PD model-building framework using stochastic differential equations was applied to the data to identify nonlinear dynamic dependencies and to deconvolve the functional feedback interactions of the HPG axis. RESULTS: In our final PK/PD model of the HPG axis, the half-life of LH was estimated to be 1.3 h and that of testosterone 7.69 h, which corresponds well with literature values. The estimated potency of LH with respect to testosterone secretion was 5.18 IU l(-1), with a maximal stimulation of 77.5 times basal testosterone production. The estimated maximal triptorelin stimulation of the basal LH pool release was 1330 times above basal concentrations, with a potency of 0.047 ng ml(-1). The LH pool release was decreased by a maximum of 94.2% by degarelix with an estimated potency of 1.49 ng ml(-1). CONCLUSIONS: Our model of the HPG axis was able to account for the different dynamic responses observed after administration of both GnRH agonists and GnRH receptor blockers, suggesting that the model adequately characterizes the underlying physiology of the endocrine system.

Semi-mechanistic pharmacodynamic modeling for degarelix, a novel gonadotropin releasing hormone (GnRH) blocker.

An integrated semi-mechanistic pharmacodynamic (PD) model describing the relationship between luteinizing hormone (LH) and testosterone (T) after short-term administration of degarelix was developed. Data from three clinical studies involving, intravenous (IV) and subcutaneous (SC) dosing, in healthy male subjects were available. Degarelix pharmacokinetic (PK) data from all studies were modeled simultaneously. One intravenous study was used to develop the PD model and the two other studies (IV and SC dosing) were used to qualify the model. Degarelix PK follows a two-compartment model and exhibits flip-flop kinetics after subcutaneous dosing. Based on physiological mechanism, the gonadotropin releasing hormone (GnRH) time course was described using a pulsatile release model. A precursor-dependent pool model was used to describe the kinetics of LH in the pituitary and plasma compartment. In males, LH regulates T production in leydig cells. Degarelix inhibits the release of LH from the pool compartment to the plasma compartment leading to decreased T production. The plasma half-life of LH (2.6-3.3 hr) and T (2.7 hr) match well with the literature reports. The proposed PD model reasonably described the time course of LH and T including the LH rebound for short-term studies. The model predicted the time course of LH and T for the second IV and SC dosing studies very well. However, the long term simulations from the final model did not match with literature reports. A modification is suggested based on the physiological understanding of the system. The proposed novel modification to precursor models can be of general use for predicting long term responses.

Non-linear mixed-effects models with stochastic differential equations: implementation of an estimation algorithm.

Pharmacokinetic/pharmacodynamic modelling is most often performed using non-linear mixed-effects models based on ordinary differential equations with uncorrelated intra-individual residuals. More sophisticated residual error models as e.g. stochastic differential equations (SDEs) with measurement noise can in many cases provide a better description of the variations, which could be useful in various aspects of modelling. This general approach enables a decomposition of the intra-individual residual variation epsilon into system noise w and measurement noise e. The present work describes implementation of SDEs in a non-linear mixed-effects model, where parameter estimation was performed by a novel approximation of the likelihood function. This approximation is constructed by combining the First-Order Conditional Estimation (FOCE) method used in non-linear mixed-effects modelling with the Extended Kalman Filter used in models with SDEs. Fundamental issues concerning the proposed model and estimation algorithm are addressed by simulation studies, concluding that system noise can successfully be separated from measurement noise and inter-individual variability.

Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations.

PURPOSE: The objective of the present analysis was to explore the use of stochastic differential equations (SDEs) in population pharmacokinetic/pharmacodynamic (PK/PD) modeling. METHODS: The intra-individual variability in nonlinear mixed-effects models based on SDEs is decomposed into two types of noise: a measurement and a system noise term. The measurement noise represents uncorrelated error due to, for example, assay error while the system noise accounts for structural misspecifications, approximations of the dynamical model, and true random physiological fluctuations. Since the system noise accounts for model misspecifications, the SDEs provide a diagnostic tool for model appropriateness. The focus of the article is on the implementation of the Extended Kalman Filter (EKF) in NONMEM for parameter estimation in SDE models. RESULTS: Various applications of SDEs in population PK/PD modeling are illustrated through a systematic model development example using clinical PK data of the gonadotropin releasing hormone (GnRH) antagonist degarelix. The dynamic noise estimates were used to track variations in model parameters and systematically build an absorption model for subcutaneously administered degarelix. CONCLUSIONS: The EKF-based algorithm was successfully implemented in NONMEM for parameter estimation in population PK/PD models described by systems of SDEs. The example indicated that it was possible to pinpoint structural model deficiencies, and that valuable information may be obtained by tracking unexplained variations in parameters.

Non-linear mixed-effects pharmacokinetic/pharmacodynamic modelling in NLME using differential equations.

The standard software for non-linear mixed-effect analysis of pharmacokinetic/pharmacodynamic (PK/PD) data is NONMEM while the non-linear mixed-effects package NLME is an alternative as long as the models are fairly simple. We present the nlmeODE package which combines the ordinary differential equation (ODE) solver package odesolve and the non-linear mixed effects package NLME thereby enabling the analysis of complicated systems of ODEs by non-linear mixed-effects modelling. The pharmacokinetics of the anti-asthmatic drug theophylline is used to illustrate the applicability of the nlmeODE package for population PK/PD analysis using the available data analysis tools in R for model inspection and validation. The nlmeODE package is numerically stable and provides accurate parameter estimates which are consistent with NONMEM estimates.

Population pharmacokinetic modeling of a subcutaneous depot for GnRH antagonist degarelix.

PURPOSE: The objective of this study is to develop a population pharmacokinetic (PK) model that describes the subcutaneous (SC) depot formation of gonadotropin-releasing hormone (GnRH) antagonist degarelix, which is being developed for treatment of prostate cancer, exhibiting dose-volume and dose-concentration dependent absorption. METHODS: The PK analysis is made in NONMEM through joint analysis of data from two phase I clinical studies; an intravenous infusion study and a single SC dose escalation study. The SC absorption is modeled using an approximation to Ficks' second law of diffusion out of a spherical depot. The dose-volume effect on the SC release is estimated using a B-spline basis whereas the bioavailability is modeled as a function of the dose-concentration. RESULTS: The SC depot model is approximated by using two concentric spherical compartments for the SC absorption combined with a two-compartment disposition model. The results indicate that the volume effect is most apparent at low injection volumes whereas the effect is diminishing at higher injection volumes. The dose-concentration effect on the bioavailability is estimated to decrease at increasing dose-concentrations. CONCLUSIONS: The presented SC depot model describes the PK profile of GnRH antagonist degarelix. This modeling approach might also be applicable for other depot-formulated drugs exhibiting complex PK profiles.

Grey-box modelling of pharmacokinetic/pharmacodynamic systems.

Grey-box pharmacokinetic/pharmacodynamic (PK/PD) modelling is presented as a promising way of modelling PK/PD systems. The concept behind grey-box modelling is based on combining physiological knowledge along with information from data in the estimation of model parameters. Grey-box modelling consists of using stochastic differential equations (SDEs) where the stochastic term in the differential equations represents unknown or incorrectly modelled dynamics of the system. The methodology behind the grey-box PK/PD modelling framework for systematic model improvement is illustrated using simulated data and furthermore applied to Bergman's minimal model of glucose kinetics using clinical data from an intravenous glucose tolerance test (IVGTT). The grey-box estimates of the stochastic system noise parameters indicate that the glucose minimal model is too simple and should preferably be revised in order to describe the complicated in vivo system of insulin and glucose following an IVGTT.

Pharmacokinetic/pharmacodynamic modelling of GnRH antagonist degarelix: a comparison of the non-linear mixed-effects programs NONMEM and NLME.

In this paper, the two non-linear mixed-effects programs NONMEM and NLME were compared for their use in population pharmacokinetic/pharmacodynamic (PK/PD) modelling. We have described the first-order conditional estimation (FOCE) method as implemented in NONMEM and the alternating algorithm in NLME proposed by Lindstrom and Bates. The two programs were tested using clinical PK/PD data of a new gonadotropin-releasing hormone (GnRH) antagonist degarelix currently being developed for prostate cancer treatment. The pharmacokinetics of intravenous administered degarelix was analysed using a three compartment model while the pharmacodynamics was analysed using a turnover model with a pool compartment. The results indicated that the two algorithms produce consistent parameter estimates. The bias and precision of the two algorithms were further investigated using a parametric bootstrap procedure which showed that NONMEM produced more accurate results than NLME together with the nlmeODE package for this specific study.