Temporal stability of child growth associations in Demographic and Health Surveys in 25 countries.

Background: Socio-economic and demographic determinants of child growth at ages 0-5 years in developing countries are well documented. However, Precision Public Health interventions and population targeting require more finely grained knowledge about the existence and character of temporal changes in child growth associations.

Methods: We evaluated the temporal stability of associations between height-for-age z-score (HAZ) of children aged 0-59 months and child, parental, household, and community and infrastructure factors by following 25 countries over time (1991-2014) in repeated cross-sections of 91 Demographic and Health Surveys using random effect models and Wald tests.

Exposure-Response Model of Subcutaneous C1-Inhibitor Concentrate to Estimate the Risk of Attacks in Patients With Hereditary Angioedema.

Subcutaneous C1-inhibitor (HAEGARDA, CSL Behring), is a US Food and Drug Administration (FDA)-approved, highly concentrated formulation of a plasma-derived C1-esterase inhibitor (C1-INH), which, in the phase III Clinical Studies for Optimal Management in Preventing Angioedema with Low-Volume Subcutaneous C1-inhibitor Replacement Therapy (COMPACT) trial, reduced the incidence of hereditary angioedema (HAE) attacks when given prophylactically. Data from the COMPACT trial were used to develop a repeated time-to-event model to characterize the timing and frequency of HAE attacks as a function of C1-INH activity, and then develop an exposure-response model to assess the relationship between C1-INH functional activity levels (C1-INH(f)) and the risk of an attack. The C1-INH(f) values of 33.

Use of statistical and pharmacokinetic-pharmacodynamic modeling and simulation to improve decision-making: A section summary report of the trends and innovations in clinical trial statistics conference.

The application of modeling and simulation (M&S) methods to improve decision-making was discussed during the Trends & Innovations in Clinical Trial Statistics Conference held in Durham, North Carolina, USA on May 1-4, 2016. Uses of both pharmacometric and statistical M&S were presented during the conference, highlighting the diversity of the methods employed by pharmacometricians and statisticians to address a broad range of quantitative issues in drug development. Five presentations are summarized herein, which cover the development strategy of employing M&S to drive decision-making; European initiatives on best practice in M&S; case studies of pharmacokinetic/pharmacodynamics modeling in regulatory decisions; estimation of exposure-response relationships in the presence of confounding; and the utility of estimating the probability of a correct decision for dose selection when prior information is limited.

Comparative assessment of clinical response in patients with rheumatoid arthritis between PF-05280586, a proposed rituximab biosimilar, and rituximab.

Aims: To evaluate potential differences between PF-05280586 and rituximab sourced from the European Union (rituximab-EU) and USA (rituximab-US) in clinical response (Disease Activity Score in 28 Joints [DAS28] and American College of Rheumatology [ACR] criteria), as part of the overall biosimilarity assessment of PF-05280586.

Methods: A randomised, double-blind, pharmacokinetic similarity trial was conducted in patients with active rheumatoid arthritis refractory to anti-tumour necrosis factor therapy on a background of methotrexate. Patients were treated with 1000 mg of PF-05280586, rituximab-EU or rituximab-US on days 1 and 15 and followed over 24 weeks for pharmacokinetic, clinical response and safety assessments.

Evaluation of estimation, prediction and inference for autocorrelated latent variable modeling of binary data-a simulation study.

Longitudinal models of binary or ordered categorical data are often evaluated for adequacy by the ability of these to characterize the transition frequency and type between response states. Drug development decisions are often concerned with accurate prediction and inference of the probability of response by time and dose. A question arises on whether the transition probabilities need to be characterized adequately to ensure accurate response prediction probabilities unconditional on the previous response state.

Application of a hazard-based visual predictive check to evaluate parametric hazard models.

Parametric models used in time to event analyses are evaluated typically by survival-based visual predictive checks (VPC). Kaplan-Meier survival curves for the observed data are compared with those estimated using model-simulated data. Because the derivative of the log of the survival curve is related to the hazard--the typical quantity modeled in parametric analysis--isolation, interpretation and correction of deficiencies in the hazard model determined by inspection of survival-based VPC's is indirect and thus more difficult.

Integrated nonclinical and clinical risk assessment of the investigational proteasome inhibitor ixazomib on the QTc interval in cancer patients.

Background: Ixazomib is the first oral, proteasome inhibitor to reach phase III trials. Here, we present an integrated nonclinical and clinical assessment of ixazomib's effect on QTc intervals.

Methods: Nonclinical studies assessed (1) the in vitro binding of ixazomib to the hERG channel and (2) its effect on QT/QTc in dogs (N = 4) via telemetry.

Exposure-response modeling of average daily pain score, and dizziness and somnolence, for mirogabalin (DS-5565) in patients with diabetic peripheral neuropathic pain.

Mirogabalin (DS-5565) is an α2δ-1 ligand being developed for pain associated with diabetic peripheral neuropathy, fibromyalgia, and postherpetic neuralgia. Nonlinear mixed-effects analyses were performed on average daily pain and on the incidence of the adverse events dizziness and somnolence. These models were used to predict the dose of mirogabalin equivalent to pregabalin and the probability of meaningful reduction in pain compared with placebo and pregabalin.

Population pharmacokinetics of pegaptanib sodium (Macugen(®)) in patients with diabetic macular edema.

Objective: Population pharmacokinetic modeling of pegaptanib was undertaken to determine influence of renal function on apparent clearance.

Methods: In a randomized, double-masked multicenter trial, intravitreal pegaptanib (0.3, 1.

Population dose-response analysis of daily seizure count following vigabatrin therapy in adult and pediatric patients with refractory complex partial seizures.

Vigabatrin is an irreversible inhibitor of γ-aminobutyric acid transaminase (GABA-T) and is used as an adjunctive therapy for adult patients with refractory complex partial seizures (rCPS). The purpose of this investigation was to describe the relationship between vigabatrin dosage and daily seizure rate for adults and children with rCPS and identify relevant covariates that might impact seizure frequency. This population dose-response analysis used seizure-count data from three pediatric and two adult randomized controlled studies of rCPS patients.

Changes in serum creatinine in patients with active rheumatoid arthritis treated with tofacitinib: results from clinical trials.

Introduction: Small increases in mean serum creatinine (SCr) were observed in studies of rheumatoid arthritis patients during tofacitinib treatment. These SCr changes were investigated and potential mechanisms explored.

Methods: SCr values and renal adverse event data were pooled from five Phase 3 and two long-term extension (LTE) studies.

Covariate selection in pharmacometric analyses: a review of methods.

Covariate selection is an activity routinely performed during pharmacometric analysis. Many are familiar with the stepwise procedures, but perhaps not as many are familiar with some of the issues associated with such methods. Recently, attention has focused on selection procedures that do not suffer from these issues and maintain good predictive properties.

Predicting the time to clinically worsening in mild cognitive impairment patients and its utility in clinical trial design by modeling a longitudinal clinical dementia rating sum of boxes from the ADNI database.

Background: Growing interest in treating Alzheimer's disease (AD) patients in the earliest stages requires new clinical endpoints. Currently, there is no established clinical endpoint or treatment duration for mild cognitive impairment (MCI) trials.

Objective: This analysis attempts to answer "how long the MCI clinical trial would be necessary" using the Clinical Dementia Rating Sum of Boxes (CDR-SB) as a clinical endpoint, where CDR-SB is an example of a suitable tool to assess both cognition and function as a single primary efficacy outcome.

Predicting relapsing-remitting dynamics in multiple sclerosis using discrete distribution models: a population approach.

Background: Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI) as contrast enhancing lesions (CEL).

Simultaneous pharmacokinetic model for rolofylline and both M1-trans and M1-cis metabolites.

Rolofylline is a potent, selective adenosine A1 receptor antagonist that was under development for the treatment of patients with acute congestive heart failure and renal impairment. Rolofylline is metabolized primarily to the pharmacologically active M1-trans and M1-cis metabolites (metabolites) by cytochrome P450 (CYP) 3A4. The aim of this investigation was to provide a pharmacokinetic (PK) model for rolofylline and metabolites following intravenous administration to healthy volunteers.

Longitudinal FEV1 dose-response model for inhaled PF-00610355 and salmeterol in patients with chronic obstructive pulmonary disease.

The objective of this work was to characterize the dose-response relationship between two inhaled long-acting beta agonists (PF-00610355 and salmeterol) and the forced expiratory volume in one second (FEV1) in order to inform dosing recommendations for future clinical trials in patients with chronic obstructive pulmonary disease (COPD). This meta-analysis of four studies included 8,513 FEV1 measurements from 690 patients with moderate COPD. A longitudinal kinetic-pharmacodynamic (K-PD) model was developed and adequately described changes in FEV1 measurements over time, including circadian patterns within a day, as well as changes in FEV1 measurements elicited from administration of PF-00610355 or salmeterol.

Extending the latent variable model for extra correlated longitudinal dichotomous responses.

Since generalized nonlinear mixed-effects modeling methodology of ordered categorical data became available in the pharmacokinetic/pharmacodynamic (PK/PD) literature over a decade ago, pharmacometricians have been increasingly performing exposure-response analyses of such data to inform drug development. Also, as experiences with and scrutiny of these data have increased, pharmacometricians have noted fewer transitions (or greater correlations) between response values than predicted by the model. In this paper, we build on the latent variable (LV) approach, which is convenient for incorporating pharmacological concepts such as pharmacodynamic onset of drug effect, and present a PK/PD methodology which we term the multivariate latent variable (MLV) approach.

Translational PK-PD modelling of molecular target modulation for the AMPA receptor positive allosteric modulator Org 26576.

Introduction: The α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptor potentiator Org 26576 represents an interesting pharmacological tool to evaluate the utility of glutamatergic enhancement towards the treatment of psychiatric disorders. In this study, a rat-human translational pharmacokinetic-pharmacodynamic (PK-PD) model of AMPA receptor modulation was used to predict human target engagement and inform dose selection in efficacy clinical trials.

Methods: Modelling and simulation was applied to rat plasma and cerebrospinal fluid (CSF) pharmacokinetic and pharmacodynamic measurements to identify a target concentration (EC(80)) for AMPA receptor modulation.

Estimating transformations for repeated measures modeling of continuous bounded outcome data.

Continuous bounded outcome data are unlikely to meet the usual assumptions for mixed-effects models of normally distributed and independent subject-specific and residual random effects. Additionally, overly complicated model structures might be necessary to account adequately for non-drug (time-dependent) and drug treatment effects. A transformation strategy with a likelihood component for censoring is developed to promote the simplicity of model structures and to improve the plausibility of assumptions on the random effects.

Joint modeling of dizziness, drowsiness, and dropout associated with pregabalin and placebo treatment of generalized anxiety disorder.

Dizziness and drowsiness are cited as being predictors of dropout from clinical trials for the medicine pregabalin. These adverse events are typically recorded daily on a four point ordinal scale (0 = none, 1 = mild, 2 = moderate, 3 = severe), with most subjects never reporting either adverse event. We modeled the dizziness, drowsiness, and dropout associated with pregabalin use in generalized anxiety disorder using piecewise Weibull distributions for the time to first non-zero dizziness or drowsiness score, after which the dizziness or drowsiness was modeled with ordinal regression with a Markovian element.

An alternative method for population pharmacokinetic data analysis under noncompliance.

Noncompliance presents a persistent problem while analyzing PK data from outpatient clinical studies. Ignoring dose omission or making uninformed assumptions about patient drug intake history can prove detrimental to the objectives of the analysis (e.g.

Performance characteristics for some typical QT study designs under the ICH E-14 guidance.

The International Conference on Harmonization (ICH) guidance for clinical evaluation of QT prolongation (E14) affected drug development by advocating that a thorough QT study (TQT) be conducted during development to assess the QT prolongation liability of a compound. The ICH E14 Statistics Group shortly thereafter recommended that a noninferiority intersection-union test (IUT) be used to exclude a clinically worrisome QT prolongation. Recent analyses have indicated that the IUT might be overly conservative with respect to excluding QT prolongation.

Exposure-response modeling using latent variables for the efficacy of a JAK3 inhibitor administered to rheumatoid arthritis patients.

Currently, no general methods have been developed to relate pharmacologically based models, such as indirect response models, to discrete or ordered categorical data. We propose the use of an unobservable latent variable (LV), through which indirect response models can be linked with drug exposure. The resulting indirect latent variable response model (ILVRM) is demonstrated using a case study of a JAK3 inhibitor, which was administered to patients in a rheumatoid arthritis (RA) study.

Modeling the exposure-response relationship of etanercept in the treatment of patients with chronic moderate to severe plaque psoriasis.

Modeling exposure-response relationships adds significant value to comprehending and interpreting both efficacy and safety data. An exposure-response model was developed using generalized nonlinear mixed-effects methodologies to correlate etanercept exposure with a 75% or greater reduction from baseline in the psoriasis area and severity index (PASI75). Three randomized trials of psoriasis patients were pooled for analysis.

Collapsing mechanistic models: an application to dose selection for proof of concept of a selective irreversible antagonist.

When data fail to support fully mechanistic models, alternative modeling strategies must be pursued. Simpler, more empirical models or the fixing of various rate constants are necessary to avoid over-parameterization. Fitting empirical models can dilute information, limit interpretation, and cloud inference.