A Model-Based Evaluation of Noninvasive Biomarkers to Reflect Histological Nonalcoholic Fatty Liver Disease Scores.

Background: Nonalcoholic fatty liver disease (NAFLD) comprises multiple heterogeneous pathophysiological conditions commonly evaluated by suboptimal liver biopsies. This study aimed to elucidate the role of 13 diverse histological liver scores in assessing NAFLD disease activity using an in silico pharmacometric model-based approach. We further sought to investigate various noninvasive patient characteristics for their ability to reflect all 13 histological scores and the NAFLD activity score (NAS).

A tutorial on pharmacometric Markov models.

The Markov chain is a stochastic process in which the future value of a variable is conditionally independent of the past, given its present value. Data with Markovian features are characterized by: frequent observations relative to the expected changes in values, many consecutive same-category or similar-value observations at the individual level, and a positive correlation observed between the current and previous values for that variable. In drug development and clinical settings, the data available commonly present Markovian features and are increasingly often modeled using Markov elements or dedicated Markov models.

Immunogenicity dynamics and covariate effects after satralizumab administration predicted with a hidden Markov model.

Immunogenicity is the propensity of a therapeutic protein to generate an immune response to itself. While reporting of antidrug antibodies (ADAs) is increasing, model-based analysis of such data is seldom performed. Model-based characterization of factors affecting the emergence and dissipation of ADAs may inform drug development and/or improve understanding in clinical practice.

Quantitative Comparisons of Progressive Supranuclear Palsy Rating Scale Versions Using Item Response Theory.

Background: Progressive supranuclear palsy (PSP) is a neurodegenerative, late-onset disease that is challenging in terms of assessment. The Progressive Supranuclear Palsy Rating Scale (PSPRS), a 28-item clinician-reported scale, is the most established clinical outcome assessment method. Recently, the U.

Characterization of anti-drug antibody dynamics using a bivariate mixed hidden-markov model by nonlinear-mixed effects approach.

Biological therapies may act as immunogenic triggers leading to the formation of anti-drug antibodies (ADAs). Population pharmacokinetic (PK) models can be used to characterize the relationship between ADA and drug disposition but often rely on the ADA bioassay results, which may not be sufficiently sensitive to inform on this characterization.In this work, a methodology that could help to further elucidate the underlying ADA production and impact on the drug disposition was explored.

A disease model predicting placebo response and remission status of patients with ulcerative colitis using modified Mayo score.

The Mayo Clinical Score is used in clinical trials to describe the clinical status of patients with ulcerative colitis (UC). It comprises four subscores: rectal bleeding (RB), stool frequency (SF), physician's global assessment, and endoscopy (ENDO). According to recent US Food and Drug Administration guidelines (Ulcerative colitis: developing drugs for treatment, Guidance Document, https://www.

Training the next generation of pharmacometric modelers: a multisector perspective.

The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing.

Joint longitudinal model-based meta-analysis of FEV and exacerbation rate in randomized COPD trials.

Model-based meta-analysis (MBMA) is an approach that integrates relevant summary level data from heterogeneously designed randomized controlled trials (RCTs). This study not only evaluated the predictability of a published MBMA for forced expiratory volume in one second (FEV) and its link to annual exacerbation rate in patients with chronic obstructive pulmonary disease (COPD) but also included data from new RCTs. A comparative effectiveness analysis across all drugs was also performed.

Improved Confidence in a Confirmatory Stage by Application of Item-Based Pharmacometrics Model: Illustration with a Phase III Active Comparator-Controlled Trial in COPD Patients.

Purpose: The current study aimed to illustrate how a non-linear mixed effect (NLME) model-based analysis may improve confidence in a Phase III trial through more precise estimates of the drug effect.

Methods: The FULFIL clinical trial was a Phase III study that compared 24 weeks of once daily inhaled triple therapy with twice daily inhaled dual therapy in patients with chronic obstructive pulmonary disease (COPD). Patient reported outcome data, obtained by using The Evaluating Respiratory Symptoms in COPD (E-RS:COPD) questionnaire, from the FULFIL study were analyzed using an NLME item-based response theory model (IRT).

Improved Decision-Making Confidence Using Item-Based Pharmacometric Model: Illustration with a Phase II Placebo-Controlled Trial.

This study aimed to illustrate how a new methodology to assess clinical trial outcome measures using a longitudinal item response theory-based model (IRM) could serve as an alternative to mixed model repeated measures (MMRM). Data from the EXACT (Exacerbation of chronic pulmonary disease tool) which is used to capture frequency, severity, and duration of exacerbations in COPD were analyzed using an IRM. The IRM included a graded response model characterizing item parameters and functions describing symptom-time course.

Detecting placebo and drug effects on Parkinson's disease symptoms by longitudinal item-score models.

This study tested the hypothesis that analyzing longitudinal item scores of the Unified Parkinson's Disease Rating Scale could allow a smaller trial size and describe a drug's effect on symptom progression. Two historical studies of the dopaminergic drug ropinirole were analyzed: a cross-over formulation comparison trial in 161 patients with early-stage Parkinson's disease, and a 24-week, parallel-group, placebo-controlled efficacy trial in 393 patients with advanced-stage Parkinson's disease. We applied item response theory to estimate the patients' symptom severity and developed a longitudinal model using the symptom severity to describe the time course of the placebo response and the drug effect on the time course.

Item Response Model Adaptation for Analyzing Data from Different Versions of Parkinson's Disease Rating Scales.

Purpose: The aim of this work was to allow combination of information from recent and historical trials in Parkinson's Disease (PD) by developing bridging methodology between two versions of the clinical endpoint.

Methods: A previously developed Item Response Model (IRM), that described longitudinal changes in Movement Disorder Society (MDS) sponsored revision of Unified Parkinson's Disease Rating Scale (UPDRS) [MDS-UPDRS] data from the De Novo PD cohort in Parkinson's Progression Markers Initiative, was first adapted to describe baseline UPDRS data from two clinical trials, one in subjects with early PD and another in subjects with advanced PD. Assuming similar IRM structure, items of the UPDRS version were mapped to those in the MDS-UPDRS version.

Sensitivity of Pegfilgrastim Pharmacokinetic and Pharmacodynamic Parameters to Product Differences in Similarity Studies.

In this work, a previously developed pegfilgrastim (PG) population pharmacokinetic-pharmacodynamic (PKPD) model was used to evaluate potential factors of importance in the assessment of PG PK and PD similarity. Absolute neutrophil count (ANC) was the modelled PD variable. A two-way cross-over study was simulated where a reference PG and a potentially biosimilar test product were administered to healthy volunteers.

A Novel Method for Analysing Frequent Observations from Questionnaires in Order to Model Patient-Reported Outcomes: Application to EXACT® Daily Diary Data from COPD Patients.

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease with approximately 174 million cases worldwide. Electronic questionnaires are increasingly used for collecting patient-reported-outcome (PRO) data about disease symptoms. Our aim was to leverage PRO data, collected to record COPD disease symptoms, in a general modelling framework to enable interpretation of PRO observations in relation to disease progression and potential to predict exacerbations.

A Population Pharmacokinetic-Pharmacodynamic Model of Pegfilgrastim.

Neutropenia and febrile neutropenia (FN) are serious side effects of cytotoxic chemotherapy which may be alleviated with the administration of recombinant granulocyte colony-stimulating factor (GCSF) derivatives, such as pegfilgrastim (PG) which increases absolute neutrophil count (ANC). In this work, a population pharmacokinetic-pharmacodynamic (PKPD) model was developed based on data obtained from healthy volunteers receiving multiple administrations of PG. The developed model was a bidirectional PKPD model, where PG stimulated the proliferation, maturation, and margination of neutrophils and where circulating neutrophils in turn increased the elimination of PG.

Dosing and Switching Strategies for Paliperidone Palmitate 3-Month Formulation in Patients with Schizophrenia Based on Population Pharmacokinetic Modeling and Simulation, and Clinical Trial Data.

Paliperidone palmitate 3-month formulation (PP3M), a long-acting injectable atypical antipsychotic, was recently approved in the US and Europe for the treatment of schizophrenia in adult patients who have already been treated with paliperidone palmitate 1-month formulation (PP1M) for ≥4 months. This article reviews the pharmacokinetic rationale for the approved dosing regimens for PP3M, dosing windows, management of missed doses and treatment discontinuation, switching to other formulations, and dosing in special populations. Approved PP3M dosing regimens are based on the comparisons of simulations with predefined dosing regimens using paliperidone palmitate and oral paliperidone extended release (ER) population pharmacokinetic models (one-compartment model with two saturable absorption processes for PP3M; one-compartment model with parallel zero- and first-order absorption for PP1M; two-compartment model with sequential zero- and first-order absorption for ER) versus clinical trial data.

Modeling a Composite Score in Parkinson's Disease Using Item Response Theory.

In the current work, we present the methodology for development of an Item Response Theory model within a non-linear mixed effects framework to characterize the longitudinal changes of the Movement Disorder Society (sponsored revision) of Unified Parkinson's Disease Rating Scale (MDS-UPDRS) endpoint in Parkinson's disease (PD). The data were obtained from Parkinson's Progression Markers Initiative database and included 163,070 observations up to 48 months from 430 subjects belonging to De Novo PD cohort. The probability of obtaining a score, reported for each of the items in the questionnaire, was modeled as a function of the subject's disability.

Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis.

Evaluation of bias, precision, robustness and runtime for estimation methods in NONMEM 7.

NONMEM is the most widely used software for population pharmacokinetic (PK)-pharmacodynamic (PD) analyses. The latest version, NONMEM 7 (NM7), includes several sampling-based estimation methods in addition to the classical methods. In this study, performance of the estimation methods available in NM7 was investigated with respect to bias, precision, robustness and runtime for a diverse set of PD models.

Improved utilization of ADAS-cog assessment data through item response theory based pharmacometric modeling.

Purpose: This work investigates improved utilization of ADAS-cog data (the primary outcome in Alzheimer's disease (AD) trials of mild and moderate AD) by combining pharmacometric modeling and item response theory (IRT).

Methods: A baseline IRT model characterizing the ADAS-cog was built based on data from 2,744 individuals. Pharmacometric methods were used to extend the baseline IRT model to describe longitudinal ADAS-cog scores from an 18-month clinical study with 322 patients.

Performance comparison of various maximum likelihood nonlinear mixed-effects estimation methods for dose-response models.

Estimation methods for nonlinear mixed-effects modelling have considerably improved over the last decades. Nowadays, several algorithms implemented in different software are used. The present study aimed at comparing their performance for dose-response models.

Transient lower esophageal sphincter relaxation pharmacokinetic-pharmacodynamic modeling: count model and repeated time-to-event model.

Transient lower esophageal sphincter relaxation (TLESR) is the major mechanism for gastroesophageal reflux. Characterizations of candidate compounds for reduction of TLESRs are traditionally done through summary exposure and response measures and would benefit from model-based analyses of exposure-TLESR events relationships. Pharmacokinetic (PK)-pharmacodynamic (PD) modeling approaches treating TLESRs either as count data or repeated time-to-event (RTTE) data were developed and compared in terms of their ability to characterize system and drug characteristics.

Modeling longitudinal daily seizure frequency data from pregabalin add-on treatment.

The purpose of this study was to describe longitudinal daily seizure count data with respect to the effects of time and pregabalin add-on therapy. Models were developed in a stepwise manner: base model, time effect model, and time and drug effect (final) model, using a negative binomial distribution with Markovian features. Mean daily seizure count (λ) was estimated to be 0.