11 Result(s)
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Sebastian Ueckert
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Open AccessPharmacokinetics and Tolerability of Zibotentan in Patients with Concurrent Moderate Renal and Moderate Hepatic Impairment
Zibotentan, a selective endothelin A receptor antagonist, is in development for chronic liver and kidney disease. The pharmacokinetics (PK) of zibotentan were previously investigated in patients with either re...
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Open AccessImproved numerical stability for the bounded integer model
This article highlights some numerical challenges when implementing the bounded integer model for composite score modeling and suggests an improved implementation. The improvement is based on an approximation ...
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Open AccessAn Item Response Theory–Informed Strategy to Model Total Score Data from Composite Scales
Composite scale data is widely used in many therapeutic areas and consists of several categorical questions/items that are usually summarized into a total score (TS). Such data is discrete and bounded by natur...
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Open AccessPerformance of longitudinal item response theory models in shortened or partial assessments
This work evaluates the performance of longitudinal item response (IR) theory models in shortened assessments using an existing model for part II and III of the MDS-UPDRS score. Based on the item information c...
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Open AccessModel-Based Conditional Weighted Residuals Analysis for Structural Model Assessment
Nonlinear mixed effects models are widely used to describe longitudinal data to improve the efficiency of drug development process or increase the understanding of the studied disease. In such settings, the ap...
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Comparison of Model Averaging and Model Selection in Dose Finding Trials Analyzed by Nonlinear Mixed Effect Models
In drug development, pharmacometric approaches consist in identifying via a model selection (MS) process the model structure that best describes the data. However, making predictions using a selected model ign...
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Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson’s Disease Patients
This manuscript aims to precisely describe the natural disease progression of Parkinson’s disease (PD) patients and evaluate approaches to increase the drug effect detection power.
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Open AccessAccelerating Monte Carlo power studies through parametric power estimation
Estimating the power for a non-linear mixed-effects model-based analysis is challenging due to the lack of a closed form analytic expression. Often, computationally intensive Monte Carlo studies need to be emp...
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Open AccessImproved Utilization of ADAS-Cog Assessment Data Through Item Response Theory Based Pharmacometric Modeling
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).
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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 ...
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Optimizing disease progression study designs for drug effect discrimination
Investigate the possibility to directly optimize a clinical trial design for statistical power to detect a drug effect and compare to optimal designs that focus on parameter precision. An improved statistic de...
