Objectives: Chronic kidney disease (CKD) is a major public healthcare priority. Patients with CKD are also at higher risk of comorbidities…
Read morePoster: Methodology - Estimation Methods
Implementation of non-linear mixed effects models in NONMEM described by fractional differential equations.
Introduction: Fractional calculus has been used within the last couple of decades, to describe anomalous diffusion (i.e. diffusion not described…
Read moreDevelopment of population pharmacokinetic models using informative priors in clinical settings
Introduction and objectives: In the clinical setting, one of the limitations of developing population pharmacokinetic (PopPK) models is the sparseness…
Read moreOn the error of the Laplace approximation when lags and duration parameters have between-subject variation
It is well known that estimation based on the Laplace approximation, such as the First Order Conditional Estimation (FOCE), of…
Read moreGeneralized FOCE with Pumas
Introduction: Traditionally, the first-order estimation method (FOCE) [1] has been associated with the Gaussian error models. However, when FOCE is…
Read moreTorsten: Stan functions for pharmacometric applications – Improvements and new R interface workflow
Objectives: Stan is a widely used, open-source, probabilistic programming language and Bayesian inference engine [1]. It provides a general model…
Read moreImplementation of the standard concentration – QTc study using MonolixSuite applications on the example of Dofetilide.
Objectives: QT interval is the period when ventricles start to contract to when they finish. But when this period becomes…
Read morePKPDposterior: R package for structured full-Bayesian model-informed precision dosing
Objectives: Most point-of-care model-informed precision dosing (MIPD) software tools use maximum likelihood (maximum a posteriori MAP Bayesian) estimation to adjust…
Read moreDiffMEM: an open-source package for high-performance pharmacometric model estimation
Introduction: DiffMEM is an open-source software package, freely available on Bitbucket[1], for rapid optimization of non-linear mixed effect models using ordinary…
Read moreGauss-Newton algorithm for parameter estimation of nonlinear mixed-effects models
Objectives: Solving (nonlinear) least squares problems (LS problems) with a Gauss-Newton (GN) algorithm is a state-of-the-art approach and the algorithm’s…
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