Thursday 16 October, 2025
IntroductionQuantitative system pharmacology (QSP) models are applied with increasing frequency to describe and study complex biological systems including drug effects…
Read morePoster: Methodology - Other topics
Subspace MCMC algorithm for Bayesian parameter estimation of hierarchical PK/PD models in Pumas
Thursday 16 October, 2025
Objectives: To speed up the sampling from high-dimensional posteriors of hierarchical Pumas [1] models with a high correlation between the…
Read moreEvaluation of extrapolation potential of IMPRES-M, a non-parametric Impulse-Response Modeling framework when applied to pharmacokinetic profiles of different dosing frequencies
Thursday 16 October, 2025
Introduction: Effective utilization of smoothing in pharmacokinetic (PK) and pharmacodynamic (PK-PD) modeling is limited as currently available approaches [1-4] cannot…
Read moreExtrapolation of Phase 0 microdosing trials: a naïve pooled data modelling approach.
Thursday 16 October, 2025
Objectives: Microdosing is a method to predict pharmacokinetics of a therapeutic dose from microdose (max. 100 µg) data (1). The…
Read moreThe effect of CYP2D6 phenotypes on the pharmacokinetics of propafenone: a systematic review and meta-analysis
Thursday 16 October, 2025
Objectives: Propafenone (PPF) is a class 1C antiarrhythmic agent mainly metabolized to 5-hydroxypropafenone by cytochrome (CYP) 2D6 and norpropafenone by…
Read moreComputation of standard errors at finite distance in non linear mixed effects models
Thursday 16 October, 2025
Introduction: Longitudinal data are often collected in clinical trials, and non linear mixed effects models (NLMEM) are powerful to model…
Read moreUncertainty computation at finite distance in nonlinear mixed effects models – a new method evaluated on simulations and applied to the evolution of clinical status of patients hospitalised for COVID-19
Thursday 16 October, 2025
Number of characters: 4429/4500 Objectives: The standard error (SE) of the maximum likelihood estimate (MLE) of the population parameter vector…
Read moreExplainable machine learning for time-to-event analysis: exploring time-dependent covariate effects on models of small cell lung cancer
Thursday 16 October, 2025
Objectives: Traditional time-to-event analysis relies on parametric or semi-parametric models, such as the Cox proportional hazards model, to estimate the effects…
Read moreMachine learning for covariate selection and prediction of pharmacokinetic data illustrated with rifampicin
Thursday 16 October, 2025
Objectives: Pharmacometrics (PMX) plays a vital role in various areas ranging from model-informed drug development, regulatory decision-making to model-informed precision…
Read morePK-DB: pharmacokinetics database for individualized and stratified computational modeling
Thursday 16 October, 2025
Objectives: A multitude of pharmacokinetics studies has been published. However, due to the lack of an open database, pharmacokinetics data,…
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