Objectives: Autosomal Recessive Cerebellar Ataxias (ARCAs) are ultra-rare, progressive neurodegenerative disorders that primarily affect the cerebellum but also cause multi-systemic…
Read moreOral: Methodology - New Modelling Approaches
Large-language-model-guided discovery of population pharmacokinetic structural models:Evaluation across synthetic and real data
Introduction/Objectives: Structural model discovery in pharmacometrics is a highly iterative, manual, and time-intensive endeavor. Pharmacometricians must continuously propose structural hypotheses,…
Read moreGaussian Process Flows: Accurately characterising drug exposure and effects through Bayesian Inference over mechanistic models.
Background Recently, NeuralODE-based approaches have emerged as promising tools to learn dynamical systems governing drug exposure and effects directly from…
Read moreAutomating Population Pharmacokinetic Model Development using Machine Learning
Population pharmacokinetic (popPK) models are used in decision-making throughout drug development to inform dose selection, clinical study design, and labelling…
Read moreMeta-analysis of parameter estimates of non-linear mixed effect models using Approximate Bayesian Computation: application to population pharmacokinetics
Introduction: Non-Linear Mixed Effect Models (NLMEM) are a gold standard tool to analyze pharmacokinetic (PK) data. Generally, numerous population PK…
Read moreBayesian framework for multi-source data integration – application to Human extrapolation from preclinical studies
Introduction: In preclinical research, including in vitro studies (conducted within subcellular fractions, cell cultures, micro-organisms, organoid models, etc.), in vivo…
Read moreThe estimates for the absorption rate constant in pharmacokinetics and pharmacometrics are wrong: A new era based on the finite absorption time concept rises
Introduction: Common practice in pharmacokinetic analyses and data evaluation as well as in simulations is based on the assumption that…
Read moreA methodology to de-shrink Empirical Bayes Estimates
Objectives: Therapeutic drug monitoring (TDM) is used for some drugs to evaluate drugs exposures and optimize the therapeutic management of…
Read moreBenefits of integrating machine learning with clinical pharmacology principles for predictive pharmacokinetic modeling
Introduction: Machine learning (ML) applications in clinical pharmacology have been rapidly increasing over the last several years (1). While most…
Read moreA Semi Parametric Method for the Estimation of End of Treatment Effect
Objectives: End of treatment effect is a commonly used endpoint in Randomized Clinical Trials (RCTs). Several methods are used for…
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