Trial reportPharmaceutical research2005
Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations.
Trial report in Pharmaceutical research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Trial
- Population pharmacokinetic/pharmacodynamic (PK/PD) modelling of the hypothalamic-pituitary-gonadal axis following treatment with GnRH analogues.British journal of clinical pharmacology · 2007Trial
- Stochastic Differential Equations (SDEs) in NONMEM for Probing Population Pharmacokinetic Model Misspecification: Diagnostic Utility, Practical Considerations, and Future Directions.The AAPS journal · 2026Article
- Neural Controlled Differential Equation and Its Application in Pharmacokinetics and Pharmacodynamics.CPT: pharmacometrics & systems pharmacology · 2026Article
- Multi-scale digital twins for personalized medicine.Frontiers in digital health · 2026Review
- Digital Twins for Personalized Medicine Require Epidemiological Data and Mathematical Modeling: Viewpoint.Journal of medical Internet research · 2025Article
- A tutorial on pharmacometric Markov models.CPT: pharmacometrics & systems pharmacology · 2025Article
- Physiological Dynamics in the Upper Gastrointestinal Tract and the Development of Gastrointestinal Absorption Models for the Immediate-Release Oral Dosage Forms in Healthy Adult Human.Pharmaceutical research · 2023Review
- Stochastic Differential Equation-based Mixed Effects Model of the Fluid Volume in the Fasted Stomach in Healthy Adult Human.The AAPS journal · 2023Article
- A stochastic mixed effects model to assess treatment effects and fluctuations in home-measured peak expiratory flow and the association with exacerbation risk in asthma.CPT: pharmacometrics & systems pharmacology · 2022Article
- Beyond Deterministic Models in Drug Discovery and Development.Trends in pharmacological sciences · 2020Review
- Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data.British journal of clinical pharmacology · 2019Article
- Exact Gradients Improve Parameter Estimation in Nonlinear Mixed Effects Models with Stochastic Dynamics.The AAPS journal · 2018Article
- Pharmacometrics models with hidden Markovian dynamics.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- Modeling Variability in the Progression of Huntington's Disease A Novel Modeling Approach Applied to Structural Imaging Markers from TRACK-HD.CPT: pharmacometrics & systems pharmacology · 2016Article
- Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.Journal of pharmacokinetics and pharmacodynamics · 2016Article
- Stochastic nonlinear mixed effects: a metformin case study.Journal of pharmacokinetics and pharmacodynamics · 2016Article
- Mixed Effects Modeling Using Stochastic Differential Equations: Illustrated by Pharmacokinetic Data of Nicotinic Acid in Obese Zucker Rats.The AAPS journal · 2015Article
- Modeling and simulation of count data.CPT: pharmacometrics & systems pharmacology · 2014Article
- Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.Journal of diabetes science and technology · 2014Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe objective of the present analysis was to explore the use of stochastic differential equations (SDEs) in population pharmacokinetic/pharmacodynamic (PK/PD) modeling.
methodsThe intra-individual variability in nonlinear mixed-effects models based on SDEs is decomposed into two types of noise: a measurement and a system noise term. The measurement noise represents uncorrelated error due to, for example, assay error while the system noise accounts for structural misspecifications, approximations of the dynamical model, and true random physiological fluctuations. Since the system noise accounts for model misspecifications, the SDEs provide a diagnostic tool for model appropriateness. The focus of the article is on the implementation of the Extended Kalman Filter (EKF) in NONMEM for parameter estimation in SDE models.
resultsVarious applications of SDEs in population PK/PD modeling are illustrated through a systematic model development example using clinical PK data of the gonadotropin releasing hormone (GnRH) antagonist degarelix. The dynamic noise estimates were used to track variations in model parameters and systematically build an absorption model for subcutaneously administered degarelix.
conclusionsThe EKF-based algorithm was successfully implemented in NONMEM for parameter estimation in population PK/PD models described by systems of SDEs. The example indicated that it was possible to pinpoint structural model deficiencies, and that valuable information may be obtained by tracking unexplained variations in parameters.
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