ArticleThe AAPS journal2016
Preconditioning of Nonlinear Mixed Effects Models for Stabilisation of Variance-Covariance Matrix Computations.
Article in The AAPS journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Population Pharmacokinetics of Dupilumab in Adults, Adolescents, and Children With Eosinophilic Esophagitis.Clinical pharmacology and therapeutics · 2026Trial
- Pharmacokinetic/Pharmacodynamic Modelling of Allopurinol, its Active Metabolite Oxypurinol, and Biomarkers Hypoxanthine, Xanthine and Uric Acid in Hypoxic-Ischemic Encephalopathy Neonates.Clinical pharmacokinetics · 2022Trial
- Disease Systems Analysis of Bone Mineral Density and Bone Turnover Markers in Response to Alendronate, Placebo, and Washout in Postmenopausal Women.CPT: pharmacometrics & systems pharmacology · 2016Trial
- Population Pharmacokinetics of Radotinib in Healthy Volunteers and Patients with Chronic Myeloid Leukemia.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Bayesian estimation in NONMEM.CPT: pharmacometrics & systems pharmacology · 2024Article
- Metaheuristics for pharmacometrics.CPT: pharmacometrics & systems pharmacology · 2021Review
- Saddle-Reset for Robust Parameter Estimation and Identifiability Analysis of Nonlinear Mixed Effects Models.The AAPS journal · 2020Article
- Population pharmacokinetics and covariate analysis of Sym004, an antibody mixture against the epidermal growth factor receptor, in subjects with metastatic colorectal cancer and other solid tumors.Journal of pharmacokinetics and pharmacodynamics · 2020Article
- Lessons learned from IDeAl - 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials.Orphanet journal of rare diseases · 2018Review
- Model selection and averaging of nonlinear mixed-effect models for robust phase III dose selection.Journal of pharmacokinetics and pharmacodynamics · 2017Article
- Parameter Identifiability of Fundamental Pharmacodynamic Models.Frontiers in physiology · 2016Article
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3 authors.
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Abstract
As the importance of pharmacometric analysis increases, more and more complex mathematical models are introduced and computational error resulting from computational instability starts to become a bottleneck in the analysis. We propose a preconditioning method for non-linear mixed effects models used in pharmacometric analyses to stabilise the computation of the variance-covariance matrix. Roughly speaking, the method reparameterises the model with a linear combination of the original model parameters so that the Hessian matrix of the likelihood of the reparameterised model becomes close to an identity matrix. This approach will reduce the influence of computational error, for example rounding error, to the final computational result. We present numerical experiments demonstrating that the stabilisation of the computation using the proposed method can recover failed variance-covariance matrix computations, and reveal non-identifiability of the model parameters.
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