ArticleJournal of pharmacokinetics and pharmacodynamics2016
A strategy for residual error modeling incorporating scedasticity of variance and distribution shape.
Article in Journal of pharmacokinetics and pharmacodynamics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Exposure-response modeling of liver fat imaging endpoints in non-alcoholic fatty liver disease populations administered ervogastat alone and co-administered with clesacostat.CPT: pharmacometrics & systems pharmacology · 2025Trial
- Plasma and CSF pharmacokinetics of meropenem in neonates and young infants: results from the NeoMero studies.The Journal of antimicrobial chemotherapy · 2018Trial
- Comparing heavy-tailed residual error models for outlier handling in population PK modeling.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- Population Pharmacokinetics of Sotorasib in Healthy Subjects and Advanced Solid Tumor Patients Harboring a KRASThe AAPS journal · 2025Article
- A PK-PD model linking biomarker dynamics to progression-free survival in patients treated with everolimus and sorafenib combination therapy, EVESOR phase I trial.Cancer chemotherapy and pharmacology · 2023Article
- Population Pharmacokinetics of Meropenem in Critically Ill Korean Patients and Effects of Extracorporeal Membrane Oxygenation.Pharmaceutics · 2021Article
- Predicting ewe body condition score using adjusted liveweight for conceptus and fleece weight, height at withers, and previous body condition score record.Translational animal science · 2021Article
- Prospective Cohort Study of Population Pharmacokinetics and Pharmacodynamic Target Attainment of Vancomycin in Adults on Extracorporeal Membrane Oxygenation.Antimicrobial agents and chemotherapy · 2021Article
- Pharmacokinetics and Monte Carlo Simulation of Meropenem in Critically Ill Adult Patients Receiving Extracorporeal Membrane Oxygenation.Frontiers in pharmacology · 2021Article
- Observational
- Predicting Ewe Body Condition Score Using Lifetime Liveweight and Liveweight Change, and Previous Body Condition Score Record.Animals : an open access journal from MDPI · 2020Article
- Population Pharmacokinetics of the Antituberculosis Agent Pretomanid.Antimicrobial agents and chemotherapy · 2019Article
- Variability Attribution for Automated Model Building.The AAPS journal · 2019Article
- Model-Based Residual Post-Processing for Residual Model Identification.The AAPS journal · 2018Article
- Semi-Mechanistic Model for Predicting the Dosing Rate in Children and Neonates for Drugs Mainly Eliminated by Cytochrome Metabolism.Clinical pharmacokinetics · 2018Article
- Investigation of the Discriminatory Ability of Pharmacokinetic Metrics for the Bioequivalence Assessment of PEGylated Liposomal Doxorubicin.Pharmaceutical research · 2018Article
- Use of a linearization approximation facilitating stochastic model building.Journal of pharmacokinetics and pharmacodynamics · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nonlinear mixed effects models parameters are commonly estimated using maximum likelihood. The properties of these estimators depend on the assumption that residual errors are independent and normally distributed with mean zero and correctly defined variance. Violations of this assumption can cause bias in parameter estimates, invalidate the likelihood ratio test and preclude simulation of real-life like data. The choice of error model is mostly done on a case-by-case basis from a limited set of commonly used models. In this work, two strategies are proposed to extend and unify residual error modeling: a dynamic transform-both-sides approach combined with a power error model (dTBS) capable of handling skewed and/or heteroscedastic residuals, and a t-distributed residual error model allowing for symmetric heavy tails. Ten published pharmacokinetic and pharmacodynamic models as well as stochastic simulation and estimation were used to evaluate the two approaches. dTBS always led to significant improvements in objective function value, with most examples displaying some degree of right-skewness and variances proportional to predictions raised to powers between 0 and 1. The t-distribution led to significant improvement for 5 out of 10 models with degrees of freedom between 3 and 9. Six models were most improved by the t-distribution while four models benefited more from dTBS. Changes in other model parameter estimates were observed. In conclusion, the use of dTBS and/or t-distribution models provides a flexible and easy-to-use framework capable of characterizing all commonly encountered residual error distributions.
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