ArticlePharmaceutical research2013
Prediction of shrinkage of individual parameters using the bayesian information matrix in non-linear mixed effect models with evaluation in pharmacokinetics.
Article in Pharmaceutical research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.Journal of clinical pharmacology · 2018Trial
- Model-based approaches for ivabradine development in paediatric population, part II: PK and PK/PD assessment.Journal of pharmacokinetics and pharmacodynamics · 2016Trial
- Simulation-Based Evaluation of Busulfan Sampling Strategies in Adults and Adolescents Undergoing Allogeneic Hematopoietic Stem Cell Transplantation.Journal of clinical pharmacology · 2026Article
- Advancing Precision Dosing of 5-FU: Population PK Model Development, Limited Sampling Strategies, and Fit-for-Use Application.Clinical pharmacokinetics · 2026Article
- Assessing the Validity of the Fellow Eye as an Internal Control in Early-Phase Clinical Trials for Myopic Chorioretinal Atrophy.Journal of clinical medicine · 2026Article
- The Use of Microdosing for In vivo Phenotyping of Cytochrome P450 Enzymes: Where Do We Stand? A Narrative Review.European journal of drug metabolism and pharmacokinetics · 2024Review
- Establishment of a pharmacokinetics and pharmacodynamics model of Schisandra lignans against hippocampal neurotransmitters in AD rats based on microdi-alysis liquid chromatography-mass spectrometry.Frontiers in pharmacology · 2024Article
- "De-Shrinking" EBEs: The Solution for Bayesian Therapeutic Drug Monitoring.Clinical pharmacokinetics · 2022Article
- Tutorial for $DESIGN in NONMEM: Clinical trial evaluation and optimization.CPT: pharmacometrics & systems pharmacology · 2021Article
- Individual Bayesian Information Matrix for Predicting Estimation Error and Shrinkage of Individual Parameters Accounting for Data Below the Limit of Quantification.Pharmaceutical research · 2017Article
- Safety and pharmacokinetics of the CIME combination of drugs and their metabolites after a single oral dosing in healthy volunteers.European journal of drug metabolism and pharmacokinetics · 2016Article
- Combined Analysis of Phase I and Phase II Data to Enhance the Power of Pharmacogenetic Tests.CPT: pharmacometrics & systems pharmacology · 2016Article
- A limited sampling strategy based on maximum a posteriori Bayesian estimation for a five-probe phenotyping cocktail.European journal of clinical pharmacology · 2016Article
- Inter occasion variability in individual optimal design.Journal of pharmacokinetics and pharmacodynamics · 2015Article
- MatVPC: A User-Friendly MATLAB-Based Tool for the Simulation and Evaluation of Systems Pharmacology Models.CPT: pharmacometrics & systems pharmacology · 2015Article
- Powers of the likelihood ratio test and the correlation test using empirical bayes estimates for various shrinkages in population pharmacokinetics.CPT: pharmacometrics & systems pharmacology · 2014Article
- Largazole pharmacokinetics in rats by LC-MS/MS.Marine drugs · 2014Article
- Influence of a priori Information, Designs, and Undetectable Data on Individual Parameters Estimation and Prediction of Hepatitis C Treatment Outcome.CPT: pharmacometrics & systems pharmacology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWhen information is sparse, individual parameters derived from a non-linear mixed effects model analysis can shrink to the mean. The objective of this work was to predict individual parameter shrinkage from the Bayesian information matrix (M BF ). We 1) Propose and evaluate an approximation of M BF by First-Order linearization (FO), 2) Explore by simulations the relationship between shrinkage and precision of estimates and 3) Evaluate prediction of shrinkage and individual parameter precision.
methodsWe approximated M BF using FO. From the shrinkage formula in linear mixed effects models, we derived the predicted shrinkage from M BF . Shrinkage values were generated for parameters of two pharmacokinetic models by varying the structure and the magnitude of the random effect and residual error models as well as the design. We then evaluated the approximation of M BF FO and compared it to Monte-Carlo (MC) simulations. We finally compared expected and observed shrinkage as well as the predicted and estimated Standard Errors (SE) of individual parameters.
resultsM BF FO was similar to M BF MC. Predicted and observed shrinkages were close . Predicted and estimated SE were similar.
conclusionsM BF FO enables prediction of shrinkage and SE of individual parameters. It can be used for design optimization.
Indexed as
Identifiers
23743656What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.