ReviewBritish journal of clinical pharmacology2015
A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection.
Review in British journal of clinical pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Budesonide Foam Has a Favorable Safety Profile for Inducing Remission in Mild-to-Moderate Ulcerative Proctitis or Proctosigmoiditis.Digestive diseases and sciences · 2015Pooled it
- Application of Population-Based Meta-Heuristic Algorithms for Robust Initialization in Mechanistic Pharmacometric Modeling.CPT: pharmacometrics & systems pharmacology · 2026Article
- Multi-objective optimization in population pharmacokinetic model selection and optimization: application of NSGA-II in pyDarwin.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- A machine learning approach to population pharmacokinetic modelling automation.Communications medicine · 2025Article
- A fully automatic tool for development of population pharmacokinetic models.CPT: pharmacometrics & systems pharmacology · 2024Article
- Parameter grouping and co-estimation in physiologically based kinetic models using genetic algorithms.Toxicological sciences : an official journal of the Society of Toxicology · 2024Article
- Go beyond the limits of genetic algorithm in daily covariate selection practice.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Population pharmacokinetic modelling of febuxostat in healthy subjects and people with gout.British journal of clinical pharmacology · 2022Article
- Pharmacokinetic/Pharmacodynamic Modeling and Application in Antibacterial and Antifungal Pharmacotherapy: A Narrative Review.Antibiotics (Basel, Switzerland) · 2022Review
- Development of a genetic algorithm and NONMEM workbench for automating and improving population pharmacokinetic/pharmacodynamic model selection.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- Early Warning and Clinical Epidemiological Characteristics of Lung Injury in the Treatment of InfectiousComputational intelligence and neuroscience · 2022Article
- Application of Machine Learning in Translational Medicine: Current Status and Future Opportunities.The AAPS journal · 2021Article
- English Feature Recognition Based on GA-BP Neural Network Algorithm and Data Mining.Computational intelligence and neuroscience · 2021Article
- Genetic Algorithms as a Tool for Dosing Guideline Optimization: Application to Intermittent Infusion Dosing for Vancomycin in Adults.CPT: pharmacometrics & systems pharmacology · 2020Article
- Automated proper lumping for simplification of linear physiologically based pharmacokinetic systems.Journal of pharmacokinetics and pharmacodynamics · 2019Article
- Pharmacometrics: so much mathematics and why planes achieve their destinations with almost perfect results ….British journal of clinical pharmacology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The current algorithm for selecting a population pharmacokinetic/pharmacodynamic model is based on the well-established forward addition/backward elimination method. A central strength of this approach is the opportunity for a modeller to continuously examine the data and postulate new hypotheses to explain observed biases. This algorithm has served the modelling community well, but the model selection process has essentially remained unchanged for the last 30 years. During this time, more robust approaches to model selection have been made feasible by new technology and dramatic increases in computation speed. We review these methods, with emphasis on genetic algorithm approaches and discuss the role these methods may play in population pharmacokinetic/pharmacodynamic model selection.
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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.