ArticleEuropean journal of drug metabolism and pharmacokinetics2018
Evaluation of FOCEI and SAEM Estimation Methods in Population Pharmacokinetic Analysis Using NONMEM
Article in European journal of drug metabolism and pharmacokinetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Population Pharmacokinetic/Pharmacodynamic Modeling of Therapeutic Enzymes in Lysosomal Storage Diseases.Clinical pharmacokinetics · 2026Pooled it
- Advances and Further Comparison of Software Tools for Fisher Information Matrix-Based Design Evaluation in Pharmacometrics.Pharmaceutical research · 2026Article
- Application of a Stochastic Simulation-estimation Approach to Optimize Pharmacokinetic Study Design in the Context of Paediatric Extrapolation: A Tool to Support Decision-making by Drug Sponsors and Regulators.Pharmaceutical research · 2026Article
- Safety Evaluation and Population Pharmacokinetics of Camostat Mesylate and Its Major Metabolites Using a Phase I Study.Pharmaceutics · 2023Article
- Population pharmacokinetic analysis of dexmedetomidine in children using real-world data from electronic health records and remnant specimens.British journal of clinical pharmacology · 2022Article
- Effect of CYP3A5 and CYP3A4 Genetic Variants on Fentanyl Pharmacokinetics in a Pediatric Population.Clinical pharmacology and therapeutics · 2022Article
- Population Pharmacokinetics and Pharmacodynamics of Vancomycin in Pediatric Patients With Various Degrees of Renal Function.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2022Article
- Population Pharmacokinetics of Clotting Factor Concentrates and Desmopressin in Hemophilia.Clinical pharmacokinetics · 2021Review
- Population pharmacokinetics and pharmacodynamics of piperacillin in critically ill patients during the early phase of sepsis.Journal of pharmacokinetics and pharmacodynamics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesFirst-order conditional estimation with interaction (FOCEI) is one of the most commonly used estimation methods in nonlinear mixed effects modeling, while the stochastic approximation expectation maximization (SAEM) is the newer estimation algorithm. This work aimed to compare the performance of FOCEI and SAEM methods when using NONMEM
methodsOne- and two-compartment models of the previous studies were used to simulate data in three scenarios: rich, medium, and sparse data. For each scenario, there were 100 data sets, containing 100 individuals in each data set. Every data set was estimated with both FOCEI and SAEM methods. The simulation and estimation were performed using NONMEM
resultsBoth FOCEI and SAEM methods provided comparable completion rates, median %RERs (ranged from - 9.03 to 3.27% for FOCEI and - 9.17 to 3.27% for SAEM) and RMSEs (ranged from 0.0004 to 1.244 for FOCEI and 0.0004 to 1.131 for SAEM) for most parameters in both models across three scenarios. The run times were much shorter with FOCEI (ranged from 0.18 to 0.98 min) compared to SAEM method (ranged from 4.64 to 12.03 min).
conclusionsFor the classical one- and two-compartment models, FOCEI method exhibited comparable performance similar to SAEM method but with significantly shorter runtimes across rich, medium, and sparse sampling scenarios.
Indexed as
Identifiers
29785609What 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.