Trial reportEuropean journal of clinical pharmacology2015
Development of population pharmacokinetics model of icotinib with non-linear absorption characters in healthy Chinese volunteers to assess the CYP2C19 polymorphism and food-intake effect.
Trial report in European 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 5 papers.
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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
5 citing papers in PubMed, 6 citations in OpenAlex.
- Modeling exposure-driven adverse events of EGFR TKIs in the treatment of patients with non-small cell lung cancer.Acta pharmacologica Sinica · 2025Article
- A Randomized, Open, Single-Centre, Crossed Study of the Effect of Food on the Pharmacokinetics of One Oral Dose of Alflutinib Mesylate Tablets (AST2818) in Healthy Male Subjects.Iranian journal of pharmaceutical research : IJPR · 2020Article
- Population pharmacokinetic modeling of flurbiprofen, the active metabolite of flurbiprofen axetil, in Chinese patients with postoperative pain.Journal of pain research · 2018Article
- Population Pharmacokinetic Modeling of Olmesartan, the Active Metabolite of Olmesartan Medoxomil, in Patients with Hypertension.European journal of drug metabolism and pharmacokinetics · 2017Article
- A Phase I Study of the Safety and Pharmacokinetics of Higher-Dose Icotinib in Patients With Advanced Non-Small Cell Lung Cancer.The oncologist · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeIcotinib is a potent and selective inhibitor of epidermal growth factor receptors (EGFR) approved to treat non-small cell lung cancer (NSCLC). However, its high variability may impede its application. The objectives of this analysis were to assess plasma pharmacokinetics and identify covariates that may explain variability in icotinib absorption and/or disposition following single dose of icotinib in healthy volunteers.
methodsData from two clinical studies (n = 22) were analyzed. One study was designed as three-period and Latin-squared (six sequence) trial to evaluate dose proportionality, and the other one was designed as two-way crossover trial to evaluate food effect on pharmacokinetics (PK) characters. Icotinib concentrations in plasma were analyzed using non-linear mixed-effects model (NONMEM) method. The model was used to assess influence of food, demographic characteristics, measurements of blood biochemistry, and CYP2C19 genotype on PK characters of icotinib in humans. The final model was diagnosed by goodness-of-fit plots and evaluated by visual predictive check (VPC) and bootstrap methods.
resultsA two-compartment model with saturated absorption character was developed to capture icotinib pharmacokinetics. Typical value of clearance, distribution clearance, central volume of distribution, maximum absorption rate were 29.5 L/h, 24.9 L/h, 18.5 L, 122.2 L and 204,245 μg/h, respectively. When icotinib was administrated with food, bioavailability was estimated to be increased by 48%. Inter-occasion variability was identified to affect on maximum absorption rate constant in food-effect study. CL was identified to be significantly influenced by age, albumin concentration (ALB), and CYP2C19 genotype. No obvious bias was found by VPC and bootstrap methods.
conclusionsThe developed model can capture icotinib pharmacokinetics well in healthy volunteers. Food intake can increase icotinib exposure. Three covariates, age, albumin concentration, and CYP2C19 genotype, were identified to significantly affect icotinib PK profiles in healthy subjects.
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