ArticleThe Journal of pharmacy and pharmacology2008
Pharmacokinetic differentiation of drug candidates using system analysis and physiological-based modelling. Comparison of C.E.R.A. and erythropoietin.
Article in The Journal of pharmacy and pharmacology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Once-monthly continuous erythropoietin receptor activator (CERA) for haemoglobin maintenance in haemodialysis patients with chronic renal anaemia.Clinical kidney journal · 2014Article
- Applications of minimal physiologically-based pharmacokinetic models.Journal of pharmacokinetics and pharmacodynamics · 2012Article
- Differential pharmacokinetic analysis of in vivo erythropoietin receptor interaction with erythropoietin and continuous erythropoietin receptor activator in sheep.Biopharmaceutics & drug disposition · 2011Article
- Pharmacokinetic analysis of continuous erythropoietin receptor activator disposition in adult sheep using a target-mediated, physiologic recirculation model and a tracer interaction methodology.Drug metabolism and disposition: the biological fate of chemicals · 2011Article
- Selection between Michaelis-Menten and target-mediated drug disposition pharmacokinetic models.Journal of pharmacokinetics and pharmacodynamics · 2010Article
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
Abstract
Evaluation of the pharmacokinetics (PKs) in a proper physiological context is paramount to elucidate the factors that may improve a drug's PK properties. Using modern system analysis-based physiological modelling principles, this work applies a novel kinetic analysis framework to a PK comparison of two erythropoietically active drugs, C.E.R.A. (continuous erythropoietin receptor activator) and recombinant human erythropoietin (Epo), aimed at elucidating the main factors responsible for the substantial PK differences seen. The evaluation according to the new model is compared with a compartmental model analysis. Sheep (n = 7 for Epo; n = 8 for C.E.R.A.) received intravenous bolus injections of Epo and C.E.R.A. Baseline and 20-30 blood samples per injection were assayed by radioimmunoassay. Fundamental physiologically based PK building block principles were introduced, proceeding to the construction of a general PK model and several sub-models from which a final PK model was selected based on information theoretical principles. The compartmental comparison analysis use a two-compartment model with central Michaelis-Menten elimination. Several lines of evidence support the hypothesis that the desirable slow elimination of C.E.R.A. relative to Epo is mainly caused by a smaller recirculation extraction fraction, which appears more influential on the elimination kinetics than the mean circulation transit time. The compartmental analysis demonstrates large differences in several PK parameters that contribute to C.E.R.A.'s slower elimination, consistent with the recirculation model analysis. It is hypothesized that C.E.R.A.'s smaller recirculatory extraction fraction is due to a reduced receptor-mediated elimination, consistent with in-vitro measurements where C.E.R.A. shows Epo-receptor binding with a lower association constant and a larger dissociation constant.
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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.