Evidence map›Paper›PMID 27491774›Full record

ArticleEuropean journal of clinical pharmacology2016

Prediction of drug interaction between oral adsorbent AST-120 and concomitant drugs based on the in vitro dissolution and in vivo absorption behavior of the drugs.

Yohei Koya, Shinya Uchida, Yoshiki Machi, Yuko Shobu, Noriyuki Namiki, Tsutomu Kotegawa

Abstract read
In one paragraph

Article in European journal of clinical pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yohei KoyaPharmaceutical & Agrochemicals Division, KUREHA CORPORATION, 3-26-2 Hyakunin-cho, Shinjuku-ku, Tokyo, 169-8503, Japan. y-koya@kureha.co.jp.
Shinya UchidaDepartment of Pharmacy Practice and Science, School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526, Japan.
Yoshiki MachiPharmaceutical & Agrochemicals Division, KUREHA CORPORATION, 3-26-2 Hyakunin-cho, Shinjuku-ku, Tokyo, 169-8503, Japan.
Yuko ShobuPharmaceutical & Agrochemicals Division, KUREHA CORPORATION, 3-26-2 Hyakunin-cho, Shinjuku-ku, Tokyo, 169-8503, Japan.
Noriyuki NamikiDepartment of Pharmacy Practice and Science, School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526, Japan.
Tsutomu KotegawaOasis Daiichi Hospital, 3-3-19 Higashi-tsurusaki, Oita, 870-0103, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAST-120 is used to decrease the abundance of serum uremic toxins in treatment of chronic kidney disease; however, it could also adsorb concomitantly administered drugs. This study aimed to develop a prediction method for drug interaction between AST-120 and concomitantly administered drugs based on in vitro dissolution and in vivo absorption behavior.

methodsSixty-eight drugs were selected for the analysis. For each drug, theoretical dissolution (R

resultsThe in vitro dissolution and in vivo absorption behavior of the selected drugs were well fitted to the Noyes-Whitney formula and one- or two-compartment models. The optimal R

conclusionA new drug interaction prediction method based on the pharmacokinetic parameters of drugs was developed. The new model is useful for estimating the risk of drug interaction in clinical practice when AST-120 is used in combination with other drugs.

Indexed as

Models, BiologicalAdministration, OralAdsorptionAluminum HydroxideAmlodipineAspirinCarbonDrug InteractionsGlycineHumansIntestinal AbsorptionLosartanMagnesiumMetoprololNifedipineOxidesAluminum HydroxideAmlodipineAspirinAST 120Carbondihydroxyaluminum aminoacetateGlycineLosartanMagnesiummagnesium carbonateMetoprololNifedipineOxidesTriazolamAST-120DissolutionDosing intervalDrug interactionIndoxyl sulfatePharmacokinetics

Identifiers

PMID27491774
PMCPMC5055906

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Registered trials

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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.