Evidence map›Paper›PMID 25716146›Full record

ArticleThe AAPS journal2015

Development of a Novel Oral Cavity Compartmental Absorption and Transit Model for Sublingual Administration: Illustration with Zolpidem.

Binfeng Xia, Zhen Yang, Haiying Zhou, Viera Lukacova, Wei Zhu, Mikolaj Milewski, Filippos Kesisoglou

Abstract read
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Article in The AAPS journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

7 authors.

Binfeng XiaBiopharmaceutics, Pharmaceutical Sciences and Clinical Supply, Merck & Co. Inc., West Point, Pennsylvania, 19486, USA, binfeng.xia@merck.com.
Zhen Yang
Haiying Zhou
Viera Lukacova
Wei Zhu
Mikolaj Milewski
Filippos Kesisoglou

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intraoral (IO) delivery is an alternative administration route to deliver a drug substance via the mouth that provides several advantages over conventional oral dosage forms. The purpose of this work was to develop and evaluate a novel, physiologically based oral cavity model for projection and mechanistic analysis of the clinical pharmacokinetics of intraoral formulations. The GastroPlus™ Oral Cavity Compartmental Absorption and Transit (OCCAT™) model was used to simulate the plasma concentration versus time profiles and the fraction and rate of intraoral drug transit/absorption for Intermezzo® sublingual tablets (zolpidem tartrate). The model was evaluated by the goodness-of-fit between simulated and observed concentrations and the deviation of key PK parameters (e.g., C max, T max, and AUC). In addition, a sensitivity analysis was conducted to demonstrate the interplay and impact of key modeling parameters on the fraction absorbed via oral mucosa (F a_IO). The OCCAT™ model captured the observed pharmacokinetics for Intermezzo® sublingual tablets (R (2) > 0.9). The predicted deviations (%) for C max, AUC0-inf, AUC0-20 min, and T max were 5.7, 28.0, 11.8, and 28.6%, respectively, indicating good prediction accuracy. The model also estimated ~18% of total drug was absorbed via the IO route. Furthermore, the sensitivity analysis indicated that the F a_IO was not only associated with drug diffusivity and unbound fraction in epithelium tissue (f ut) but also depended on the physicochemical properties of compounds for IO delivery (e.g., solubility and logD pH = 7.4). The novel physiologically based IO absorption OCCAT™ model showed satisfactory performance and will be helpful to guide development of future intraoral formulations.

Indexed as

Models, BiologicalAdministration, OralAdministration, SublingualArea Under CurveComputer SimulationDrug DesignHumansHypnotics and SedativesMouthMouth MucosaPyridinesSolubilityTabletsZolpidemHypnotics and SedativesPyridinesTabletsZolpidem

Identifiers

PMID25716146
PMCPMC4406949

What OpenQuestion holds

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Read underepoch 390

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.