Evidence map›Paper›PMID 35215362›Full record

ArticlePharmaceuticals (Basel, Switzerland)2022

In Vitro-In Silico Modeling of Caffeine and Diclofenac Permeation in Static and Fluidic Systems with a 16HBE Lung Cell Barrier.

Lukas Kovar, Lena Wien, Dominik Selzer, Yvonne Kohl, Robert Bals, Thorsten Lehr

Abstract read
In one paragraph

Article in Pharmaceuticals (Basel, Switzerland), 2022. 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

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.

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
  2. Article
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.

Lukas KovarDepartment of Clinical Pharmacy, Saarland University, 66123 Saarbrucken, Germany.ORCID 0000-0003-1832-5498
Lena WienFraunhofer Institute for Biomedical Engineering IBMT, 66280 Sulzbach, Germany.
Dominik SelzerDepartment of Clinical Pharmacy, Saarland University, 66123 Saarbrucken, Germany.
Yvonne KohlFraunhofer Institute for Biomedical Engineering IBMT, 66280 Sulzbach, Germany.ORCID 0000-0001-8119-5441
Robert BalsDepartment of Internal Medicine V, Saarland University, 66421 Homburg, Germany.
Thorsten LehrDepartment of Clinical Pharmacy, Saarland University, 66123 Saarbrucken, Germany.ORCID 0000-0002-8372-1465

Funding

Federal Ministry of Education and Research 031L0153
6 · The paper itself

Abstract

Static in vitro permeation experiments are commonly used to gain insights into the permeation properties of drug substances but exhibit limitations due to missing physiologic cell stimuli. Thus, fluidic systems integrating stimuli, such as physicochemical fluxes, have been developed. However, as fluidic in vitro studies display higher complexity compared to static systems, analysis of experimental readouts is challenging. Here, the integration of in silico tools holds the potential to evaluate fluidic experiments and to investigate specific simulation scenarios. This study aimed to develop in silico models that describe and predict the permeation and disposition of two model substances in a static and fluidic in vitro system. For this, in vitro permeation studies with a 16HBE cellular barrier under both static and fluidic conditions were performed over 72 h. In silico models were implemented and employed to describe and predict concentration-time profiles of caffeine and diclofenac in various experimental setups. For both substances, in silico modeling identified reduced apparent permeabilities in the fluidic compared to the static cellular setting. The developed in vitro-in silico modeling framework can be expanded further, integrating additional cell tissues in the fluidic system, and can be employed in future studies to model pharmacokinetic and pharmacodynamic drug behavior.

Indexed as

16HBEcaffeinediclofenacfluidic systemin vitro–in silico modelingstatic system

Identifiers

PMID35215362
PMCPMC8876625

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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.