Evidence map›Paper›PMID 35456611›Full record

ArticlePharmaceutics2022

Fabrication and Modelling of a Reservoir-Based Drug Delivery System for Customizable Release.

Margarethe Hauck, Jan Dittmann, Berit Zeller-Plumhoff, Roshani Madurawala, Dana Hellmold, Carolin Kubelt, Michael Synowitz, Janka Held-Feindt, Rainer Adelung, Stephan Wulfinghoff and 1 more

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 27% of its field
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

7 citing papers in PubMed, 15 citations in OpenAlex.

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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

11 authors at 3 institutions in 1 country.

Margarethe HauckFunctional Nanomaterials, Institute for Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.
Jan DittmannComputational Materials Science, Institute for Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.
Berit Zeller-PlumhoffInstitute of Metallic Biomaterials, Helmholtz-Zentrum Hereon, Max-Planck-Str. 1, 21502 Geesthacht, Germany.
Roshani MadurawalaFunctional Nanomaterials, Institute for Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.
Dana HellmoldDepartment of Neurosurgery, University Medical Center Schleswig-Holstein UKSH, Campus Kiel, 24105 Kiel, Germany.
Carolin KubeltDepartment of Neurosurgery, University Medical Center Schleswig-Holstein UKSH, Campus Kiel, 24105 Kiel, Germany.
Michael SynowitzDepartment of Neurosurgery, University Medical Center Schleswig-Holstein UKSH, Campus Kiel, 24105 Kiel, Germany.
Janka Held-FeindtDepartment of Neurosurgery, University Medical Center Schleswig-Holstein UKSH, Campus Kiel, 24105 Kiel, Germany.
Rainer AdelungFunctional Nanomaterials, Institute for Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.
Stephan WulfinghoffComputational Materials Science, Institute for Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.
Fabian SchüttFunctional Nanomaterials, Institute for Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.
Hochschule für Angewandte Wissenschaften Kiel · DEUniversity Hospital Schleswig-Holstein · DEHelmholtz-Zentrum Hereon · DE

Funding

Deutsche Forschungsgemeinschaft GRK2154
6 · The paper itself

Abstract

Localized therapy approaches have emerged as an alternative drug administration route to overcome the limitations of systemic therapies, such as the crossing of the blood-brain barrier in the case of brain tumor treatment. For this, implantable drug delivery systems (DDS) have been developed and extensively researched. However, to achieve an effective localized treatment, the release kinetics of DDS needs to be controlled in a defined manner, so that the concentration at the tumor site is within the therapeutic window. Thus, a DDS, with patient-specific release kinetics, is crucial for the improvement of therapy. Here, we present a computationally supported reservoir-based DDS (rDDS) development towards patient-specific release kinetics. The rDDS consists of a reservoir surrounded by a polydimethylsiloxane (PDMS) microchannel membrane. By tailoring the rDDS, in terms of membrane porosity, geometry, and drug concentration, the release profiles can be precisely adapted, with respect to the maximum concentration, release rate, and release time. The release is investigated using a model dye for varying parameters, leading to different distinct release profiles, with a maximum release of up to 60 days. Finally, a computational simulation, considering exemplary in vivo conditions (e.g., exchange of cerebrospinal fluid), is used to study the resulting drug release profiles, demonstrating the customizability of the system. The establishment of a computationally supported workflow, for development towards a patient-specific rDDS, in combination with the transfer to suitable drugs, could significantly improve the efficacy of localized therapy approaches.

Indexed as

computational modellingdiffusion-controlleddrug delivery systemdrug reservoirglioblastoma

Identifiers

PMID35456611
PMCPMC9025308
OpenAlexW4224317163

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.