Evidence map›Paper›PMID 22172168›Full record

ArticleChemical biology & drug design2012

Virtual design of chemical penetration enhancers for transdermal drug delivery.

Sharath Golla, Brian J Neely, Eric Whitebay, Sundar Madihally, Robert L Robinson, Khaled A M Gasem

Abstract read
In one paragraph

Article in Chemical biology & drug design, 2012. 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
–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

7 citing papers in PubMed.

  1. Unraveling the Potential of Vitamin BMolecular pharmaceutics · 2024
    Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Computational methods in drug discovery.Pharmacological reviews · 2014
    Review
  7. 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.

Sharath GollaSchool of Chemical Engineering, Oklahoma State University, Stillwater, OK, USA.
Brian J Neely
Eric Whitebay
Sundar Madihally
Robert L Robinson
Khaled A M Gasem

Funding

Design of Chemical Penetration Enhancers for Transdermal Drug DeliveryR21EB005749 · NIBIB · OKLAHOMA STATE UNIVERSITY STILLWATER · PI GASEM, K A.M. · 2006 to 2007
$396k
NIBIB NIH HHS 1R21EB005749NIBIB NIH HHS R21 EB005749
6 · The paper itself

Abstract

Traditional drug design is a laborious and expensive process that often challenges the pharmaceutical industries. As a result, researchers have turned to computational methods for computer-assisted molecular design. Recently, genetic and evolutionary algorithms have emerged as efficient methods in solving combinatorial problems associated with computer-aided molecular design. Further, combining genetic algorithms with quantitative structure-property relationship analyses has proved effective in drug design. In this work, we have integrated a new genetic algorithm and nonlinear quantitative structure-property relationship models to develop a reliable virtual screening algorithm for the generation of potential chemical penetration enhancers. The genetic algorithms-quantitative structure-property relationship algorithm has been implemented successfully to identify potential chemical penetration enhancers for transdermal drug delivery of insulin. Validation of the newly identified chemical penetration enhancer molecular structures was conducted through carefully designed experiments, which elucidated the cytotoxicity and permeability of the chemical penetration enhancers.

Indexed as

Computer-Aided DesignSkin AbsorptionAdministration, CutaneousAlgorithmsAnimalsHumansPermeabilityPharmaceutical PreparationsPharmaceutical VehiclesQuantitative Structure-Activity RelationshipSkinPharmaceutical PreparationsPharmaceutical Vehicles

Identifiers

PMID22172168
PMCPMC3467970

What OpenQuestion holds

Textmetadata
LicenceTDM
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.