Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Time Is Key: Early Diagnosis of Post-Transplant Lymphoproliferative Disorder Presenting as Primary CNS Diffuse Large B-Cell Lymphoma.

Current oncology (Toronto, Ont.)·2026
Same author

Differences in Safety Risks Across Languages in Health-Relevant Queries: Vulnerability Analysis of Large Language Model Responses.

JMIR formative research·2026
Same author

Designing Psychologically Grounded Artificial Intelligence for Supporting Bystander-Based Cyberaggression Intervention: Mixed Methods Exploratory Study.

JMIR formative research·2026
Same author

Fairness aware subset selection for advancing equity in skin cancer detection.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Engineering the Future of Heart Failure Therapeutics: Integrating 3D Printing, Silicone Molding, and Translational Development for Implantable Cardiac Devices.

Bioengineering (Basel, Switzerland)·2026
Same author

Managing Obesity in Heart Failure Patients: Current Evidence and Strategies.

The American journal of cardiology·2026

Related Experiment Video

Updated: Mar 19, 2026

Cultivating a Three-dimensional Reconstructed Human Epidermis at a Large Scale
08:49

Cultivating a Three-dimensional Reconstructed Human Epidermis at a Large Scale

Published on: May 28, 2021

13.5K

Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

Konda Leela Sarath Kumar1,2, Sujit R Tangadpalliwar1,2, Aarti Desai1

  • 1LABS, Persistent Systems Limited, Pune, Maharashtra, India.

Plos One
|June 9, 2016
PubMed
Summary

A new computational tool, SkinSense, offers improved accuracy and coverage for predicting skin sensitization, addressing limitations of current methods. This advance supports the cosmetic and dermatology industries by reducing animal testing, time, and costs.

More Related Videos

An In Vitro Skin Irritation Test SIT using the EpiDerm Reconstructed Human Epidermal RHE Model
21:16

An In Vitro Skin Irritation Test SIT using the EpiDerm Reconstructed Human Epidermal RHE Model

Published on: July 13, 2009

69.3K
Generation of a Simplified Three-Dimensional Skin-on-a-chip Model in a Micromachined Microfluidic Platform
06:30

Generation of a Simplified Three-Dimensional Skin-on-a-chip Model in a Micromachined Microfluidic Platform

Published on: May 17, 2021

5.0K

Related Experiment Videos

Last Updated: Mar 19, 2026

Cultivating a Three-dimensional Reconstructed Human Epidermis at a Large Scale
08:49

Cultivating a Three-dimensional Reconstructed Human Epidermis at a Large Scale

Published on: May 28, 2021

13.5K
An In Vitro Skin Irritation Test SIT using the EpiDerm Reconstructed Human Epidermal RHE Model
21:16

An In Vitro Skin Irritation Test SIT using the EpiDerm Reconstructed Human Epidermal RHE Model

Published on: July 13, 2009

69.3K
Generation of a Simplified Three-Dimensional Skin-on-a-chip Model in a Micromachined Microfluidic Platform
06:30

Generation of a Simplified Three-Dimensional Skin-on-a-chip Model in a Micromachined Microfluidic Platform

Published on: May 17, 2021

5.0K

Area of Science:

  • Toxicology
  • Computational Chemistry
  • Dermatology

Background:

  • Skin sensitization is a critical toxicological endpoint for cosmetic and dermatological products.
  • The ban on animal testing necessitates alternative methods for assessing skin sensitization.
  • Existing computational tools often suffer from high false positive rates or limited coverage.

Purpose of the Study:

  • To develop an integrated computational solution (SkinSense) for predicting skin sensitization.
  • To overcome the limitations of current in silico methods for skin sensitization assessment.

Main Methods:

  • Development of SkinSense integrating Quantitative Structure-Activity Relationship (QSAR) models, similarity analysis, and literature-derived substructure patterns.
  • Evaluation of prediction performance on a challenge set of molecules.

Main Results:

  • SkinSense achieved an accuracy of 75.32%, CCR of 74.36%, sensitivity of 70.00%, and specificity of 78.72%.
  • Performance metrics surpassed those of VEGA, DEREK, and TOPKAT.
  • While TIMES-SS showed higher predictive power, its coverage was significantly limited.

Conclusions:

  • SkinSense provides improved prediction performance and coverage for skin sensitization assessment.
  • The tool can be utilized as an expert system within Integrated Approaches to Testing and Assessment (IATA).
  • It offers significant value to the cosmetic and dermatology industries for molecule pre-screening, reducing time, cost, and animal use.