Evaluating Skin Sensitization Via Soft and Hard Multivariate Modeling

Abstract

Allergic contact dermatitis is the most frequent manifestation of immunotoxicity in humans with a prevalence rate of 15% to 20% over general population. Skin sensitization is a complex end point that was for a long time being evaluated using animal testing. Great efforts have been made to completely substitute the use of animals and replace them by integrating data from in vitro and in chemico assays with in sil ico calculated parameters. However, it remains undefined how to make the best use of the cumulative data in such a way that information gain is maximized and accomplished with the fewest number of tests possible. In this work, 3 skin sensitization prediction models were considered: one to discriminate sensitizers from non-sensitizers, considering a 2-level scale; one according to the GHS, considering a 3-level scale; and the other to categorize potency in a 6-level scale, according to available human data. We used a data set of known human skin allergens for which i n vitro, in chemico, and in silico descriptors where available to build classifiers based on soft and hard multivariate modeling. Model building, optimization, and refinement resulted in 100% accuracy in distinguishing between sensitizers and non-sensitizers. The same model was able to perform the characterization, in 3 and 6 levels, respectively, with 98.8 and 97.5% accuracy. Combining data from in vitro and in chemico tests with in silico descriptors is relatively simple to implement and some predictors are fitting the adverse outcome pathway for skin sensitization.

In silico Prediction of Skin Sensitization: Quo vadis?

“…Moreover, the models reached an accuracy of 100% in differentiating sensitizers from non-sensitizers. When the same model was, it exhibited the accuracies of 98.8 and 97.5% accuracy when applied to the compounds based on GHS classification (3-level scales) and human data (6-level scales), respectively ( Silva et al, 2020 ).…”

Development of a method for evaluating skin dullness: A mathematical model explaining dullness by the color, optical properties, and microtopography of the skin

“…R 2 > 0.5 represents a high level of confidence in the prediction whereas 0.3 < R 2 < 0.5 indicates acceptable prediction accuracy. PLS analysis is adopted in a wide range of research fields, including skin sensory evaluation and drug efficacy evaluation 10–15 . In the present study, we applied PLS analysis to explain the sensory evaluation of skin dullness using skin parameters and proposed that the perception of dullness is age dependent among Japanese women.…”

“…PLS analysis is adopted in a wide range of research fields, including skin sensory evaluation and drug efficacy evaluation. [10][11][12][13][14][15] In the present study, we applied PLS analysis to explain the sensory evaluation of skin dullness using skin parameters and proposed that the perception of dullness is age dependent among Japanese women. Such methodology and this paper's insights into physiological changes can be applied to define the perception of dullness on a global scale in the future.…”

A Hydrophilic Sulfated Resveratrol Derivative for Topical Application: Sensitization and Anti-Allergic Potential

“…Other skin disturbances can also be driven by immune system issues, illnesses, and normal aging [ 2 , 3 ]. Currently, over 4000 substances have been classified as skin allergens, with some of them found in a wide range of consumer products such as cosmetics, cleaning agents, and perfumes [ 4 , 5 , 6 , 7 , 8 ]. Indeed, skin sensitization has been identified as a critical adverse effect of a wide range of chemicals, and the related disease, allergic contact dermatitis (ACD), can severely impact one’s quality of life [ 7 ].…”