Evaluation of the global performance of eight in silico skin sensitization models using human data

Golden, Emily

doi:10.14573/altex.1911261

Cited by 14 publications

(33 citation statements)

References 53 publications

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“…The final step of the process for strategic development of KOS development is in its evaluation. Although computational approaches to chemical assessment are still in very early development, and none that we are aware of use semantic data, a nascent predictive toxicology application based on AOPs has already been attempted (Burgoon 2017), and a comparison has been made between in silico approaches to in vivo assays and human data for identifying skin sensitizers (Luechtefeld et al 2018;Golden 2020). These are suggestive of the future direction of computational toxicology and would be well supported by KOSs that make computationally accessible the human knowledge written up in scientific documents.…”

Section: Escaping the Streetlightmentioning

confidence: 99%

Knowledge Organization Systems for Systematic Chemical Assessments

Whaley

Edwards

Kraft

et al. 2020

Environ Health Perspect

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Background: Although the implementation of systematic review and evidence mapping methods stands to improve the transparency and accuracy of chemical assessments, they also accentuate the challenges that assessors face in ensuring they have located and included all the evidence that is relevant to evaluating the potential health effects an exposure might be causing. This challenge of information retrieval can be characterized in terms of “semantic” and “conceptual” factors that render chemical assessments vulnerable to the streetlight effect. Objectives: This commentary presents how controlled vocabularies, thesauruses, and ontologies contribute to overcoming the streetlight effect in information retrieval, making up the key components of Knowledge Organization Systems (KOSs) that enable more systematic access to assessment-relevant information than is currently achievable. The concept of Adverse Outcome Pathways is used to illustrate what a general KOS for use in chemical assessment could look like. Discussion: Ontologies are an underexploited element of effective knowledge organization in the environmental health sciences. Agreeing on and implementing ontologies in chemical assessment is a complex but tractable process with four fundamental steps. Successful implementation of ontologies would not only make currently fragmented information about health risks from chemical exposures vastly more accessible, it could ultimately enable computational methods for chemical assessment that can take advantage of the full richness of data described in natural language in primary studies. https://doi.org/10.1289/EHP6994

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Section: Escaping the Streetlightmentioning

confidence: 99%

Knowledge Organization Systems for Systematic Chemical Assessments

Whaley

Edwards

Kraft

et al. 2020

Environ Health Perspect

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“…Therefore, Pubchem database was used to retrieve isomeric (when available) or canonical simplified molecular-input lineentry system (SMILES) of each compound [33]. This information was used without further treatment in Molinspiration [34], pkCSM [35], SwissADME [36,37] and Pred-Skin [38,39] cheminformatic tools.…”

Section: Methodsmentioning

confidence: 99%

“…Regarding the predicted skin sensitization, pkCSM database results differed from the ones provided by Pred-Skin (Table 3). This difference may be attributed to distinct algorithms and weightings employed when imputed information was compiled [35,38,39]. Regardless of the case, Pred-Skin results were sound when compared to empiric investigations, which showcased the skin sensitizing effects of LF by different in vitro and in vivo approaches [1,3,59,60].…”

Section: Figurementioning

confidence: 99%

Exploring Cheminformatic Toolsets for Predicting the Dermal Toxicity of Furanocoumarins

Thomaz

Oliveira

Silva

et al. 2021

PoS

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Linear furanocoumarins are skin sensitizers and anticancer agents whose appeal in skincare therapeutics is widely exploited. Owing to the need to predict the biological activities of medicines, this work aimed the investigate the predicted dermal toxicity of linear furanocoumarins through chemoinformatic approaches. Therefore, eight major linear furanocoumarins of interest in medicine were selected, and their pharmacophores / toxicophores were modelled and inputted in several databases and cheminformatic toolsets previously described in the literature. Moreover, Principal Components Analysis was performed to allow multivariable comparisons. Results showcased that the first two PCs accounted for 95.48% of all variance in the model, and molecular weight and polar surface showcased a positive correlation to Log P and Log K p , which may be involved in skin penetration. Moreover, the pharmacophore modelling evidenced superimposition between linear furanocoumarins, ethidium bromide and acridine orange, thereby suggesting that these compounds share similar biological effects, supported by their acknowledged DNA intercalating activities. Therefore, this work showcased the application of various cheminformatic tools to screen the dermal toxicity of chemicals.

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“…In 2020, Golden et al carried out an investigation, which compared the accuracy of eight in silico models (PredSkin, Toxtree, QSAR Toolbox, Danish QSAR database, CAESAR, REACHAcross™, TIMES-S and Derek Nexus) against human data sets. Most of the models showed the accuracies of 70–80% on human data sets, suggesting that in silico models can be a convenient and inexpensive tool to define the skin sensitization in human ( Golden et al, 2021 ). There is no doubt that an in silico model to predict skin sensitization based on human data will be more realistic and much needed.…”

Section: Future Perspectivesmentioning

confidence: 99%

In silico Prediction of Skin Sensitization: Quo vadis?

Weng²,

Leong

2021

Front. Pharmacol.

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Skin direct contact with chemical or physical substances is predisposed to allergic contact dermatitis (ACD), producing various allergic reactions, namely rash, blister, or itchy, in the contacted skin area. ACD can be triggered by various extremely complicated adverse outcome pathways (AOPs) remains to be causal for biosafety warrant. As such, commercial products such as ointments or cosmetics can fulfill the topically safe requirements in animal and non-animal models including allergy. Europe, nevertheless, has banned animal tests for the safety evaluations of cosmetic ingredients since 2013, followed by other countries. A variety of non-animal in vitro tests addressing different key events of the AOP, the direct peptide reactivity assay (DPRA), KeratinoSens™, LuSens and human cell line activation test h-CLAT and U-SENS™ have been developed and were adopted in OECD test guideline to identify the skin sensitizers. Other methods, such as the SENS-IS are not yet fully validated and regulatorily accepted. A broad spectrum of in silico models, alternatively, to predict skin sensitization have emerged based on various animal and non-animal data using assorted modeling schemes. In this article, we extensively summarize a number of skin sensitization predictive models that can be used in the biopharmaceutics and cosmeceuticals industries as well as their future perspectives, and the underlined challenges are also discussed.

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Evaluation of the global performance of eight in silico skin sensitization models using human data

Cited by 14 publications

References 53 publications

Knowledge Organization Systems for Systematic Chemical Assessments

Knowledge Organization Systems for Systematic Chemical Assessments

Exploring Cheminformatic Toolsets for Predicting the Dermal Toxicity of Furanocoumarins

In silico Prediction of Skin Sensitization: Quo vadis?

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