Raspberry pi: Assessments of emerging organic chemicals by the predictive <i>in silico</i> methods

Arulanandam, Charli Deepak; Prathiviraj, R.; Kaveriyappan, Govindarajan Rasiravathanahalli

doi:10.1101/2021.01.15.426465

Cited by 1 publication

(1 citation statement)

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“…These data provide valuable resources for building some in silico models to assess the covert of skin sensitization. In addition, the skin sensitization QSAR models can be applied to not only cosmetic ingredients but also the compound, which can impact the ecosystems such as dye pollution, the effect of personal care products on aquatic species, or plasticizers (Arulanandam et al, 2021;Funar-Timofei and Ilia, 2020;Khan et al, 2020) as well as the pharmacokinetics profiles of low molecular weight oligohydroxyalkanoates (Roman et al, 2020), suggesting that the skin sensitization models has a wide range of applications. To date, most of the published skin sensitization models are qualitative predictions, viz.…”

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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