Tag Archive for: No Expected Sensitization Induction Level (NESIL)

Joint publication with L’Oréal: In vitro prediction of skin sensitizing potency using the GARDskin Dose-Response assay: A simple regression approach

New joint publication with L’Oréal.

We are excited to announce the recent publication of a collaborative scientific paper by the expert teams at L’Oréal and SenzaGen, in Toxics MDPI. This peer-reviewed article presents new evidence on the performance of the GARD®skin Dose-Response for quantitative potency assessment of skin sensitizers.

With an extended set of 30 chemicals and a composite potency model for the prediction of sensitizing potency, the study demonstrates the ability of GARD®skin Dose-Response to predict a Point-of-Departure (PoD) for potential skin sensitizers, showing concordance with NESIL values derived from LLNA and Human data.

This research represents a significant advancement in deriving PoD values for chemicals which can be used directly in improving downstream risk assessment strategies.

Gradin R, Tourneix F, Mattson U, Andersson J, Amaral F, Forreryd A, Alépée N, Johansson H. 
Toxics. 2024; 12(9):626. 
https://doi.org/10.3390/toxics12090626

Keywords

NAM; GARDskin Dose-Response; Sensitizing potency; Quantitative risk assessment; Point of departure


Abstract

Toxicological assessments of skin sensitizers have progressed towards a higher reliance on non-animal methods. Current technological trends aim to extend the utility of non-animal methods to accurately characterize skin sensitizer potency.

The GARDskin Dose-Response assay was previously described where it was shown that its main readout, the cDV0 concentration, was associated with skin sensitizing potency. The ability to predict potency in the form of NESILs derived from LLNA or human NOEL, from cDV0, was evaluated. The assessment of a dataset of 30 chemicals showed that the cDV0 values still correlated strongly and significantly with both LLNA EC3 and human NOEL values (ρ = 0.645-0.787 [p < 1×10-3]).

A composite potency value that combined LLNA and human potency data was defined, which aided the performance of the proposed model for the prediction of NESIL. The potency model accurately predicted sensitizing potency, with cross-validation errors of 2.75 and 3.22 fold changes compared with NESILs from LLNA and human, respectively.

In conclusion, the results suggest that the GARDskin Dose-Response assay may be used to derive an accurate quantitative continuous potency estimate of skin sensitizers.

 

Joint publication with IFF and RIFM: GARDskin dose-response assay and its application in conducting Quantitative Risk Assessment (QRA) for fragrance materials using a Next Generation Risk Assessment (NGRA) framework

New joint publication with International Flavors & Fragrances Inc (IFF) and Research Institute for Fragrance Materials (RIFM).

SenzaGen scientists, alongside the scientific teams at International Flavors & Fragrances Inc and Research Institute for Fragrance Materials, have jointly published an article in Regulatory Toxicology and Pharmacology, presenting new peer-reviewed evidence on the performance of the GARD®skin Dose-Response assay for Quantitative Risk Assessment of fragrance materials.

The study results confirm the ability of GARD®skin Dose-Response to predict human NESIL values with good predictive performance, showing good concordance with published reference Human data and demonstrating good reproducibility.

Furthermore, the paper also presents a case study to illustrate how the predicted NESIL value from GARDskin Dose-Response can be used in practice within a NGRA framework to establish a maximum allowable concentration of a sensitizer in different consumer products.

The study represents a major step towards the establishment of the assay to derive NESIL values for conducting QRA evaluations for fragrance materials using an NGRA framework.

Shashikiran Donthamsetty, Andy Forreryd, Paul Sterchele, Xiao Huang, Robin Gradin, Henrik Johansson, Ulrika Mattson, Isabelle Lee, Anne Marie Api, Gregory Ladics,
Regulatory Toxicology and Pharmacology, Volume 149, 2024, 105597, ISSN 0273-2300,
https://doi.org/10.1016/j.yrtph.2024.105597

Keywords

QRA (Quantitative Risk Assesment); Dermal sensitization; Fragrance materials; Next Generation Risk Assesment (NGRA); GARD assay; No Expected Sensitization Induction Level (NESIL); New Approach Methodologies (NAMs); OECD 442E

Highlights

  • Developed a Next Generation Risk Assessment (NGRA) framework for conducting QRA2 for fragrance materials.
  • The GARDskin Dose Response (DR) assay is a reliable and reproducible method for predicting NESIL for fragrance materials.
  • NGRA for QRA2 was validated using isocyclocitral as a case study.


Abstract

Development of New Approach Methodologies (NAMs) capable of providing a No Expected Sensitization Induction Level (NESIL) value remains a high priority for the fragrance industry for conducting a Quantitative Risk Assesment (QRA) to evaluate dermal sensitization. The in vitro GARDskin assay was recently adopted by the OECD (TG 442E) for the hazard identification of skin sensitizers. Continuous potency predictions are derived using a modified protocol that incorporates dose-response measurements. Linear regression models have been developed to predict human NESIL values. The aim of the study was to evaluate the precision and reproducibility of the continuous potency predictions from the GARDskin Dose-Response (DR) assay and its application in conducting QRA for fragrance materials using a Next Generation Risk Assessment (NGRA) framework. Results indicated that the GARDskin Dose-Response model predicted human NESIL values with a good degree of concordance with published NESIL values, which were also reproducible in 3 separate experiments. Using Isocyclocitral as an example, a QRA was conducted to determine its safe use levels in different consumer product types using a NGRA framework. This study represents a major step towards the establishment of the assay to derive NESIL values for conducting QRA evaluations for fragrance materials using a NGRA framework.