Comparison of Cramer classification between Toxtree, the OECD QSAR Toolbox and expert judgment.

The Threshold of Toxicological Concern (TTC) is a pragmatic approach in risk assessment. In the absence of data, it sets up levels of human exposure that are considered to have no appreciable risk to human health. The Cramer decision tree is used extensively to determine these exposure thresholds by categorizing non-carcinogenic chemicals into three different structural classes. Therefore, assigning an accurate Cramer class to a material is a crucial step to preserve the integrity of the risk assessment. In this study the Cramer class of over 1000 fragrance materials across diverse chemical classes were determined by using Toxtree (TT), the OECD QSAR Toolbox (TB), and expert judgment. Disconcordance was observed between TT and the TB. A total of 165 materials (16%) showed different results from the two programs. The overall concordance for Cramer classification between TT and expert judgment is 83%, while the concordance between the TB and expert judgment is 77%. Amines, lactones and heterocycles have the lowest percent agreement with expert judgment for TT and the TB. For amines, the expert judgment agreement is 45% for TT and 55% for the TB. For heterocycles, the expert judgment agreement is 55% for TT and the TB. For lactones, the expert judgment agreement is 56% for TT and 50% for the TB. Additional analyses were conducted to determine the concordance within various chemical classes. Critical checkpoints in the decision tree are identified. Strategies and guidance on determining the Cramer class for various chemical classes are discussed.

A practical guidance for Cramer class determination.

Expanded use of the Threshold of Toxicological Concern (TTC) methodology has brought into discussion the intent of the original questions used in the Cramer scheme or Cramer decision tree. We have analysed, both manually and by Toxtree software, a large dataset of fragrance ingredients and identified several issues with the original Cramer questions. Some relate to definitions and wording of questions; others relate to in silico interpretation of the questions. We have endeavoured to address all of these inconsistencies and misinterpretations without changing the basic structure and principles of the original decision tree. Based on the analysis of a large data set of over 2500 fragrance ingredients, we found that most of the 33 questions in the original Cramer scheme are straightforward. Through repeated examination each of the 33 questions, we found 14 where the logic underlying the development of the rule is unclear. These questions are well served by minor wording changes and/or further explanation designed to capture what we perceive to be the intent of the original decision tree. The findings reported here could be used as a guidance for conducting Cramer classification and provide advices for the improvement of the in silico tools.

An in silico skin absorption model for fragrance materials.

Fragrance materials are widely used in cosmetics and other consumer products. The Research Institute for Fragrance Materials (RIFM) evaluates the safety of these ingredients and skin absorption is an important parameter in refining systemic exposure. Currently, RIFM's safety assessment process assumes 100% skin absorption when experimental data are lacking. This 100% absorption default is not supportable and alternate default values were proposed. This study aims to develop and validate a practical skin absorption model (SAM) specific for fragrance material. It estimates skin absorption based on the methodology proposed by Kroes et al. SAM uses three default absorption values based on the maximum flux (J(max)) - namely, 10%, 40%, and 80%. J(max) may be calculated by using QSAR models that determine octanol/water partition coefficient (K(ow)), water solubility (S) and permeability coefficient (K(p)). Each of these QSAR models was refined and a semi-quantitative mechanistic model workflow is presented. SAM was validated with a large fragrance-focused data set containing 131 materials. All resulted in predicted values fitting the three-tiered absorption scenario based on Jmax ranges. This conservative SAM may be applied when fragrance material lack skin absorption data.