Accounting for data variability, a key factor in in vivo/in vitro relationships: application to the skin sensitization potency (in vivo LLNA versus in vitro DPRA) example.

When searching for alternative methods to animal testing, confidently rescaling an in vitro result to the corresponding in vivo classification is still a challenging problem. Although one of the most important factors affecting good correlation is sample characteristics, they are very rarely integrated into correlation studies. Usually, in these studies, it is implicitly assumed that both compared values are error-free numbers, which they are not. In this work, we propose a general methodology to analyze and integrate data variability and thus confidence estimation when rescaling from one test to another. The methodology is demonstrated through the case study of rescaling the in vitro Direct Peptide Reactivity Assay (DPRA) reactivity to the in vivo Local Lymph Node Assay (LLNA) skin sensitization potency classifications. In a first step, a comprehensive statistical analysis evaluating the reliability and variability of LLNA and DPRA as such was done. These results allowed us to link the concept of gray zones and confidence probability, which in turn represents a new perspective for a more precise knowledge of the classification of chemicals within their in vivo OR in vitro test. Next, the novelty and practical value of our methodology introducing variability into the threshold optimization between the in vitro AND in vivo test resides in the fact that it attributes a confidence probability to the predicted classification. The methodology, classification and screening approach presented in this study are not restricted to skin sensitization only. They could be helpful also for fate, toxicity and health hazard assessment where plenty of in vitro and in chemico assays and/or QSARs models are available. Copyright © 2016 John Wiley & Sons, Ltd.

Surfactant-polymer interactions: molecular architecture does matter.

Polymer-surfactant mixtures are found in many industrial formulations, and hence there is a significant interest in understanding, at a molecular level, how the self-assembly of surfactant is affected by oppositely-charged polyelectrolytes (PEs). We use self-consistent field modeling and show that the modes of interaction of PEs strongly depend on the architecture of the PE on the segmental level. Hydrophilic cationic PEs with their charge proximal to the linear backbone are expected to bind electrostatically to the outsides of the coronas of the spherical micelles of anionic surfactants, such as sodium laureth sulphate (SLES). As a result, the surfactant aggregation number increases, but at the same time the colloidal stability deteriorates, due to bridging of the PEs between micelles. PEs with their charge somewhat displaced from the backbone by way of short hydrophobic spacers, are expected to be present inside a micelle at the core-corona boundary. In this case the aggregation number decreases, yet the colloidal stability is retained. Hence, SLES tends to remove hydrophilic PEs from an aqueous solution, whereas it solubilizes more hydrophobic ones. The binding isotherm shows that the uptake of PEs remains typically below charge compensation and in this case the spherical micelle topology remains the preferred state.

TIMES-SS--recent refinements resulting from an industrial skin sensitisation consortium.

The TImes MEtabolism Simulator platform for predicting Skin Sensitisation (TIMES-SS) is a hybrid expert system, first developed at Bourgas University using funding and data from a consortium of industry and regulators. TIMES-SS encodes structure-toxicity and structure-skin metabolism relationships through a number of transformations, some of which are underpinned by mechanistic 3D QSARs. The model estimates semi-quantitative skin sensitisation potency classes and has been developed with the aim of minimising animal testing, and also to be scientifically valid in accordance with the OECD principles for (Q)SAR validation. In 2007 an external validation exercise was undertaken to fully address these principles. In 2010, a new industry consortium was established to coordinate research efforts in three specific areas: refinement of abiotic reactions in the skin (namely autoxidation) in the skin, refinement of the manner in which chemical reactivity was captured in terms of structure-toxicity rules (inclusion of alert reliability parameters) and defining the domain based on the underlying experimental data (study of discrepancies between local lymph node assay Local Lymph Node Assay (LLNA) and Guinea Pig Maximisation Test (GPMT)). The present paper summarises the progress of these activities and explains how the insights derived have been translated into refinements, resulting in increased confidence and transparency in the robustness of the TIMES-SS predictions.