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.

Summary Several alternative methods to replace animal experiments have been accepted by legal bodies. An even larger number of tests are under development or already in use for non-regulatory applications or for the generation of information stored in proprietary knowledge bases. The next step for the use of the different in vitro methods is their combination into integrated testing strategies (ITS) to get closer to the overall goal of predictive "in vitro-based risk evaluation processes." We introduce here a conceptual framework as the basis for future ITS and their use for risk evaluation without animal experiments. The framework allows incorporation of both individual tests and already integrated approaches. Illustrative examples for elements to be incorporated are drawn from the session "

The overall objective was to identify an accurate computational electronic method to virtually screen phenolic compounds through their antioxidant and free-radical scavenging activity. The impact of a key parameter of the density functional theory (DFT) approach was studied. Performances of the 21 most commonly used exchange-correlation functionals are thus detailed in the evaluation of the main energetic parameters related to the activities of two prototype antioxidants, namely quercetin and edaravone, is reported. These functionals have been chosen among those belonging to three different families of hybrid functionals, namely global, range separated, and double hybrids. Other computational parameters have also been considered, such as basis set and solvent effects. The selected parameters, namely bond dissociation enthalpy (BDE), ionization potential (IP), and proton dissociation enthalpy (PDE) allow a mechanistic evaluation of the antioxidant activities of free radical scavengers. Our results show that all the selected functionals provide a coherent picture of these properties, predicting the same order of BDEs and PDEs. However, with respect to the reference values, the errors found at CBS-Q3 level significantly vary with the functional. Although it is difficult to evidence a global trend from the reported data, it clearly appears that LC-ωPBE, M05-2X, and M06-2X are the most suitable approaches for the considered properties, giving the lowest cumulative mean absolute errors. These methods are therefore suggested for an accurate and fast evaluation of energetic parameters related to an antioxidant activity via free radical scavenging.

Depositing cationic polyelectrolytes (PEs) from micellar solutions that include surfactants (SU) onto surfaces is a rich, complex, highly relevant, and challenging topic that covers a broad field of practical applications (e.g., from industrial to personal care). The role of the molecular architecture of the constituents of the PEs are often overruled, or at least and either, underestimated in regard to the surface properties. In this work, we aim to evaluate the effect of a model biomimetic surface that shares the key characteristics of the extreme surface of hair and its concomitant chemo- and physisorbed properties onto the deposition of a complex PEs:SU system. To tackle out the effect of the molecular architecture of the PEs, we consider (i) a purely linear and hydrophilic PE (P100) and (ii) a PE with lateral amphiphilic chains (PegPE). Using numerical self-consistent field calculations, we show that the architecture of the constituents interfere with the surface properties in a nonintuitive way such that, depending on the amphiphilicity and hydrophilicity of the PEs and the hydrophobicity of the surface, a re-entrant adsorbing transition can be observed, the lipid coverage of the model hair surface being the unique control parameter. Such a behavior is rationalized by the anticooperative associative properties of the coacervate micelles in solution, which is also controlled by the architecture of the PEs and SU. We now expect that PEs adsorption, as a rule, is governed by the molecular details of the species in solution as well as the surface specificities. We emphasize that molecular realistic modeling is essential to rationalize and optimize the adsorption process of, for example, polymer conditioning agents in water-rinsed cosmetic or textile applications.

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.

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.

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