Mechanistic Skin Modeling of Plasma Concentrations of Sunscreen Active Ingredients Following Facial Application

Sunscreen products constitute two distinct categories. Recreational sunscreens protect against high-intensity, episodic sun exposure, often applied over the entire body. In contrast, facial sunscreen products are designed for sub-erythemal, low-intensity daily sun exposure. Such different exposures necessitate distinctive product safety assessments. Building on earlier methods for predicting dermal disposition, a mechanistic model was developed to simulate plasma concentrations of seven organic sunscreen active ingredients: avobenzone, ensulizole, homosalate, octinoxate, octisalate, octocrylene, and oxybenzone, following facial application. In vitro permeation testing (IVPT) was performed with two different vehicles using a subset of the UV filters. These IVPT results, in addition to previously published IVPT data and published in vivo Maximal Usage Trial (MUsT) data for the UV filters, were used to train the mechanistic dermal model via a Bayesian Markov chain Monte Carlo (MCMC) method. An external validation of the trained model with real-world in vivo datasets demonstrated that the model's predicted UV filter plasma concentrations align well with experimental measurements and capture the observed inter-individual variability. Predictions of steady-state UV filter plasma concentrations under facial application scenarios at 5% concentration and at the maximal allowable concentrations were then generated by the trained model. Oxybenzone had the greatest predicted plasma concentration following facial application. Homosalate and octisalate predictions had high uncertainty associated with the absence of data. Several application scenarios pertaining to avobenzone, ensulizole, octocrylene and octinoxate were identified in which median plasma concentration levels were at 0.5 ng/ml or below when applied in the recreational or facial product. Model limitations include uncertainty in vehicle/water partitioning, formulation metamorphosis, and UV filter systemic clearance, all of which can be refined with additional data. For UV filters, limiting exposure to facial application reduces human safety concerns based on FDA established thresholds.

A chemical structure-based approach for estimating the added levels of flavourings to foods for the purpose of assessing consumer intake

Intake assessment and hazard profile of chemical substances are the two critical inputs in a safety assessment. Human intake assessment presents challenges that stem either from the absence of data or from numerous sources of variability and uncertainty, which have led regulators to adopt conservative approaches that inevitably overestimate intake. Refinements of intake assessments produce more realistic estimates and help prioritise areas of concern and better direct investment of resources. However, use levels (ULs), which represent the usual added amount of flavourings to food products, are the starting point for refined intake assessments, are data-intensive, and data availability is often a limitation. The work presented here was undertaken to investigate the use level patterns of substances used as flavourings in foods and to develop a systematic tool for data extrapolation based on chemical structure. The available dataset consists of use levels reported through eight industry surveys and hence are representative of industry uses rather than regulatory limits, which are higher by design and not realistic. A systematic statistical analysis was undertaken to determine whether the industry-reported UL data can be used to estimate use levels of flavouring substances belonging to the same chemical group for which such data are not available. Predictive modelling approaches were explored to evaluate relationships in the data and utilised additional variables relevant to technological considerations, such as volatility losses upon heat treatment, and Tanimoto index-based pair-wise structural similarity scores to determine whether more granular similarity information can reduce the within-group variability. The analyses indicated that the use levels of flavouring substances can reasonably be estimated based on the available data using chemical group classifications stratified by food category. Source of uncertainty and limitations are discussed.

Absence of mutagenic activity in the bacterial reverse mutation assay with pulegone and peppermint oil

The essential oil of peppermint and one of its natural constituents, (R)-(+)-pulegone, are approved flavorings added to food worldwide. (R)-(+)-Pulegone and peppermint oil were tested separately in two independent bacterial reverse mutation assays according to Organisation for Economic Co-operation and Development Guideline 471. Both flavorings did not produce any evidence of mutagenicity up to cytotoxic concentrations in either the presence or the absence of exogenous metabolic activation.

Insights and perspectives on emerging inputs to weight of evidence determinations for food safety: workshop proceedings

This workshop aimed to elucidate the contribution of computational and emerging in vitro methods to the weight of evidence used by risk assessors in food safety assessments. The following issues were discussed: using in silico and high-throughput screening (HTS) data to confirm the safety of approved food ingredients, applying in silico and HTS data in the process of assessing the safety of a new food ingredient, and utilizing in silico and HTS data in communicating the safety of food ingredients while enhancing the public's trust in the food supply. Perspectives on integrating computational modeling and HTS assays as well as recommendations for optimizing predictive methods for risk assessment were also provided. Given the need to act quickly or proceed cautiously as new data emerge, this workshop also focused on effectively identifying a path forward in communicating in silico and in vitro data.

Determining the applicability of threshold of toxicological concern approaches to substances found in foods

Threshold of Toxicological Concern (TTC) decision-support methods present a pragmatic approach to using data from well-characterized chemicals and protective estimates of exposure in a stepwise fashion to inform decisions regarding low-level exposures to chemicals for which few data exist. It is based on structural and functional categorizations of chemicals derived from decades of animal testing with a wide variety of chemicals. Expertise is required to use the TTC methods, and there are situations in which its use is clearly inappropriate or not currently supported. To facilitate proper use of the TTC, this paper describes issues to be considered by risk managers when faced with the situation of an unexpected substance in food. Case studies are provided to illustrate the implementation of these considerations, demonstrating the steps taken in deciding whether it would be appropriate to apply the TTC approach in each case. By appropriately applying the methods, employing the appropriate scientific expertise, and combining use with the conservative assumptions embedded within the derivation of the thresholds, the TTC can realize its potential to protect public health and to contribute to efficient use of resources in food safety risk management.