Toxins in Botanical Drugs and Plant-derived Food and Feed - from Science to Regulation: A Workshop Review

In September 2022, the 3rd International Workshop on pyrrolizidine alkaloids (PAs) and related phytotoxins was held on-line, entitled 'Toxins in botanical drugs and plant-derived food and feed - from science to regulation'. The workshop focused on new findings about the occurrence, exposure, toxicity, and risk assessment of PAs. In addition, new scientific results related to the risk assessment of alkenylbenzenes, a distinct class of herbal constituents, were presented. The presence of PAs and alkenylbenzenes in plant-derived food, feed, and herbal medicines has raised health concerns with respect to their acute and chronic toxicity but mainly related to the genotoxic and carcinogenic properties of several congeners. The compounds are natural constituents of a variety of plant families and species widely used in medicinal, food, and feed products. Their individual occurrence, levels, and toxic properties, together with the broad range of congeners present in nature, represent a striking challenge to modern toxicology. This review tries to provide an overview of the current knowledge on these compounds and indicates needs and perspectives for future research.

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.

Enhancement of Skin Permeability Prediction through PBPK Modeling, Bayesian Inference, and Experiment Design

Physiologically based pharmacokinetic (PBPK) models of skin absorption are a powerful resource for estimating drug delivery and chemical risk of dermatological products. This paper presents a PBPK workflow for the quantification of the mechanistic determinants of skin permeability and the use of these quantities in the prediction of skin absorption in novel contexts. A state-of-the-art mechanistic model of dermal absorption was programmed into an open-source modeling framework. A sensitivity analysis was performed to identify the uncertain compound-specific, individual-specific, and site-specific model parameters that impact permeability. A Bayesian Markov Chain Monte Carlo algorithm was employed to derive distributions of these parameters given in vitro experimental permeability measurements. Extrapolations to novel contexts were generated by simulating the model following its update with samples drawn from the learned distributions as well as parameters that represent the intended scenario. This algorithm was applied multiple times, each using a unique set of permeability measurements sourced under experimental contexts that differ in terms of the compound, vehicle pH, skin sample anatomical site, and the number of compounds under which each subject's skin samples were tested. Among the data sets used in this study, the highest accuracy and precision in the extrapolated permeability was achieved in those that include measurements conducted under multiple vehicle pH levels and in which individual subjects' skin samples are tested under multiple compounds. This work thus identifies factors for consideration in the design of experiments for the purpose of training dermal models to robustly estimate drug delivery and chemical risk.

A Mechanistic Bayesian Inferential Workflow for Estimation of In Vivo Skin Permeation from In Vitro Measurements

Computational models can play an integral role in the chemical risk assessment of dermatological products. However, a limitation on the ability of mathematical models to extrapolate from in vitro measurements to in human predictions arises from context-dependence: modeling assumptions made in one setting may not carry over to another scenario. Mechanistic models of dermal absorption relate the skin penetration kinetics of permeants to their partitioning and diffusion across elementary sub-compartments of the skin. This endows them with a flexibility through which specific model components can be adjusted to better reflect dermal absorption in contexts that differ from the in vitro setting, while keeping fixed any context-invariant parameters that remain unchanged in the two scenarios. This paper presents a workflow for predicting in vivo dermal absorption by integrating a mechanistic model of skin penetration with in vitro permeation test (IVPT) measurements. A Bayesian approach is adopted to infer a joint posterior distribution of context-invariant model parameters. By populating the model with samples of context-invariant parameters from this distribution and adjusting context-dependent parameters to suit the in vivo setting, simulations of the model yield estimates of the likely range of in vivo dermal absorption given the IVPT data. This workflow is applied to five compounds previously tested in vivo. In each case, the range of in vivo predictions encompassed the range observed experimentally. These studies demonstrate that the proposed workflow enables the derivation of mechanistically derived upper bounds on dermal absorption for the purposes of chemical risk assessment.

Use of in vitro metabolism and biokinetics assays to refine predicted in vivo and in vitro internal exposure to the cosmetic ingredient, phenoxyethanol, for use in risk assessment

A novel approach was developed to help characterize the biokinetics of the cosmetic ingredient, phenoxyethanol, to help assess the safety of the parent and its major stable metabolite. In the first step of this non-animal tiered approach, primary human hepatocytes were used to confirm or refute in silico predicted metabolites, and elucidate the intrinsic clearance of phenoxyethanol. A key result was the identification of the major metabolite, phenoxyacetic acid (PAA), the exposure to which in the kidney was subsequently predicted to far exceed that of phenoxyethanol in blood or other tissues. Therefore, a novel aspect of this approach was to measure in the subsequent step the formation of PAA in the cells dosed with phenoxyethanol that were used to provide points of departure (PoDs) and express the intracellular exposure as the Cmax and AUC24. This enabled the calculation of the intracellular concentrations of parent and metabolite at the PoD in the cells used to derive this value. These concentrations can be compared with in vivo tissue levels to conclude on the safety margin. The lessons from this case study will help to inform the design of other non-animal safety assessments.

Novel Insights into Pyrrolizidine Alkaloid Toxicity and Implications for Risk Assessment: Occurrence, Genotoxicity, Toxicokinetics, Risk Assessment-A Workshop Report

This paper reports on the major contributions and results of the 2nd International Workshop of Pyrrolizidine Alkaloids held in September 2020 in Kaiserslautern, Germany. Pyrrolizidine alkaloids are among the most relevant plant toxins contaminating food, feed, and medicinal products of plant origin. Hundreds of PA congeners with widespread occurrence are known, and thousands of plants are assumed to contain PAs. Due to certain PAs' pronounced liver toxicity and carcinogenicity, their occurrence in food, feed, and phytomedicines has raised serious human health concerns. This is particularly true for herbal teas, certain food supplements, honey, and certain phytomedicinal drugs. Due to the limited availability of animal data, broader use of in vitro data appears warranted to improve the risk assessment of a large number of relevant, 1,2-unsaturated PAs. This is true, for example, for the derivation of both toxicokinetic and toxicodynamic data. These efforts aim to understand better the modes of action, uptake, metabolism, elimination, toxicity, and genotoxicity of PAs to enable a detailed dose-response analysis and ultimately quantify differing toxic potencies between relevant PAs. Accordingly, risk-limiting measures comprising production, marketing, and regulation of food, feed, and medicinal products are discussed.

Effect of chain length and branching on the in vitro metabolism of a series of parabens in human liver S9, human skin S9, and human plasma

Parabens are antimicrobial compounds used as preservatives in cosmetics, foods, and pharmaceuticals. Paraben exposure occurs through a variety of routes including dermal absorption, ingestion, and inhalation. Ester bond hydrolysis has been shown to be the predominant biotransformation for this chemical class. Here we evaluated a series of parabens of increasing alkyl chain length and branching in addition to the aryl side chain of phenyl paraben (PhP). We evaluated the parabens under full Michaelis-Menten (MM) parameters to obtain intrinsic clearance values and found different trends between human liver and skin, which correlate with the predominant esterase enzymes in those matrices, respectively. In liver, where carboxylesterase 1 (CES1) is the predominant esterase enzyme, the shorter chain parabens were more readily metabolized, while in skin, where carboxylesterase 2 (CES2) is the predominant esterase enzyme, the longer chain parabens were more readily metabolized. Alkyl chain branching reduced the hydrolysis rates relative to those for the straight chain compounds, while the addition of a phenyl group, as in PhP, showed an increase in hydrolysis, producing the highest observed hydrolysis rate for skin. These data summarize the structure-metabolism relationship for a series of parabens and contribute to the safety assessment of this class of compounds.

Intrinsic relative potency of a series of pyrrolizidine alkaloids characterized by rate and extent of metabolism

1,2-Unsaturated pyrrolizidine alkaloids (PAs) are sometimes present in foods or herbal supplements/medicines as impurities and pose potential concerns for liver genotoxicity/carcinogenicity. PAs display a strong structure toxicity relationship, however, current regulatory approaches to risk assessment take the precautionary approach of assuming all PAs display the same potency as the most toxic congeners lasiocarpine (LAS) and riddelliine (RID). Here we explore the relative potencies of a series of structurally diverse PAs by measuring DNA adduct formation in vitro in a rat sandwich culture hepatocyte (SCH) cell system. The adducts generated are consistent with those identified in vivo as biomarkers of PA exposure and potential liver-tumor formation. DNA reactive PAs require metabolic activation to form intermediates that bind DNA, therefore, adduct formation is a direct reflection of reactive metabolite formation. Since the area under the concentration versus time curve (AUC) for the depletion of parent PA from the extracellular media is a measure of PA exposure, the ratio of adducts/AUC provides a measure of hepatocyte exposure to DNA-binding metabolites corresponding to an intrinsic potency for DNA adduct formation. Intrinsic potencies relative to potencies for LAS compare well with existing relative potency data further affirming that PA toxicity varies considerably with chemical structure.

Next generation physiologically based kinetic (NG-PBK) models in support of regulatory decision making

The fields of toxicology and chemical risk assessment seek to reduce, and eventually replace, the use of animals for the prediction of toxicity in humans. In this context, physiologically based kinetic (PBK) modelling based on in vitro and in silico kinetic data has the potential to a play significant role in reducing animal testing, by providing a methodology capable of incorporating in vitro human data to facilitate the development of in vitro to in vivo extrapolation of hazard information. In the present article, we discuss the challenges in: 1) applying PBK modelling to support regulatory decision making under the toxicology and risk-assessment paradigm shift towards animal replacement; 2) constructing PBK models without in vivo animal kinetic data, while relying solely on in vitro or in silico methods for model parameterization; and 3) assessing the validity and credibility of PBK models built largely using non-animal data. The strengths, uncertainties, and limitations of PBK models developed using in vitro or in silico data are discussed in an effort to establish a higher degree of confidence in the application of such models in a regulatory context. The article summarises the outcome of an expert workshop hosted by the European Commission Joint Research Centre (EC-JRC) - European Union Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM), on "Physiologically-Based Kinetic modelling in risk assessment - reaching a whole new level in regulatory decision-making" held in Ispra, Italy, in November 2016, along with results from an international survey conducted in 2017 and recently reported activities occurring within the PBK modelling field. The discussions presented herein highlight the potential applications of next generation (NG)-PBK modelling, based on new data streams.

In vitro to in vivo extrapolation for high throughput prioritization and decision making

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.

Introduction of a methoxymethyl side chain into p-phenylenediamine attenuates its sensitizing potency and reduces the risk of allergy induction

The strong sensitizing potencies of the most important primary intermediates of oxidative hair dyes, p-phenylenediamine (PPD) and p-toluylenediamine (PTD, i.e. 2-methyl-PPD) are well established. They are considered as the key sensitizers in hair dye allergic contact dermatitis. While modification of their molecular structure is expected to alter their sensitizing properties, it may also impair their color performance. With introduction of a methoxymethyl side chain we found the primary intermediate 2-methoxymethyl-p-phenylenediamine (ME-PPD) with excellent hair coloring performance but significantly reduced sensitizing properties compared to PPD and PTD: In vitro, ME-PPD showed an attenuated innate immune response when analyzed for its protein reactivity and dendritic cell activation potential. In vivo, the effective concentration of ME-PPD necessary to induce an immune response 3-fold above vehicle control (EC3 value) in the local lymph node assay (LLNA) was 4.3%, indicating a moderate skin sensitizing potency compared to values of 0.1 and 0.17% for PPD and PTD, respectively. Finally, assessing the skin sensitizing potency of ME-PPD under consumer hair dye usage conditions through a quantitative risk assessment (QRA) indicated an allergy induction risk negligible compared to PPD or PTD.