In vitro to in vivo extrapolation to derive a metabolism factor for estimating the aggregate exposure to salicylic acid after dermal exposure of its esters.

As part of the safety assessment of salicylate esters in cosmetics, we developed a metabolism factor based on in vitro to in vivo extrapolation (IVIVE) to provide a better estimation of the aggregate internal exposure to the common metabolite, salicylic acid. Optimal incubation conditions using human liver S9 were identified before measuring salicylic acid formation from 31 substances. Four control substances, not defined as salicylic esters but which could be mistaken as such due to their nomenclature, did not form salicylic acid. For the remaining substances, higher in vitro intrinsic clearance (CLint, in vitro) values generally correlated with lower LogP values. A "High-Throughput Pharmacokinetic" (HTPK) model was used to extrapolate CLint, in vitro values to human in vivo clearance and half-lives. The latter were used to calculate the percentage of substance metabolised to salicylic acid in 24 h in vivo following human exposure to the ester, i.e. the "metabolism factor". The IVIVE model correctly reproduced the observed elimination rate of 3 substances using in silico or in vitro input parameters. For other substances, in silico only-based predictions generally resulted in lower metabolism factors than when in vitro values for plasma binding and liver S9 CLint, in vitro were used. Therefore, in vitro data input provides the more conservative metabolism factors compared to those derived using on in silico input. In conclusion, these results indicate that not all substances contribute equally (or at all) to the systemic exposure to salicylic acid. Therefore, we propose a realistic metabolism correction factor by which the potential contribution of salicylate esters to the aggregate consumer exposure to salicylic acid from cosmetic use can be estimated.

Report of the First ONTOX Stakeholder Network Meeting: Digging Under the Surface of ONTOX Together With the Stakeholders.

The first Stakeholder Network Meeting of the EU Horizon 2020-funded ONTOX project was held on 13-14 March 2023, in Brussels, Belgium. The discussion centred around identifying specific challenges, barriers and drivers in relation to the implementation of non-animal new approach methodologies (NAMs) and probabilistic risk assessment (PRA), in order to help address the issues and rank them according to their associated level of difficulty. ONTOX aims to advance the assessment of chemical risk to humans, without the use of animal testing, by developing non-animal NAMs and PRA in line with 21st century toxicity testing principles. Stakeholder groups (regulatory authorities, companies, academia, non-governmental organisations) were identified and invited to participate in a meeting and a survey, by which their current position in relation to the implementation of NAMs and PRA was ascertained, as well as specific challenges and drivers highlighted. The survey analysis revealed areas of agreement and disagreement among stakeholders on topics such as capacity building, sustainability, regulatory acceptance, validation of adverse outcome pathways, acceptance of artificial intelligence (AI) in risk assessment, and guaranteeing consumer safety. The stakeholder network meeting resulted in the identification of barriers, drivers and specific challenges that need to be addressed. Breakout groups discussed topics such as hazard versus risk assessment, future reliance on AI and machine learning, regulatory requirements for industry and sustainability of the ONTOX Hub platform. The outputs from these discussions provided insights for overcoming barriers and leveraging drivers for implementing NAMs and PRA. It was concluded that there is a continued need for stakeholder engagement, including the organisation of a 'hackathon' to tackle challenges, to ensure the successful implementation of NAMs and PRA in chemical risk assessment.

Practical application of the interim internal threshold of toxicological concern (iTTC): a case study based on clinical data.

We present a case study that provides a practical step-by-step example of how the internal Threshold of Toxicological Concern (iTTC) can be used as a tool to refine a TTC-based assessment for dermal exposures to consumer products. The case study uses a theoretical scenario where there are no systemic toxicity data for the case study chemicals (avobenzone, oxybenzone, octocrylene, homosalate, octisalate, octinoxate, and ecamsule). Human dermal pharmacokinetic data following single and repeat dermal exposure to products containing the case study chemicals were obtained from data published by the US FDA. The clinical studies utilized an application procedure that followed maximal use conditions (product applied as 2 mg/cm2 to 75% of the body surface area, 4 times a day). The case study chemicals were first reviewed to determine if they were in the applicability domain of the iTTC, and then, the human plasma concentrations were compared to an iTTC limit of 1 µM. When assessed under maximum usage, the external exposure of all chemicals exceeded the external dose TTC limits. By contrast, the internal exposure to all chemicals, except oxybenzone, was an order of magnitude lower than the 1 µM interim iTTC threshold. This work highlights the importance of understanding internal exposure relative to external dose and how the iTTC can be a valuable tool for assessing low-level internal exposures; additionally, the work demonstrates how to use an iTTC, and highlights considerations and refinement opportunities for the approach.

Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment.

With an increasing need to incorporate new approach methodologies (NAMs) in chemical risk assessment and the concomitant need to phase out animal testing, the interpretation of in vitro assay readouts for quantitative hazard characterisation becomes more important. Physiologically based kinetic (PBK) models, which simulate the fate of chemicals in tissues of the body, play an essential role in extrapolating in vitro effect concentrations to in vivo bioequivalent exposures. As PBK-based testing approaches evolve, it will become essential to standardise PBK modelling approaches towards a consensus approach that can be used in quantitative in vitro-to-in vivo extrapolation (QIVIVE) studies for regulatory chemical risk assessment based on in vitro assays. Based on results of an ECETOC expert workshop, steps are recommended that can improve regulatory adoption: (1) define context and implementation, taking into consideration model complexity for building fit-for-purpose PBK models, (2) harmonise physiological input parameters and their distribution and define criteria for quality chemical-specific parameters, especially in the absence of in vivo data, (3) apply Good Modelling Practices (GMP) to achieve transparency and design a stepwise approach for PBK model development for risk assessors, (4) evaluate model predictions using alternatives to in vivo PK data including read-across approaches, (5) use case studies to facilitate discussions between modellers and regulators of chemical risk assessment. Proof-of-concepts of generic PBK modelling approaches are published in the scientific literature at an increasing rate. Working on the previously proposed steps is, therefore, needed to gain confidence in PBK modelling approaches for regulatory use.

Identification of PKMYT1 inhibitors by screening the GSK published protein kinase inhibitor set I and II.

As a member of the Wee-kinase family protein kinase PKMYT1 is involved in G2/M checkpoint regulation of the cell cycle. Recently, a peptide microarray approach led to the identification of a small peptide; EFS247-259 as substrate of PKMYT1, which allowed for subsequent development of an activity assay. The developed activity assay was used to characterize the PKMYT1 catalyzed phosphorylation of EFS247-259. For the first time kinetic parameters for PKMYT1, namely Km, Km, ATP and vmax were determined. The optimized assay was used to screen the published protein kinase inhibitor sets (PKIS I and II), two sets of small molecule ATP-competitive kinase inhibitors reported by GlaxoSmithKline. We identified ten inhibitors, providing different scaffolds. The inhibitors were further characterized by using binding assay, activity and functional assay. In addition, docking studies were carried out in order to rationalize the observed biological activities. The derived results provide the basis for further chemical optimization of PKMYT1 inhibitors and for further analysis of PKMYT1 as target for anti-cancer therapy.

Discovery of novel dual inhibitors of receptor tyrosine kinases EGFR and PDGFR-ß related to anticancer drug resistance.

With ongoing resistance problems against the marketed EGFR inhibitors having a quinazoline core scaffold there is a need for the development of novel inhibitors having a modified scaffold and, thus, expected lower EGFR resistance problems. An additional problem concerning EGFR inhibitor resistance is an observed heterodimerization of EGFR with PDGFR-ß that neutralises the sole inhibitor activity towards EGFR. We developed novel pyrimido[4,5-b]indoles with varied substitution patterns at the 4-anilino residue to evaluate their EGFR and PDGFR-ß inhibiting properties. We identified dual inhibitors of both EGFR and PDGFR-ß in the nanomolar range which have been initially screened in cancer cell lines to prove a benefit of both EGFR and PDGFR-ß inhibition.

Discovery of novel substituted benzo-anellated 4-benzylamino pyrrolopyrimidines as dual EGFR and VEGFR2 inhibitors.

The quinazoline scaffold is the main part of many marketed EGFR inhibitors. Resistance developments against those inhibitors enforced the search for novel structural lead compounds. We developed novel benzo-anellated 4-benzylamine pyrrolopyrimidines with varied substitution patterns at both the molecular scaffold and the attached residue in the 4-position. The structure-dependent affinities towards EGFR are discussed and first nanomolar derivatives have been identified. Docking studies were carried out for EGFR in order to explore the potential binding mode of the novel inhibitors. As the receptor tyrosine kinase VEGFR2 recently gained an increasing interest as an upregulated signaling kinase in many solid tumors and in tumor metastasis we determined the affinity of our compounds to inhibit VEGFR2. So we identified novel dually acting EGFR and VEGFR2 inhibitors for which first anticancer screening data are reported. Those data indicate a stronger antiproliferative effect of a VEGFR2 inhibition compared to the EGFR inhibition.

Discovery of novel dual inhibitors of receptor tyrosine kinases EGFR and IGF-1R.

Novel 4-benzylamino benzo-anellated pyrrolo[2,3-b]pyridines have been synthesized with varied substitution patterns both at the molecular scaffold of the benzo-anellated ring and at the 4-benzylamino residue. With a structural similarity to substituted thieno[2,3-d]pyrimidines as epidermal growth factor receptor (EGFR) inhibitors, we characterized the inhibition of EGFR for our novel compounds. As receptor heterodimerization gained certain interest as mechanism of cancer cells to become resistant against novel protein kinase inhibitors, we additionally measured the inhibition of insulin-like growth factor receptor IGF-1R which is a prominent receptor for such heterodimerizations with EGFR. Structure-activity relationships are discussed for both kinase inhibitions depending on the varied substitution patterns. We discovered novel dual inhibitors of both receptor tyrosine kinases with interest for further studies to reduce inhibitor resistance developments in cancer treatment.

Regulation of G2/M Transition by Inhibition of WEE1 and PKMYT1 Kinases.

In the cell cycle, there are two checkpoint arrests that allow cells to repair damaged DNA in order to maintain genomic integrity. Many cancer cells have defective G1 checkpoint mechanisms, thus depending on the G2 checkpoint far more than normal cells. G2 checkpoint abrogation is therefore a promising concept to preferably damage cancerous cells over normal cells. The main factor influencing the decision to enter mitosis is a complex composed of Cdk1 and cyclin B. Cdk1/CycB is regulated by various feedback mechanisms, in particular inhibitory phosphorylations at Thr14 and Tyr15 of Cdk1. In fact, Cdk1/CycB activity is restricted by the balance between WEE family kinases and Cdc25 phosphatases. The WEE kinase family consists of three proteins: WEE1, PKMYT1, and the less important WEE1B. WEE1 exclusively mediates phosphorylation at Tyr15, whereas PKMYT1 is dual-specific for Tyr15 as well as Thr14. Inhibition by a small molecule inhibitor is therefore proposed to be a promising option since WEE kinases bind Cdk1, altering equilibria and thus affecting G2/M transition.

Next generation risk assessment: an ab initio case study to assess the systemic safety of the cosmetic ingredient, benzyl salicylate, after dermal exposure.

We performed an ab initio next-generation risk assessment (NGRA) for a fragrance ingredient, benzyl salicylate (BSal), to demonstrate how cosmetic ingredients can be evaluated for systemic toxicity endpoints based on non-animal approaches. New approach methodologies (NAMs) used to predict the internal exposure included skin absorption assays, hepatocyte metabolism, and physiologically based pharmacokinetic (PBPK) modeling, and potential toxicodynamic effects were assessed using pharmacology profiling, ToxProfiler cell stress assay, transcriptomics in HepG2 and MCF-7 cells, ReproTracker developmental and reproductive toxicology (DART) assays, and cytotoxicity assays in human kidney cells. The outcome of the NGRA was compared to that of the traditional risk assessment approach based on animal data. The identification of the toxicologically critical entity was a critical step that directed the workflow and the selection of chemicals for PBPK modeling and testing in bioassays. The traditional risk assessment and NGRA identified salicylic acid (SA) as the "toxdriver." A deterministic PBPK model for a single-day application of 1.54 g face cream containing 0.5% BSal estimated the Cmax for BSal (1 nM) to be much lower than that of its major in vitro metabolite, SA (93.2 nM). Therefore, SA was tested using toxicodynamics bioassays. The lowest points of departure (PoDs) were obtained from the toxicogenomics assays. The interpretation of these results by two companies and methods were similar (SA only results in significant gene deregulation in HepG2 cells), but PoD differed (213 µM and 10.6 µM). A probabilistic PBPK model for repeated applications of the face cream estimated the highest Cmax of SA to be 630 nM. The resulting margins of internal exposure (MoIE) using the PoDs were 338 and 16, which were more conservative than those derived from external exposure and in vivo PoDs (margin of safety values were 9,705). In conclusion, both traditional and ab initio NGRA approaches concluded that the daily application of BSal in a cosmetic leave-on face cream at 0.5% is safe for humans. The processing and interpretation of toxicogenomics data can lead to different PoDs, which can subsequently affect the calculation of the MoIE. This case study supports the use of NAMs in a tiered NGRA ab initio approach.

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.

Prediction of in vivo prenatal chlorpyrifos exposure leading to developmental neurotoxicity in humans based on in vitro toxicity data by quantitative in vitro-in vivo extrapolation.

Introduction: Epidemiological studies in children suggested that in utero exposure to chlorpyrifos (CPF), an organophosphate insecticide, may cause developmental neurotoxicity (DNT). We applied quantitative in vitro-in vivo extrapolation (QIVIVE) based on in vitro concentration and non-choline esterase-dependent effects data combined with Benchmark dose (BMD) modelling to predict oral maternal CPF exposure during pregnancy leading to fetal brain effect concentration. By comparing the results with data from epidemiological studies, we evaluated the contribution of the in vitro endpoints to the mode of action (MoA) for CPF-induced DNT. Methods: A maternal-fetal PBK model built in PK-Sim® was used to perform QIVIVE predicting CPF concentrations in a pregnant women population at 15 weeks of gestation from cell lysate concentrations obtained in human induced pluripotent stem cell-derived neural stem cells undergoing differentiation towards neurons and glia exposed to CPF for 14 days. The in vitro concentration and effect data were used to perform BMD modelling. Results: The upper BMD was converted into maternal doses which ranged from 3.21 to 271 mg/kg bw/day. Maternal CPF blood levels from epidemiological studies reporting DNT findings in their children were used to estimate oral CPF exposure during pregnancy using the PBK model. It ranged from 0.11 to 140 µg/kg bw/day. Discussion: The effective daily intake doses predicted from the in vitro model were several orders of magnitude higher than exposures estimated from epidemiological studies to induce developmental non-cholinergic neurotoxic responses, which were captured by the analyzed in vitro test battery. These were also higher than the in vivo LOEC for cholinergic effects. Therefore, the quantitative predictive value of the investigated non-choline esterase-dependent effects, although possibly relevant for other chemicals, may not adequately represent potential key events in the MoA for CPF-associated DNT.

Development of a microphysiological skin-liver-thyroid Chip3 model and its application to evaluate the effects on thyroid hormones of topically applied cosmetic ingredients under consumer-relevant conditions.

All cosmetic ingredients registered in Europe must be evaluated for their safety using non-animal methods. Microphysiological systems (MPS) offer a more complex higher tier model to evaluate chemicals. Having established a skin and liver HUMIMIC Chip2 model demonstrating how dosing scenarios impact the kinetics of chemicals, we investigated whether thyroid follicles could be incorporated to evaluate the potential of topically applied chemicals to cause endocrine disruption. This combination of models in the HUMIMIC Chip3 is new; therefore, we describe here how it was optimized using two chemicals known to inhibit thyroid production, daidzein and genistein. The MPS was comprised of Phenion® Full Thickness skin, liver spheroids and thyroid follicles co-cultured in the TissUse HUMIMIC Chip3. Endocrine disruption effects were determined according to changes in thyroid hormones, thyroxine (T4) and 3,3',5-triiodothyronine (T3). A main part of the Chip3 model optimization was the replacement of freshly isolated thyroid follicles with thyrocyte-derived follicles. These were used in static incubations to demonstrate the inhibition of T4 and T3 production by genistein and daidzein over 4 days. Daidzein exhibited a lower inhibitory activity than genistein and both inhibitory activities were decreased after a 24 h preincubation with liver spheroids, indicating metabolism was via detoxification pathways. The skin-liver-thyroid Chip3 model was used to determine a consumer-relevant exposure to daidzein present in a body lotion based on thyroid effects. A "safe dose" of 0.235 µg/cm2 i.e., 0.047% applied in 0.5 mg/cm2 of body lotion was the highest concentration of daidzein which does not result in changes in T3 and T4 levels. This concentration correlated well with the value considered safe by regulators. In conclusion, the Chip3 model enabled the incorporation of the relevant exposure route (dermal), metabolism in the skin and liver, and the bioactivity endpoint (assessment of hormonal balance i.e., thyroid effects) into a single model. These conditions are closer to those in vivo than 2D cell/tissue assays lacking metabolic function. Importantly, it also allowed the assessment of repeated doses of chemical and a direct comparison of systemic and tissue concentrations with toxicodynamic effects over time, which is more realistic and relevant for safety assessment.

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 Physiologically-Based Kinetics Modelling to Reliably Predict Internal Concentrations of the UV Filter, Homosalate, After Repeated Oral and Topical Application.

Ethical and legal considerations have led to increased use of non-animal methods to evaluate the safety of chemicals for human use. We describe the development and qualification of a physiologically-based kinetics (PBK) model for the cosmetic UV filter ingredient, homosalate, to support its safety without the need of generating further animal data. The intravenous (IV) rat PBK model, using PK-Sim®, was developed and validated using legacy in vivo data generated prior to the 2013 EU animal-testing ban. Input data included literature or predicted physicochemical and pharmacokinetic properties. The refined IV rat PBK model was subject to sensitivity analysis to identify homosalate-specific sensitive parameters impacting the prediction of Cmax (more sensitive than AUC(0-∞)). These were then considered, together with population modeling, to calculate the confidence interval (CI) 95% Cmax and AUC(0-∞). Final model parameters were established by visual inspection of the simulations and biological plausibility. The IV rat model was extrapolated to oral administration, and used to estimate internal exposures to doses tested in an oral repeated dose toxicity study. Next, a human PBK dermal model was developed using measured human in vitro ADME data and a module to represent the dermal route. Model performance was confirmed by comparing predicted and measured values from a US-FDA clinical trial (Identifier: NCT03582215, https://clinicaltrials.gov/). Final exposure estimations were obtained in a virtual population and considering the in vitro and input parameter uncertainty. This model was then used to estimate the Cmax and AUC(0-24 h) of homosalate according to consumer use in a sunscreen. The developed rat and human PBK models had a good biological basis and reproduced in vivo legacy rat and human clinical kinetics data. They also complied with the most recent WHO and OECD recommendations for assessing the confidence level. In conclusion, we have developed a PBK model which predicted reasonably well the internal exposure of homosalate according to different exposure scenarios with a medium to high level of confidence. In the absence of in vivo data, such human PBK models will be the heart of future completely non-animal risk assessments; therefore, valid approaches will be key in gaining their regulatory acceptance. Clinical Trial Registration: https://clinicaltrials.gov/, identifier, NCT03582215.

Computer-aided design, synthesis and biological characterization of novel inhibitors for PKMYT1.

In the current work, we applied computational methods to analyze the membrane-associated inhibitory kinase PKMYT1 and small molecule inhibitors. PKMYT1 regulates the cell cycle at G2/M transition and phosphorylates Thr14 and Tyr15 in the Cdk1-cyclin B complex. A combination of in silico and in vitro screening was applied to identify novel PKMYT1 inhibitors. The computational approach combined structural analysis, molecular docking, binding free energy calculations, and quantitative structure-activity relationship (QSAR) models. In addition, a computational fragment growing approach was applied to a set of previously identified diaminopyrimidines. Based on the derived computational models, several derivatives were synthesized and tested in vitro on PKMYT1. Novel inhibitors active in the sub-micromolar range were identified which provide the basis for further characterization of PKMYT1 as putative target for cancer therapy.