Mechanisms of Nitrosamine Mutagenicity and Their Relationship to Rodent Carcinogenic Potency

A thorough literature review was undertaken to understand how the pathways of N-nitrosamine transformation relate to mutagenic potential and carcinogenic potency in rodents. Empirical and computational evidence indicates that a common radical intermediate is created by CYP-mediated hydrogen abstraction at the α-carbon; it is responsible for both activation, leading to the formation of DNA-reactive diazonium species, and deactivation by denitrosation. There are competing sites of CYP metabolism (e.g., β-carbon), and other reactive species can form following initial bioactivation, although these alternative pathways tend to decrease rather than enhance carcinogenic potency. The activation pathway, oxidative dealkylation, is a common reaction in drug metabolism and evidence indicates that the carbonyl byproduct, e.g., formaldehyde, does not contribute to the toxic properties of N-nitrosamines. Nitric oxide (NO), a side product of denitrosation, can similarly be discounted as an enhancer of N-nitrosamine toxicity based on carcinogenicity data for substances that act as NO-donors. However, not all N-nitrosamines are potent rodent carcinogens. In a significant number of cases, there is a potency overlap with non-N-nitrosamine carcinogens that are not in the Cohort of Concern (CoC; high-potency rodent carcinogens comprising aflatoxin-like-, N-nitroso-, and alkyl-azoxy compounds), while other N-nitrosamines are devoid of carcinogenic potential. In this context, mutagenicity is a useful surrogate for carcinogenicity, as proposed in the ICH M7 (R2) (2023) guidance. Thus, in the safety assessment and control of N-nitrosamines in medicines, it is important to understand those complementary attributes of mechanisms of mutagenicity and structure-activity relationships that translate to elevated potency versus those which are associated with a reduction in, or absence of, carcinogenic potency.

Nitrosamine acceptable intakes should consider variation in molecular weight: The implication of stoichiometric DNA damage

N-nitrosamines (NAs) are a class of compounds of which many, especially of the small dialkyl type, are indirect acting DNA alkylating mutagens. Their presence in pharmaceuticals is subject to very strict acceptable daily intake (AI) limits, which are traditionally expressed on a mass basis. Here we demonstrate that AIs that are not experimentally derived for a specific compound, but via statistical extrapolation or read across to a suitable analog, should be expressed on a molar scale or corrected for the target substance's molecular weight. This would account for the mechanistic aspect that each nitroso group can, at maximum, account for a single DNA mutation and the number of molecules per mass unit is proportional to the molecular weight (MW). In this regard we have re-calculated the EMA 18 ng/day regulatory default AI for unknown nitrosamines on a molar scale and propose a revised default AI of 163 pmol/day. In addition, we provide MW-corrected AIs for those nitrosamine drug substance related impurities (NDSRIs) for which EMA has pre-assigned AIs by read-across. Regulatory acceptance of this fundamental scientific tenet would allow one to derive nitrosamine limits for NDSRIs that both meet the health-protection goals and are technically feasible.

Revisiting the Landscape of Potential Small and Drug Substance Related Nitrosamines in Pharmaceuticals

N-Nitrosamines are a class of indirect acting mutagens, as their metabolic degradation leads to the formation of the DNA-alkylating diazonium ion. Following up on the in-silico identification of thousands of nitrosamines that can potentially be derived from small molecule drugs and their known impurities described in a previous publication, we have now re-analyzed this dataset to apply EMA's Carcinogenic Potency Categorization Approach (CPCA) introduced with the 16th revision of their Q&A document for Marketing Authorization Holders. We find that the majority of potential nitrosamines from secondary amine precursors belongs to potency categories 4 and 5, corresponding to an acceptable daily intake of 1500 ng, whereas nitrosamines from tertiary amine precursors distribute more evenly among all categories, resulting in a substantial number of structures that are assigned the more challenging acceptable intakes of 18 ng/day and 100 ng/day for potency categories 1 and 2, respectively. However, the nitrosative dealkylation pathway for tertiary amine is generally far slower than the direct nitrosation on secondary amines, with a direct nitrosation mechanism suspected only for structures featuring electron-rich (hetero)aromatic substituents. This allows for greater focus towards those structures that require further review, and we demonstrate that their number is not substantial. In addition, we reflect on the nitrosamine risk posed by secondary amine API impurities and demonstrate that based on the ICH Q3A/B identification threshold unknown impurities may exist that could be transformed to relevant amounts of NA. We also demonstrate that the analytical sensitivity required for the quantification of high potency nitrosamines can be problematic especially for high dose APIs. In summary, the regulatory framework rolled out with the latest Q&A document represents a substantial improvement compared with the previous situation, but further refinement through interaction between manufacturers, regulators, not-for-profit and academic institutions will be required to ensure patient access to vital medicines without compromising safety.

Use of the TD50 99 % CI for single dose rodent carcinogenicity studies

The Tumorigenic dose 50 (TD50) is a widely used measure of carcinogenic potency representing the dosage at which 50 % of animals exposed to a compound will develop tumours. The popularity of the TD50 is in part due to the large amount of publicly available data. TD50s were calculated for a large number of compounds in the Carcinogenic Potency Database, which has since been extended in the freely available Lhasa Carcinogenicity database, containing TD50s from over 7500 studies and 1700 compounds. However, due to the age of these studies many are of low quality, often comprising only a single test dosage, therefore raising questions about the applicability of such TD50 sfor toxicological risk assessment. We investigate whether the lower 99 % confidence interval is sufficient to produce conservative TD50 estimates for these studies.

Maximizing use of existing carcinogenicity data to support acceptable intake levels for mutagenic impurities in pharmaceuticals: Learnings from N-nitrosamine case studies

The unexpected finding of N-nitrosamine (NA) impurities in many pharmaceutical products raised significant challenges for industry and regulators. In addition to well-studied small molecular weight NAs, many of which are potent rodent carcinogens, novel NAs associated with active pharmaceutical ingredients have been found, many of which have limited or no safety data. A tiered approach to establishing Acceptable Intake (AI) limits for NA impurities has been established using chemical-specific data, read-across, or a class-specific TTC limit. There are ∼140 NAs with some rodent carcinogenicity data, but much of it is older and does not meet current guidelines for what constitutes a 'robust' bioassay. Nevertheless, these data are an important source of information to ensure the best science is used for assessing NA impurities and assuring consumer safety while minimizing impact that can lead to drug shortages. We present several strategies to maximize the use of imperfect data including using a lower confidence limit on a rodent TD50, and leveraging data from multiple NAs. Information on the chemical structure known to impact potency can also support development of an AI or potentially conclude that a particular NA does not fall in the cohort of concern for potent carcinogenicity.

A deep dive into historical Ames study data for N-nitrosamine compounds

Mutagenicity data is a core component of the safety assessment data required by regulatory agencies for acceptance of new drug compounds, with the OECD-471 bacterial reverse mutation (Ames) assay most widely used as a primary screen to assess drug impurities for potential mutagenic risk. N-Nitrosamines are highly potent mutagenic carcinogens in rodent bioassays and their recent detection as impurities in pharmaceutical products has sparked increased interest in their safety assessment. Previous literature reports indicated that the Ames test might not be sensitive enough to detect the mutagenic potential of N-nitrosamines in order to accurately predict a risk of carcinogenicity. To explore this hypothesis, public Ames and rodent carcinogenicity data pertaining to the N-nitrosamine class of compounds was collated for analysis. Here we present how variations to the OECD 471-compliant Ames test, including strain, metabolic activation, solvent type and pre-incubation/plate incorporation methods, may impact the predictive performance for carcinogenicity. An understanding of optimal conditions for testing of N-nitrosamines may improve both the accuracy and confidence in the ability of the Ames test to identify potential carcinogens.

Acceptable Intakes (AIs) for 11 Small molecule N-nitrosamines (NAs)

Low levels of N-nitrosamines (NAs) were detected in pharmaceuticals and, as a result, health authorities (HAs) have published acceptable intakes (AIs) in pharmaceuticals to limit potential carcinogenic risk. The rationales behind the AIs have not been provided to understand the process for selecting a TD₅₀ or read-across analog. In this manuscript we evaluated the toxicity data for eleven common NAs in a comprehensive and transparent process consistent with ICH M7. This evaluation included substances which had datasets that were robust, limited but sufficient, and substances with insufficient experimental animal carcinogenicity data. In the case of robust or limited but sufficient carcinogenicity information, AIs were calculated based on published or derived TD₅₀s from the most sensitive organ site. In the case of insufficient carcinogenicity information, available carcinogenicity data and structure activity relationships (SARs) were applied to categorical-based AIs of 1500 ng/day, 150 ng/day or 18 ng/day; however additional data (such as biological or additional computational modelling) could inform an alternative AI. This approach advances the methodology used to derive AIs for NAs.

Predicting Regioselectivity of Cytosolic Sulfotransferase Metabolism for Drugs

Cytosolic sulfotransferases (SULTs) are a family of enzymes responsible for the sulfation of small endogenous and exogenous compounds. SULTs contribute to the conjugation phase of metabolism and share substrates with the uridine 5'-diphospho-glucuronosyltransferase (UGT) family of enzymes. UGTs are considered to be the most important enzymes in the conjugation phase, and SULTs are an auxiliary enzyme system to them. Understanding how the regioselectivity of SULTs differs from that of UGTs is essential from the perspective of developing novel drug candidates. We present a general ligand-based SULT model trained and tested using high-quality experimental regioselectivity data. The current study suggests that, unlike other metabolic enzymes in the modification and conjugation phases, the SULT regioselectivity is not strongly influenced by the activation energy of the rate-limiting step of the catalysis. Instead, the prominent role is played by the substrate binding site of SULT. Thus, the model is trained only on steric and orientation descriptors, which mimic the binding pocket of SULT. The resulting classification model, which predicts whether a site is metabolized, achieved a Cohen's kappa of 0.71.

Nature-Derived Epoxy Resin Monomers with Reduced Sensitizing Capacity─Isosorbide-Based Bis-Epoxides

Epoxy resin systems (ERSs) are a class of thermosetting resins that become thermostable and insoluble polymers upon curing. They are widely used as components of protective surfaces, adhesives, and paints and in the manufacturing of composites in the plastics industry. The diglycidyl ether of bisphenol A (DGEBA) is used in 75-90% of ERSs and is thus by far the most used epoxy resin monomer (ERM). Unfortunately, DGEBA is a strong skin sensitizer and it is one of the most common causes of occupational contact dermatitis. Furthermore, DGEBA is synthesized from bisphenol A (BPA), which is a petroleum-derived chemical with endocrine-disruptive properties. In this work, we have used isosorbide, a renewable and nontoxic sugar-based material, as an alternative to BPA in the design of ERMs. Three different bis-epoxide isosorbide derivatives were synthesized: the diglycidyl ether of isosorbide (1) and two novel isosorbide-based bis-epoxides containing either a benzoic ester (2) or a benzyl ether linkage (3). Assessment of the in vivo sensitizing potency of the isosorbide bis-epoxides in the murine local lymph node assay (LLNA) showed that all three compounds were significantly less sensitizing than DGEBA, especially 2 which was nonsensitizing up to 25% w/v. The peptide reactivity showed the same order of reactivity as the LLNA, i.e., 2 being the least reactive, followed by 3 and then 1, which displayed similar peptide reactivity as DGEBA. Skin permeation of 2 and 3 was compared to DGEBA using ex vivo pig skin and static Franz cells. The preliminary investigations of the technical properties of the polymers formed from 1-3 were promising. Although further investigations of the technical properties are needed, all isosorbide bis-epoxides have the potential to be less sensitizing renewable replacements of DGEBA, especially 2 that had the lowest sensitizing potency in vivo as well as the lowest peptide reactivity.

Strategies for Assessing Acceptable Intakes for Novel N-Nitrosamines Derived from Active Pharmaceutical Ingredients

The detection of N-nitrosamines, derived from solvents and reagents and, on occasion, the active pharmaceutical ingredient (API) at higher than acceptable levels in drug products, has led regulators to request a detailed review for their presence in all medicinal products. In the absence of rodent carcinogenicity data for novel N-nitrosamines derived from amine-containing APIs, a conservative class limit of 18 ng/day (based on the most carcinogenic N-nitrosamines) or the derivation of acceptable intakes (AIs) using structurally related surrogates with robust rodent carcinogenicity data is recommended. The guidance has implications for the pharmaceutical industry given the vast number of marketed amine-containing drugs. In this perspective, the rate-limiting step in N-nitrosamine carcinogenicity, involving cytochrome P450-mediated α-carbon hydroxylation to yield DNA-reactive diazonium or carbonium ion intermediates, is discussed with reference to the selection of read-across analogs to derive AIs. Risk-mitigation strategies for managing putative N-nitrosamines in the preclinical discovery setting are also presented.

What Makes a Potent Nitrosamine? Statistical Validation of Expert-Derived Structure-Activity Relationships

The discovery of carcinogenic nitrosamine impurities above the safe limits in pharmaceuticals has led to an urgent need to develop methods for extending structure-activity relationship (SAR) analyses from relatively limited datasets, while the level of confidence required in that SAR indicates that there is significant value in investigating the effect of individual substructural features in a statistically robust manner. This is a challenging exercise to perform on a small dataset, since in practice, compounds contain a mixture of different features, which may confound both expert SAR and statistical quantitative structure-activity relationship (QSAR) methods. Isolating the effects of a single structural feature is made difficult due to the confounding effects of other functionality as well as issues relating to determining statistical significance in cases of concurrent statistical tests of a large number of potential variables with a small dataset; a naïve QSAR model does not predict any features to be significant after correction for multiple testing. We propose a variation on Bayesian multiple linear regression to estimate the effects of each feature simultaneously yet independently, taking into account the combinations of features present in the dataset and reducing the impact of multiple testing, showing that some features have a statistically significant impact. This method can be used to provide statistically robust validation of expert SAR approaches to the differences in potency between different structural groupings of nitrosamines. Structural features that lead to the highest and lowest carcinogenic potency can be isolated using this method, and novel nitrosamine compounds can be assigned into potency categories with high accuracy.

The Landscape of Potential Small and Drug Substance Related Nitrosamines in Pharmaceuticals

This article reports the outcome of an in silico analysis of more than 12,000 small molecule drugs and drug impurities, identifying the nitrosatable structures, assessing their potential to form nitrosamines under relevant conditions and the challenges to determine compound-specific AIs based on data available or read-across approaches for these nitrosamines and their acceptance by health authorities. Our data indicate that the presence of nitrosamines in pharmaceuticals is likely more prevalent than originally expected. In total, 40.4 % of the analyzed APIs and 29.6 % of the API impurities are potential nitrosamine precursors. Most structures identified through our workflow could form complex API-related nitrosamines, so-called nitrosamine drug substance related impurities (NDSRIs), although we also found structures that could release the well-known small and potent nitrosamines NDMA, NDEA, and others. Due to common structural motifs including secondary or tertiary amine moieties, whole essential drug classes such as beta blockers and ACE inhibitors are at risk. To avoid the risk of drug shortages or even the complete loss of therapeutic options, it will be essential that the well-established ICH M7 principles remain applicable for nitrosamines and that that the industry and regulatory authorities keep an open communication not only about the science but also to make sure there is a good balance between risk and benefit to patients.

Predicting Regioselectivity of AO, CYP, FMO, and UGT Metabolism Using Quantum Mechanical Simulations and Machine Learning

Unexpected metabolism in modification and conjugation phases can lead to the failure of many late-stage drug candidates or even withdrawal of approved drugs. Thus, it is critical to predict the sites of metabolism (SoM) for enzymes, which interact with drug-like molecules, in the early stages of the research. This study presents methods for predicting the isoform-specific metabolism for human AOs, FMOs, and UGTs and general CYP metabolism for preclinical species. The models use semi-empirical quantum mechanical simulations, validated using experimentally obtained data and DFT calculations, to estimate the reactivity of each SoM in the context of the whole molecule. Ligand-based models, trained and tested using high-quality regioselectivity data, combine the reactivity of the potential SoM with the orientation and steric effects of the binding pockets of the different enzyme isoforms. The resulting models achieve κ values of up to 0.94 and AUC of up to 0.92.

Updating the Dermal Sensitisation Thresholds using an expanded dataset and an in silico expert system

The Dermal Sensitisation Thresholds (DST) are Thresholds of Toxicological Concern, which can be used to justify exposure-based waiving when conducting a skin sensitisation risk assessment. This study aimed to update the published DST values by expanding the size of the Local Lymph Node Assay dataset upon which they are based, whilst assigning chemical reactivity using an in silico expert system (Derek Nexus). The potency values within the expanded dataset fitted a similar gamma distribution to that observed for the original dataset. Derek Nexus was used to classify the sensitisation activity of the 1152 chemicals in the expanded dataset and to predict which chemicals belonged to a High Potency Category (HPC). This two-step classification led to three updated thresholds: a non-reactive DST of 710 μg/cm² (based on 79 sensitisers), a reactive (non-HPC) DST of 73 μg/cm² (based on 331 sensitisers) and an HPC DST of 1.0 μg/cm² (based on 146 sensitisers). Despite the dataset containing twice as many sensitisers, these values are similar to the previously published thresholds, highlighting their robustness and increasing confidence in their use. By classifying reactivity in silico the updated DSTs can be applied within a skin sensitisation risk assessment in a reproducible, scalable and accessible manner.

Nature-derived epoxy resins: Synthesis, allergenicity, and thermosetting properties of pinoresinol diglycidyl ether

We describe a novel nature-derived epoxy resin monomer (ERM) derived from the plant lignan pinoresinol. Epoxy resins are thermosetting materials in global usage owing to their excellent technical properties such as flexibility and durability. However, their adverse health effects are often not considered and affect users of epoxy resins worldwide. Components of epoxy resin systems are strong skin sensitizers and cause allergic contact dermatitis. The reported prevalence attributable to epoxy chemicals is between 11.7 and 12.5% of all cases of occupational allergic contact dermatitis. We are committed to developing epoxy resins with reduced allergenic effect, while maintaining their excellent properties. The novel ERM, pinoresinol diglycidyl ether (PinoDGE), was synthesized in one step from pinoresinol and epichlorohydrin in 88% yield. It was not classified as a skin sensitizer in the in vivo local lymph node assay, at concentrations up to 0.17 m, as it did not cause a stimulation index >3 compared to control. Pinoresinol diglycidyl ether reacted with the model peptide AcPHCKRM in a reactivity assay and was predicted to be a skin sensitizer in the KeratinoSens assay. Preliminary cross-linking studies indicate that it has promising properties compared to commercially used ERMs. Pinoresinol diglycidyl ether could be seen as a lead compound for further development of alternative ERMs with a better safety profile based on natural and renewable sources for construction of epoxy resin polymers.

Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity

Lhasa Limited have had a role in the in silico prediction of drug and other chemical toxicity for over 30 years. This role has always been multifaceted, both as a provider of predictive software such as Derek Nexus, and as an honest broker for the sharing of proprietary chemical and toxicity data. A changing regulatory environment and the drive for the Replacement, Reduction and Refinement (the 3Rs) of animal testing have led both to increased acceptance of in silico predictions and a desire for the sharing of data to reduce duplicate testing. The combination of these factors has led to Lhasa Limited providing a suite of products and coordinating numerous data-sharing consortia that do indeed facilitate a significant reduction in the testing burden that companies would otherwise be laboring under. Many of these products and consortia can be organized into workflows for specific regulatory use cases, and it is these that will be used to frame the narrative in this chapter.

Use of less-than-lifetime (LTL) durational limits for nitrosamines: Case study of N-Nitrosodiethylamine (NDEA)

The ICH M7(R1) guideline describes a framework to assess the carcinogenic risk of mutagenic and carcinogenic pharmaceutical impurities following less-than-lifetime (LTL) exposures. This LTL framework is important as many pharmaceuticals are not administered for a patient's lifetime and as clinical trials typically involve LTL exposures. While there has been regulatory caution about applying LTL concepts to cohort of concern (COC) impurities such as N-nitrosamines, ICH M7 does not preclude this and indeed literature data suggests that the LTL framework will be protective of patient safety for N-nitrosamines. The goal was to investigate if applying the LTL framework in ICH M7 would control exposure to an acceptable excess cancer risk in humans. Using N-nitrosodiethylamine as a case study, empirical data correlating exposure duration (as a percentage of lifespan) and cancer incidence in rodent bioassays indicate that the LTL acceptable intake (AI) as derived using the ICH M7 framework would not exceed a negligible additional risk of cancer. Therefore, controlling N-nitrosamines to an LTL AI based on the ICH M7 framework is thus demonstrated to be protective for potential carcinogenic risk to patients over the exposure durations typical of clinical trials and many prescribed medicines.

Utilisation of parametric methods to improve percentile-based estimates for the carcinogenic potency of nitrosamines

N-Nitrosamines have recently been the subject of intense regulatory scrutiny, including the setting of low exposure limits (18 ng/day) (European Medicines Agency (EMA), 2020). This paper evaluates different methodologies to determine statistically robust bounds on the carcinogenic potency of chemical classes, using historic TD₅₀ data (Peto et al., 1984; Thresher et al., 2019) and exemplified for N-nitrosamines. Initially, the distribution of TD₅₀ values (TD₅₀s) for N-nitrosamines of known potency was characterised. From this, it is possible to compare parametric and non-parametric methods to obtain percentiles of interest from the distribution of TD₅₀s, which are shown to be robust to uncertainty in the initial TD₅₀ estimates. These methods may then be applied to different chemical subclasses. The values obtained may be of use in refining acceptable intakes for N-nitrosamines and their subclasses.

Machine Learning Predicts Degree of Aromaticity from Structural Fingerprints

Prediction of whether a compound is "aromatic" is at first glance a relatively simple task-does it obey Hückel's rule (planar cyclic π-system with 4n + 2 electrons) or not? However, aromaticity is far from a binary property, and there are distinct variations in the chemical and biological behavior of different systems which obey Hückel's rule and are thus classified as aromatic. To that end, the aromaticity of each molecule in a large public dataset was quantified by an extension of the work of Raczyńska et al. Building on this data, a method is proposed for machine learning the degree of aromaticity of each aromatic ring in a molecule. Categories are derived from the numeric results, allowing the differentiation of structural patterns between them and thus a better representation of the underlying chemical and biological behavior in expert and (Q)SAR systems.

Predicting reactivity to drug metabolism: beyond P450s-modelling FMOs and UGTs

We present a study based on density functional theory calculations to explore the rate limiting steps of product formation for oxidation by Flavin-containing Monooxygenase (FMO) and glucuronidation by the UDP-glucuronosyltransferase (UGT) family of enzymes. FMOs are responsible for the modification phase of metabolism of a wide diversity of drugs, working in conjunction with Cytochrome P450 (CYP) family of enzymes, and UGTs are the most important class of drug conjugation enzymes. Reactivity calculations are important for prediction of metabolism by CYPs and reactivity alone explains around 70-85% of the experimentally observed sites of metabolism within CYP substrates. In the current work we extend this approach to propose model systems which can be used to calculate the activation energies, i.e. reactivity, for the rate-limiting steps for both FMO oxidation and glucuronidation of potential sites of metabolism. These results are validated by comparison with the experimentally observed reaction rates and sites of metabolism, indicating that the presented models are suitable to provide the basis of a reactivity component within generalizable models to predict either FMO or UGT metabolism.

Predicting pKa Using a Combination of Semi-Empirical Quantum Mechanics and Radial Basis Function Methods

The acid dissociation constant (pK_a) has an important influence on molecular properties crucial to compound development in synthesis, formulation, and optimization of absorption, distribution, metabolism, and excretion properties. We will present a method that combines quantum mechanical calculations, at a semi-empirical level of theory, with machine learning to accurately predict pK_a for a diverse range of mono- and polyprotic compounds. The resulting model has been tested on two external data sets, one specifically used to test pK_a prediction methods (SAMPL6) and the second covering known drugs containing basic functionalities. Both sets were predicted with excellent accuracy (root-mean-square errors of 0.7-1.0 log units), comparable to other methodologies using a much higher level of theory and computational cost.

Development of New Epoxy Resin Monomers - A Delicate Balance between Skin Allergy and Polymerization Properties

Epoxy resin monomers (ERMs) are used as building blocks for thermosetting polymers in applications where strong, flexible, and lightweight materials are required. Most epoxy resins are polymers of diglycidyl ether of bisphenol A (DGEBA). It is highly allergenic and causes occupational allergic contact dermatitis and contact allergy in the general population. Thus, measures to prevent exposure by protective clothing and education are not enough. This work describes a continuation of our research aiming at reducing the skin-sensitizing potency of ERMs while maintaining the ability to form polymers. Alternative ERMs were designed and synthesized whereafter the sensitizing potency was determined using the murine local lymph node assay (LLNA). The reactivity of the diepoxides toward a nucleophilic peptide was investigated, and the differences in reactivity explained using computational studies. The diepoxides were reacted with triethylenetetramine, and the formed polymers were tested for technical applicability using thermogravimetric analysis. We had previously shown that the absence of an oxygen atom in the side chains or removal of aromaticity reduced the sensitizing potency compared to that of DGEBA. Thus, a cycloaliphatic analogue 1 of DGEBA without ether oxygen in the side chains was considered promising and was synthesized. As predicted, the sensitizing potency was considerably reduced (10 times) compared to that of DGEBA. However, the technical properties of the polymer of this compound were not considered sufficient. More polar aromatic analogues were investigated, but they could not compete with our previously described ERMs regarding polymerization properties and with 1 regarding low skin sensitization properties. Development of alternative epoxy materials is a delicate balance between allergenic activity and polymerization properties. Tuning of structural properties together with investigation of polymerization conditions combined with skin sensitization studies should be used in industrial research and development. ERM 1 could be used as a lead compound for further studies of aliphatic ERMs.

Quantifying confidence in the reporting of metabolic biotransformations

How confident can we be in the assignment of metabolite structures? Are the analytical techniques used sufficient to support hypotheses about what is being formed? In this Feature, we discuss the results of an extensive survey into the analytical techniques used, and their value in the characterisation of metabolites. The survey covers the structures of over 16000 metabolites formed from 1732 query compounds, covering over 35 years of the literature and a variety of journals. The value of different characterisation techniques is considered, alongside or in the absence of synthetic standards. The changes in analytical techniques used over time are briefly considered, and a metric for the confidence that a claimed metabolite has been confirmed is proposed.

Epoxyalcohols: bioactivation and conjugation required for skin sensitization

Allylic alcohols, such as geraniol 1, are easily oxidized by varying mechanisms, including the formation of both 2,3-epoxides and/or aldehydes. These epoxides, aldehydes, and epoxy-aldehydes can be interconverted to each other, and the reactivity of them all must be considered when considering the sensitization potential of the parent allylic alcohol. An in-depth study of the possible metabolites and autoxidation products of allylic alcohols is described, covering the formation, interconversion, reactivity, and sensitizing potential thereof, using a combination of in vivo, in vitro, in chemico, and in silico methods. This multimodal study, using the integration of diverse techniques to investigate the sensitization potential of a molecule, allows the identification of potential candidate(s) for the true culprit(s) in allergic responses to allylic alcohols. Overall, the sensitization potential of the investigated epoxyalcohols and unsaturated alcohols was found to derive from metabolic oxidation to the more potent aldehyde where possible. Where this is less likely, the compound remains weakly or nonsensitizing. Metabolic activation of a double bond to form a nonconjugated, nonterminal epoxide moiety is not enough to turn a nonsensitizing alcohol into a sensitizer, as such epoxides have low reactivity and low sensitizing potency. In addition, even an allylic 2,3-epoxide moiety is not necessarily a potent sensitizer, as shown for 2, where formation of the epoxide weakens the sensitization potential.