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

Retrospective application of ICH M7 to anti-hypertensive drugs in Brazil: Risk assessment of potentially mutagenic impurities

Potentially mutagenic impurities are likely to be formed in any drug substance, since their synthesis requires reactive intermediates which may also react with DNA. The ICH M7 guideline, which defines how to risk assess and control mutagenic impurities, was first published in 2014 and is not to be applied retrospectively; however, some impurities have been found above the permitted limits in drug products which were already on the market. This study assessed the implications of applying ICH M7 retrospectively to anti-hypertensive drugs marketed in Brazil by performing a risk assessment and establishing control strategies. The manufacturing processes of 15 drug substances were evaluated and 262 impurities were identified, from which 21% were classified as potentially mutagenic. Most of the impurities were identified below ICH M7 acceptable limits, except for impurities described in a pharmacopoeial monograph. Compendial specifications are defined based on scientific evidence and play an important role in setting quality and safety standards for pharmaceuticals, however there are opportunities for further alignment with ICH guidelines, aiming for a holistic assessment of the impurities profile to ensure the safety of medicines.

A Kinetic Model for Assessing Potential Nitrosamine Carcinogenicity

Understanding the potential carcinogenic potency of nitrosamines is necessary to setting acceptable intake limits. Nitrosamines and the components that can form them are commonly present in food, water, cosmetics, and tobacco. The recent observation of nitrosamines in pharmaceuticals highlighted the need for effective methods to determine acceptable intake limits. Herein, we describe two computational models that utilize properties based upon quantum mechanical calculations in conjunction with mechanistic insights and established data to determine the carcinogenic potency of a variety of common nitrosamines. These models can be applied to experimentally untested nitrosamines to aid in the establishment of acceptable intake limits.

N-nitrosamine impurity risk assessment in pharmaceuticals: Utilizing In vivo mutation relative potency comparison to establish an acceptable intake for NTTP

The finding of N-nitrosodiethylamine (NDEA) and N-nitrosodimethylamine (NDMA) in marketed drugs has led to implementation of risk assessment processes intended to limit exposures to the entire class of N-nitrosamines. A critical component of the risk assessment process is establishing exposure limits that are protective of human health. One approach to establishing exposure limits for novel N-nitrosamines is to conduct an in vivo transgenic rodent (TGR) mutation study. Existing regulatory guidance on N-nitrosamines provides decision making criteria based on interpreting in vivo TGR mutation studies as an overall positive or negative. However, point of departure metrics, such as benchmark dose (BMD), can be used to define potency and provide an opportunity to establish relevant exposure limits. This can be achieved through relative potency comparison of novel N-nitrosamines with model N-nitrosamines possessing robust in vivo mutagenicity and carcinogenicity data. The current work adds to the dataset of model N-nitrosamines by providing in vivo TGR mutation data for N-nitrosopiperidine (NPIP). In vivo TGR mutation data was also generated for a novel N-nitrosamine impurity identified in sitagliptin-containing products, 7-nitroso-3-(trifluoromethyl)-5,6,7,8-tetrahydro-[1,2,4]triazolo-[4,3-a]pyrazine (NTTP). Using the relative potency comparison approach, we have demonstrated the safety of NTTP exposures at or above levels of 1500 ng/day.

Estimation of acceptable daily intake values based on modeling and in vivo mutagenicity of NDSRIs of fluoxetine, duloxetine and atomoxetine

Nitrosamine drug substance related impurities or NDSRIs can be formed if an active pharmaceutical ingredient (API) has an intrinsic secondary amine that can undergo nitrosation. This is a concern as 1) nitrosamines are potentially highly potent carcinogens, 2) secondary amines in API are common, and 3) NDSRIs that might form from such secondary amines will be of unknown carcinogenic potency. Approaches for evaluating NDSRIs include read across, quantum mechanical modeling of reactivity, in vitro mutation data, and transgenic in vivo mutation data. These approaches were used here to assess NDSRIs that could potentially form from the drugs fluoxetine, duloxetine and atomoxetine. Based on a read across informed by modeling of physicochemical properties and mechanistic activation from quantum mechanical modeling, NDSRIs of fluoxetine, duloxetine, and atomoxetine were 10-100-fold less potent compared with highly potent nitrosamines such as NDMA or NDEA. While the NDSRIs were all confirmed to be mutagenic in vitro (Ames assay) and in vivo (TGR) studies, the latter data indicated that the potency of the mutation response was ≥4400 ng/day for all compounds-an order of magnitude higher than published regulatory limits for these NDSRIs. The approaches described herein can be used qualitatively to better categorize NDSRIs with respect to potency and inform whether they are in the ICH M7 (R2) designated Cohort of Concern.

Quantum Mechanical Assessment of Nitrosamine Potency

Nitrosamines are in the cohort of concern (CoC) as determined by regulatory guidance. CoC compounds are considered highly potent carcinogens that need to be limited below the threshold of toxicological concern, 1.5 μg/day. Nitrosamines like NDMA and NDEA require strict control, while novel nitrosamine drug substance-related impurities (NDSRIs) may or may not be characterized as potent carcinogens. A risk assessment based on the structural features of NDSRIs is important in order to predict potency because they lack substance-specific carcinogenicity. Herein, we present a quantum mechanical (QM)-based analysis on structurally diverse sets of nitrosamines to better understand how structure influences the reactivity that could result in carcinogenicity. We describe the potency trend through activation energies corresponding to α-hydroxylation, aldehyde formation, diazonium intermediate formation, reaction with DNA base, and hydrolysis reactions, and other probable metabolic pathways associated with the carcinogenicity of nitrosamines. We evaluated activation energies for selected cases such as N-nitroso pyrrolidines, N-nitroso piperidines, N-nitroso piperazines, N-nitroso morpholines, N-nitroso thiomorpholine, N-methyl nitroso aromatic, fluorine-substituted nitrosamines, and substituted aliphatic nitrosamines. We compare these results to the recent framework of the carcinogenic potency characterization approach (CPCA) proposed by health authorities which is meant to give guidance on acceptable intakes (AI) for NDSRIs lacking substance-specific carcinogenicity data. We show examples where QM modeling and CPCA are aligned and examples where CPCA both underestimates and overestimates the AI. In cases where CPCA predicts high potency for NDSRIs, QM modeling can help better estimate an AI. Our results suggest that a combined mechanistic understanding of α-hydroxylation, aldehyde formation, hydrolysis, and reaction with DNA bases could help identify the structural features that underpin the potency of nitrosamines. We anticipate this work will be a valuable addition to the CPCA and provide a more analytical way to estimate AI for novel NDSRIs.

Determining recommended acceptable intake limits for N-nitrosamine impurities in pharmaceuticals: Development and application of the Carcinogenic Potency Categorization Approach (CPCA)

N-Nitrosamine impurities, including nitrosamine drug substance-related impurities (NDSRIs), have challenged pharmaceutical industry and regulators alike and affected the global drug supply over the past 5 years. Nitrosamines are a class of known carcinogens, but NDSRIs have posed additional challenges as many lack empirical data to establish acceptable intake (AI) limits. Read-across analysis from surrogates has been used to identify AI limits in some cases; however, this approach is limited by the availability of robustly-tested surrogates matching the structural features of NDSRIs, which usually contain a diverse array of functional groups. Furthermore, the absence of a surrogate has resulted in conservative AI limits in some cases, posing practical challenges for impurity control. Therefore, a new framework for determining recommended AI limits was urgently needed. Here, the Carcinogenic Potency Categorization Approach (CPCA) and its supporting scientific rationale are presented. The CPCA is a rapidly-applied structure-activity relationship-based method that assigns a nitrosamine to 1 of 5 categories, each with a corresponding AI limit, reflecting predicted carcinogenic potency. The CPCA considers the number and distribution of α-hydrogens at the N-nitroso center and other activating and deactivating structural features of a nitrosamine that affect the α-hydroxylation metabolic activation pathway of carcinogenesis. The CPCA has been adopted internationally by several drug regulatory authorities as a simplified approach and a starting point to determine recommended AI limits for nitrosamines without the need for compound-specific empirical data.

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.

The comprehensive prediction of carcinogenic potency and tumorigenic dose (TD50) for two problematic N-nitrosamines in food: NMAMPA and NMAMBA using toxicology in silico methods

The identification and toxicological assessment of potential carcinogens is of paramount importance for public health and safety. This study aimed to predict the carcinogenic potency and tumorigenic dose (TD50) for two problematic N-nitrosamines (N-NAs) commonly found in food: N-2-methylpropyl-N-1-methylacetonylnitrosamine (NMAMPA, CAS: 93755-83-0) and N-3-Methylbutyl-N-1-methylacetonylnitrosamine (NMAMBA, CAS: 71016-15-4). To achieve this goal, in silico toxicology methods were employed due to their practical applications and potential in risk assessment. The justification for conducting these studies was incoherent results published by the European Food Safety Authority (EFSA). For this purpose, we applied various in silico tools, including qualitative methods (ToxTree, ProTox II and CarcinoPred-EL) and quantitative methods (QSAR Toolbox and LAZAR) were applied to predict the carcinogenic potency. These tools leverage computational approaches to analyze chemical structures for finding toxicophores and generating predictions, making them efficient alternatives to traditional in vivo experiments. The results obtained indicated that N-NAs are carcinogenic compounds, and quantitative data was obtained in the form of estimated doses of TD50 for the compounds tested.

Nitrosamine Impurities in Pharmaceuticals: An Empirical Review of their Detection, Mechanisms, and Regulatory Approaches

Since their discovery in valsartan-containing drugs, nitrosamine impurities have emerged as a significant safety problem in pharmaceutical products, prompting extensive recalls and suspensions. Valsartan, candesartan, irbesartan, olmesartan, and other sartans have been discovered to have additional nitrosamine impurities, such as N-nitroso-N-methyl-4-aminobutyric acid (NMBA), N-nitroso-Di-isopropyl amine (NDIPA), N-nitroso-Ethyl-Isopropyl amine (NEIPA), and N-nitroso-Diethyl amine (NDEA). Concerns about drug safety have grown in response to reports of nitrosamine contamination in pharmaceuticals, such as pioglitazone, rifampin, rifapentine, and varenicline. This review investigates the occurrence and impact of nitrosamine impurities in sartans and pharmaceutical goods, as well as their underlying causes. The discussion emphasizes the significance of comprehensive risk assessment and mitigation approaches at various phases of medication development and manufacturing. The link between amines and nitrosamine impurities is also investigated, with an emphasis on pH levels and the behaviour of primary, secondary, tertiary, and quaternary amines. Regulations defining standards for nitrosamine assessment and management, such as ICH Q3A-Q3E and ICH M7, are critical in resolving impurity issues. Furthermore, the Global Substance Registration System (GSRS) is underlined as being critical for information sharing and product safety in the pharmaceutical industry. The review specifically focuses on the relationship between ranitidine and N-nitroso dimethyl amine (NDMA) in the context of the implications of nitrosamine contamination on patient safety and medicine supply. The importance of regulatory authorities in discovering and correcting nitrosamine impurities is highlighted in order to improve patient safety, product quality, and life expectancy. Furthermore, the significance of ongoing study and attention to nitrosamine-related repercussions for increasing pharmaceutical safety and overall public health is emphasized.

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.

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chemistry and biochemistry. The pharmaceutical industry leverages QM models explicitly in covalent drug discovery and implicitly to characterize short-range interactions in noncovalent binding. Predictive toxicology has resisted widespread adoption of QM, including in the pharmaceutical industry, despite its obvious relevance to the metabolic processes in the upstream of adverse outcome pathways and advances in both QM methods and computational resources, which support fit-for-purpose applications in reasonable timeframes. Here, we make the case for embracing QM as an indispensable part of a toxicologist's toolkit. We argue that QM provides the necessary orthogonality to alert-based expert systems and traditional QSARs, consistent with calls for animal-free integrated testing strategies for safety assessments of commercial chemicals. We outline existing roadblocks to this transition, including the need to train model developers in QM and the shift toward service-based toxicity models that utilize high-performance computing clusters. Lastly, we describe recent examples of successful implementations of QM in hazard assessments and propose how in silico toxicology can be further advanced by integrating QM with artificial intelligence.

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.

Modeling the Impact of Excipients Selection on Nitrosamine Formation towards Risk Mitigation

Risk control for nitrosamine impurities in drug products is currently a major challenge in the industry. Nitrosamines can form during drug product manufacturing and storage through the reaction of nitrites with amine-containing APIs or impurities. The level of nitrites in excipients and the rate of reaction often control the build-up of nitrosamine. Although the variability in nitrite levels across excipient types and suppliers is well recognized, the impact of excipient selection on the level of nitrosamine formed has not been systematically studied. This gap of knowledge is addressed in the current work. We present theoretical case studies of formulations where microcrystalline cellulose (MCC), or lactose supplier, or superdisintegrant type are changed in pursuit of lower levels of nitrite. The impact of the average, maximum, and minimum levels of nitrites in each excipient on nitrosamine formation in the dosage form is calculated. The input data for this calculation are the formulation composition, nitrosamine molecular weight (MW), percentage of conversion, and nitrite levels per excipient. The percentage of conversion (based on the formulation and manufacturing variables) and nitrite levels were taken from the recent literature. We show that changing the supplier of a single excipient, or of the three most critical excipients, can reduce nitrosamine formation by up to -59% and -89%, respectively. We also show that high-risk formulations, e.g., high MW nitrosamines, high dosage weights, and high percentages of conversion (e.g., wet granulation), can often be de-risked below regulatory acceptable daily intake via careful excipient selection. Finally, we provide an open-access tool that enables users to calculate the theoretical formation of nitrosamines in their specific formulations. This calculation template can be used for (i) the preliminary screening of the risk of nitrosamine formation in drug products and (ii) the preliminary assessment of the impact of excipient selection for risk mitigation.

Computational Prediction of Metabolic α-Carbon Hydroxylation Potential of N-Nitrosamines: Overcoming Data Limitations for Carcinogenicity Assessment

Recent withdrawal of several drugs from the market due to elevated levels of N-nitrosamine impurities underscores the need for computational approaches to assess the carcinogenicity risk of nitrosamines. However, current approaches are limited because robust animal carcinogenicity data are only available for a few simple nitrosamines, which do not represent the structural diversity of the many possible nitrosamine drug substance related impurities (NDSRIs). In this paper, we present a novel method that uses data on CYP-mediated metabolic hydroxylation of CH₂ groups in non-nitrosamine xenobiotics to identify structural features that may also help in predicting the likelihood of metabolic α-carbon hydroxylation in N-nitrosamines. Our approach offers a new avenue for tapping into potentially large experimental data sets on xenobiotic metabolism to improve risk assessment of nitrosamines. As α-carbon hydroxylation is the crucial rate-limiting step in nitrosamine metabolic activation, identifying and quantifying the influence of various structural features on this step can provide valuable insights into their carcinogenic potential. This is especially important considering the scarce information available on factors that affect NDSRI metabolic activation. We have identified hundreds of structural features and calculated their impact on hydroxylation, a significant advancement compared to the limited findings from the small nitrosamine carcinogenicity data set. While relying solely on α-carbon hydroxylation prediction is insufficient for forecasting carcinogenic potency, the identified features can help in the selection of relevant structural analogues in read across studies and assist experts who, after considering other factors such as the reactivity of the resulting electrophilic diazonium species, can establish the acceptable intake (AI) limits for nitrosamine impurities.

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.

Comparative Evaluation of Chemical and Photolytic Denitrosation Methods for Chemiluminescence Detection of Total N-Nitrosamines in Wastewater Samples

N-Nitrosamines form as byproducts during oxidative water treatment and occur as impurities in consumer and industrial products. To date, two methods based on chemiluminescence (CL) detection of nitric oxide liberated from N-nitrosamines via denitrosation with acidic triiodide (HI₃) treatment or ultraviolet (UV) photolysis have been developed to enable the quantification of total N-nitrosamines (TONO) in environmental water samples. In this work, we configured an integrated experimental setup to compare the performance of HI₃-CL and UV-CL methods with a focus on their applicability for TONO measurements in wastewater samples. With the use of a large-volume purge vessel for chemical denitrosation, the HI₃-CL method achieved signal stability and detection limits comparable to those achieved by the UV-CL method which utilized a microphotochemical reactor for photolytic denitrosation. Sixty-six structurally diverse N-nitroso compounds (NOCs) yielded a range of conversion efficiencies relative to N-nitrosodimethylamine (NDMA) regardless of the conditions applied for denitrosation. On average, TONO measured in preconcentrated raw and chloraminated wastewater samples by the HI₃-CL method were 2.1 ± 1.1 times those measured by the UV-CL method, pointing to potential matrix interferences as further confirmed by spike recovery tests. Overall, our comparative assessment of the HI₃-CL and UV-CL methods serves as a basis for addressing methodological gaps in TONO analysis.

Quantum-Mechanical Approach to Predicting the Carcinogenic Potency of N-Nitroso Impurities in Pharmaceuticals

N-Nitroso contaminants in medicinal products are of concern due to their high carcinogenic potency; however, not all these compounds are created equal, and some are relatively benign chemicals. Understanding the structure-activity relationships (SARs) that drive hazards in one molecule versus another is key to both protecting human health and alleviating costly and sometimes inaccurate animal testing. Here, we report on an extension of the CADRE (computer-aided discovery and REdesign) platform, which is used broadly by the pharmaceutical and personal care industries to assess environmental and human health endpoints, to predict the carcinogenic potency of N-nitroso compounds. The model distinguishes compounds in three potency categories with 77% accuracy in external testing, which surpasses the reproducibility of rodent cancer bioassays and constraints imposed by limited (high-quality) data. The robustness of predictions for more complex pharmaceuticals is maximized by capturing key SARs using quantum mechanics, that is, by hinging the model on the underlying chemistry versus chemicals in the training set. To this end, the present approach can be leveraged in a quantitative hazard assessment and to offer qualitative guidance using electronic structure comparisons between well-studied analogues and unknown contaminants.

Current Threat of Nitrosamines in Pharmaceuticals and Scientific Strategies for Risk Mitigation

The current global situation of nitrosamine contamination has expanded from angiotensin-II receptor blockers (ARBs) to wide range of medicines as the risk of contamination via the drug substances, formulation, manufacturing process, and packaging is possible for many drug products. The understanding of chemistry, toxicology, and root causes of nitrosamines are mandatory to effectively evaluate and mitigate the risks associated with the contaminated mutagen. Lessons learnt and scientific findings from previously identified root causes are good examples on how to perform effective risk assessments and establish control strategies. Addressing the risk of nitrosamine contamination in pharmaceuticals requires significant knowledge and considerable resources to collect the necessary information for risk evaluation. Examples of the resources required include a reliable laboratory facility, reference material, highly specific and sensitive instrumentation able handle trace levels of contamination, data management, and the most limited resource - time. Therefore, the supporting tools to assist with risk assessment e.g., shared databases for drug and excipients in concern, screening models for the determination of nitrosamine formation potential, and an in silico model to help with toxicity estimation, have proven to be beneficial to tackle the risk and concern of nitrosamine contamination in pharmaceuticals.

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.

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.