Regulatory Toxicology and Pharmacology最新文献

During 2020, The European Chemicals Agency (ECHA) began evaluating the OECD Test Guideline 443: Extended One Generation Reproductive Toxicity Study (EOGRTS) to analyze specific aspects related to study design, conduct and toxicological findings. A significant outcome of this ECHA evaluation focused on adequate dose level selection. Subsequently, ECHA published recommendations for DART studies, however, these recommendations seemingly do not align with the principles of the 3Rs, animal welfare or human safety goals, specifically, regarding three aspects. First, the requirement to segregate testing for sexual function and fertility from the ability to produce normally developing offspring increases the risk of inadequate identification of postnatal hazards for development and sexual function and fertility, therefore failing human health protection goals. Second, the current ECHA high-dose level setting recommendations for EOGRTS exceed the MTD (Maximum Tolerated Dose), and therefore compromise the interpretation of the biological response relative to the intrinsic effect of the chemical under evaluation. Third, the combination of these aspects will result in an increase in the number of animals tested, increasing animal welfare concerns.

This paper reflects the consensus of subject matter experts, professional, and scientific societies who have authored and signed on to this statement. The signatories encourage ECHA to adopt a revised science-driven approach to the dose selection criteria that strikes a balance between regulatory vigilance and scientific pragmatism.

As the United States and the European Union continue their steady march towards the acceptance of new approach methodologies (NAMs), we need to ensure that the available tools are fit for purpose. Critics will be well-positioned to caution against NAMs acceptance and adoption if the tools turn out to be inadequate. In this paper, we focus on Quantitative Structure Activity-Relationship (QSAR) models and highlight how the training database affects quality and performance of these models. Our analysis goes to the point of asking, “are the endpoints extracted from the experimental studies in the database trustworthy, or are they false negatives/positives themselves?” We also discuss the impacts of chemistry on QSAR models, including issues with 2-D structure analyses when dealing with isomers, metabolism, and toxicokinetics. We close our analysis with a discussion of challenges associated with translational toxicology, specifically the lack of adverse outcome pathways/adverse outcome pathway networks (AOPs/AOPNs) for many higher tier endpoints. We recognize that it takes a collaborate effort to build better and higher quality QSAR models especially for higher tier toxicological endpoints. Hence, it is critical to bring toxicologists, statisticians, and machine learning specialists together to discuss and solve these challenges to get relevant predictions.

Read-across (RAx) and grouping of chemicals into categories are well-known concepts in toxicology. Recently, ECHA proposed a grouping approach for branched-chain carboxylic acids (BCAs) including more than 60 branched-chain saturated carboxylic acids for hazard identification. Grouping was based only on structural considerations. Due to developmental effects of two members, ECHA postulated that “all short carbon chain acids … are likely reproductive and developmental toxicants”. This work analyzes available data for BCAs. The number of compounds in the group can be significantly reduced by eliminating metal and organic salts of BCAs, compounds of unknown or variable composition, and complex reaction products or biological materials (UVCB compounds). For the resulting reduced number of compounds, grouping is supported by similar physicochemical data and expected similar biotransformation. However, analysis of adverse effects for compounds in the group and mechanistic information show that BCAs, as a class, do not cause developmental effects in rats. Rather, developmental toxicity is limited to selected BCAs with specific structures that share a common mode of action (histone deacetylase inhibition). Thus, the proposed grouping is unreasonably wide and the more detailed analyses show that structural similarity alone is not sufficient for grouping branched-chain carboxylic acids for developmental toxicity.

Background

Few methods are available for transparently combining different evidence streams for chemical risk assessment to reach an integrated conclusion on the probability of causation. Hence, the UK Committees on Toxicity (COT) and on Carcinogenicity (COC) have reviewed current practice and developed guidance on how to achieve this in a transparent manner, using graphical visualisation.

Methods/approach

All lines of evidence, including toxicological, epidemiological, new approach methodologies, and mode of action should be considered, taking account of their strengths/weaknesses in their relative weighting towards a conclusion on the probability of causation. A qualitative estimate of the probability of causation is plotted for each line of evidence and a combined estimate provided.

Discussion/conclusions

Guidance is provided on integration of multiple lines of evidence for causation, based on current best practice. Qualitative estimates of probability for each line of evidence are plotted graphically. This ensures a deliberative, consensus conclusion on likelihood of causation is reached. It also ensures clear communication of the influence of the different lines of evidence on the overall conclusion on causality. Issues on which advice from the respective Committees is sought varies considerably, hence the guidance is designed to be sufficiently flexible to meet this need.

Multiple international guidelines exist that describe both quality and safety considerations for the control of the broad spectrum of impurities inherent to drug substance and product manufacturing processes. However, regarding non-mutagenic impurities (NMI) the most relevant ICH Q3A/B guidelines are not applicable during early phases of drug development leading to confusion about acceptable limits at this stage. Thus, there is need for more flexible approaches that ensure that patient safety remains paramount, while taking into consideration the limited duration of exposure. An EFPIA survey, which collected quantitative data from different types of studies applied to qualify impurities in accordance with ICH Q3A, shows that no toxicities could be attributed to any of the 467 impurities at any tested level in vivo. This data combined with earlier published toxicological datasets encompassing drug substances and intermediates, food related substances and chemicals provide convincing evidence that for NMIs, the application of a generic 5 mg/day limit for an exposure duration <6 months, and a 1 mg/day generic limit for life-long exposure, provides sufficient margins to ensure patient safety. Hence, application of these absolute limits to trigger qualification studies (instead of the relative limits described in Q3A/B), is considered warranted. This approach will prevent conduct of unnecessary dedicated impurity qualification studies and the resulting use of animals.

Permitted Daily Exposure Limits (PDEs) are set for Active Pharmaceutical Ingredients (APIs) to control cross-contamination when manufacturing medicinal products in shared facilities. With the lack of official PDE lists for pharmaceuticals, PDEs have to be set by each company separately. Although general rules and guidelines for the setting of PDEs exist, inter-company variations in the setting of PDEs occur and are considered acceptable within a certain range. To evaluate the robustness of the PDE approach between different pharmaceutical companies, data on PDE setting of five marketed APIs (amlodipine, hydrochlorothiazide, metformin, morphine, and omeprazole) were collected and compared. Findings show that the variability between PDE values is within acceptable ranges (below 10-fold) for all compounds, with the highest difference for morphine due to different Point of Departures (PODs) and Adjustment Factors (AFs). Factors of PDE variability identified and further discussed are: (1) availability of data, (2) selection of POD, (3) assignment of AFs, (4) route-to-route extrapolation, and (5) expert judgement and differences in company policies. We conclude that the investigated PDE methods and calculations are robust and scientifically defensible. Additionally, we provide further recommendations to harmonize PDE calculation approaches across the pharmaceutical industry.

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.

ICH Q3A/B guidelines provide qualification thresholds for impurities or degradation products in new drug substances and products. However, the guidelines note that certain impurities/degradation products may warrant further safety evaluation for being unusually potent or toxic. The purpose of this study was to confirm that especially toxic non-mutagenic compounds are rare and to identify classes of compounds that could warrant lower qualification thresholds. A total of 2815 compounds were evaluated, of which 2213 were assessed as non-mutagenic. For the purpose of this analysis, compounds were considered potent when the point of departure was ≤0.2 mg/kg/day based on the qualification threshold (1 mg/day or 0.02 mg/kg/day for a 50 kg human) in a new drug substance, with an additional 10-fold margin. Only 54 of the entire set (2.4%) would be considered potent based on this conservative potency analysis, confirming that the existing ICH Q3A/B qualification thresholds are appropriate for the majority of impurities. If the Q3A/B threshold, without the additional 10-fold margin is used, 14 compounds (0.6%) are considered “highly potent”. Very few non-mutagenic structural classes were identified, including organothiophosphates and derivatives, polychlorinated benzenes and polychlorinated polycyclic aliphatics, that correlate with potential high potency, consistent with prior publications.