The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

The ICH M7 guideline describes a consistent approach to identify, categorize, and control DNA reactive, mutagenic, impurities in pharmaceutical products to limit the potential carcinogenic risk related to such impurities. This paper outlines a series of principles and procedures to consider when generating (Q)SAR assessments aligned with the ICH M7 guideline to be included in a regulatory submission. In the absence of adequate experimental data, the results from two complementary (Q)SAR methodologies may be combined to support an initial hazard classification. This may be followed by an assessment of additional information that serves as the basis for an expert review to support or refute the predictions. This paper elucidates scenarios where additional expert knowledge may be beneficial, what such an expert review may contain, and how the results and accompanying considerations may be documented. Furthermore, the use of these principles and procedures to yield a consistent and robust (Q)SAR-based argument to support impurity qualification for regulatory purposes is described in this manuscript.

No abstract

No abstract

No abstract

No abstract

1,3-Butadiene (BD) is a rodent and human carcinogen. While several epoxides formed during BD metabolism are mutagenic and may contribute to BD carcinogenicity, another proposed metabolite, hydroxymethylvinyl ketone (HMVK), could also be involved. A significant quantity of HMVK is likely to be formed since it is a proposed intermediate in the metabolism of 3-butene-1,2-diol (BD-diol) to 1,2-dihydroxy-4-(N-acetylcysteinyl)butane, the major mercapturic acid metabolite of BD in humans. In addition, BD-diol is a major BD metabolite in liver perfusion experiments in rodents. By analogy with other alpha,beta-unsaturated carbonyls, HMVK is likely to be mutagenic via formation of promutagenic 1,N(2)-propanodeoxyguanosine adducts. The objective of the current study was to investigate the formation of such adducts in vitro. The reaction between HMVK and dGuo yielded two major products shown to be identical by positive ion electrospray-MS, having protonated molecular ions with m/z consistent with HMVK-derived 1,N(2)-propanodeoxyguanosine (HMVK-dGuo). Rechromatography of each fraction yielded two fractions with retention times identical to those initially isolated, suggesting equilibration between two diastereomers. Two partially resolved sets of (1)H NMR signals were consistent with a 1:1 mixture of diastereomeric C-6-substituted adducts equilibrating slowly on an NMR time-scale. Following deglycosylation, C-6 substitution was verified by two-dimensional correlation NMR spectroscopy, indicating that the initial adducts were formed by Michael addition of dGuo-N1 to the terminal vinyl carbon followed by cyclization to the 1,N(2)-propano structure. Reactions with calf thymus DNA under physiological conditions yielded two sets of products. The first set had HPLC retention times and mass spectra identical to those of the previously characterized C-6-substituted HMVK-dGuo diastereomers. The second set had a molecular ion and fragmentation pattern identical to the C-6-substituted adducts and on this basis were assigned as the diastereomeric C-8 adducts. In addition to detecting HMVK-dGuo in treated DNA, the adducts were also present in control DNA. Overall, our research demonstrates that HMVK can form promutagenic DNA adducts and it therefore has the potential to play a role in BD-associated mutagenicity.

Species differences in drug metabolism present two challenges that may confound the nonclinical safety assessment of candidate drugs. The first challenge is encountered when metabolites are formed uniquely or disproportionately in humans. Another challenge is understanding the human relevance of toxicities associated with metabolites formed uniquely or disproportionately in a nonclinical species. One potential approach to minimize the impact of metabolite related challenges is to consider genetically engineered mouse models that express human P450 enzymes. Human P450 expressing mouse models may have the ability to generate major human metabolites and eliminate or reduce the formation of mouse specific metabolites. Prior to determining the utility of any particular model, it is important to qualify by characterizing protein expression, establishing whether the model generates an in vivo metabolite profile more closely related to that of humans than the wild-type mouse, verifying genetic stability, and evaluating animal health. When compared to the current strategy for handling metabolite challenges (i.e., direct administration of metabolite), identifying an appropriate human P450 expressing model could provide a number of benefits. Such benefits include improved scientific relevance of the evaluation, decreased resource needs, and a possible reduction in the number of animals used. These benefits may ultimately improve the quality and speed by which promising new drug candidates are developed and delivered to patients.