A practical application of two in silico systems for identification of potentially mutagenic impurities

Greene, Nigel; Dobo, Krista L.; Kenyon, Michelle; Cheung, Jennifer R.; Munzner, Jennifer B.; Sobol, Zhanna; Sluggett, Gregory W.; Zelesky, Todd; Sutter, Andreas; Wichard, Joerg

doi:10.1016/j.yrtph.2015.05.008

Cited by 45 publications

(21 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Derek Nexus 3.01 (DerN), Sarah Nexus 1.0 (SarN), LeadScope Model Applier 1.6.0 (LeadA), and Case Ultra (MCase_U) were applied to 801 in-house chemicals. In a following step, binary combinations of QSARs (DerN_MCase, DerN_SarN, DerN_LeadA) were applied to the same set of chemicals (Greene et al, 2015) Other studies considered combinations of models, and arrived to similar conclusions on the balance between sensitivity and specificity. In particular, Contrera (Contrera, 2013), in a study within the scope of ICH M7 guideline (Assessment and control of DNA-reactive impurities in pharmaceuticals to limit potential carcinogenic risk (Amberg et al, 2016)), used an expert knowledge-based system (ToxTree) and an ad hoc developed statistical model (SciQSAR).…”

Section: Combinations Of Qsar Systemsmentioning

confidence: 99%

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Benigni¹,

Battistelli²,

Bossa³

et al. 2019

EFSA Supporting Publications

View full text Add to dashboard Cite

To facilitate the practical implementation of the guidance on the residue definition for dietary risk assessment, EFSA has organized an evaluation of applicability of existing in silico models for predicting the genotoxicity of pesticides and their metabolites, including analysis of the impact on genotoxicity of the metabolic structural changes. The prediction ability of (Q)SARs for in vitro and in vivo tests were evaluated. For the Ames test, all (Q)SAR models generated statistically significant predictions, comparable with the experimental variability of the test; instead, the reliability of the (Q)SAR models for assays / endpoints different from in vitro bacterial mutagenicity appears to be quite far from optimality. Secondly, two new Read Across approaches were applied to predict Ames mutagenicity and in vitro Chromosomal Aberrations: Read Across was largely successful for predicting the Ames test results, but much less for in vitro Chromosomal Aberrations. The worse results for endpoints different from Ames may be attributable to the several revisions of experimental protocols and evaluation criteria of results that have made the databases qualitatively non‐homogeneous, and poorly suitable for modelling. A third dimension of this research is the evaluation of the impact of the structural changes‐in result of metabolic or degradation processes‐on the genotoxic potential of the substances. Parent/Metabolite structural differences (beyond the known Structural Alerts) that may, or may not cause changes in the Ames mutagenicity were identified and catalogued. In addition, Structural Alerts analysis applied under human expert supervision permitted the rationalization of the large majority of the changes of patterns of genotoxicity. The findings from this work are suitable for being integrated into Weight‐of‐Evidence and Tiered evaluation schemes. The importance of the human expert knowledge is particularly emphasized.

show abstract

Section: Combinations Of Qsar Systemsmentioning

confidence: 99%

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Benigni¹,

Battistelli²,

Bossa³

et al. 2019

EFSA Supporting Publications

View full text Add to dashboard Cite

show abstract

“…Yapısal alarmların taranmasında uzman bir sistemin ve tamamlayıcı bir istatistiksel modelin birlikte kullanılmasını önermektedir. 3,24 GENOTOKSİK SAFSIZLIKLARA ÖRNEKLER Bazı olası genotoksik yapılara örnek olarak alkil halidler, alkil sülfonatlar gibi alkilleyici ajanlar verilebilir. Bu moleküller genellikle reaktif olarak kullanılır veya kimyasal sentez sırasında oluşabilir.…”

Section: Avrupa İlaç Ajansi Yaklaşimiunclassified

Genotoxic Impurities in Drugs for Human: Review

Palabıyık¹,

Baydar²,

Şahin³

2016

Turkiye Klinikleri J Pharm Sci

View full text Add to dashboard Cite

“…The toxicity of drug impurities is closely related to their structure. Structure-activity relationships (SARs) have been widely used in Europe and the United States to predict toxicity by computer (Greene et al, 2015; Pavan et al, 2016; Guan et al, 2019). We have recently systematically discussed the structure-toxicity relationship of cephalosporins via the zebrafish embryo toxicity test combined with computational chemistry and molecular docking techniques.…”

Section: Introductionmentioning

confidence: 99%

In silico ADME and Toxicity Prediction of Ceftazidime and Its Impurities

et al. 2019

View full text Add to dashboard Cite

To improve the quality control of drugs, we predicted the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of ceftazidime (CAZ) and its impurities via in silico methods. We used three types of quantitative structure-activity relationship and docking software for precise prediction: Discovery Studio 4.0, OECD QSAR Toolbox 4.1, Toxtree, and the pkCSM approach. The pharmacokinetics and toxicity of ceftazidime and impurity A (Δ-2-CAZ) are similar. The biological properties of impurity B (CAZ E -isomer) are different from CAZ. Therefore, we focused on drug stability to analyze impurity B. Impurities D and I have strong lipophilicity, good intestinal absorption, and poor excretion in the body. Impurity D is particularly neurotoxic and genotoxic. It is important to control the content of impurity D. The toxicity of impurity F is low, but the toxicity is enhanced when it becomes the C-3 side chain of CAZ and forms a quaternary amine group. We conclude that the beta-lactam ring of nucleus, the quaternary amine group at the C-3 side chain, and the acetates at the C-7 side chain of CAZ are the main toxic functional groups. Impurities B and D may be the genetic impurity in CAZ and may also have neurotoxicity. This in silico approach can predict the toxicity of other cephalosporins and impurities.

show abstract

A practical application of two in silico systems for identification of potentially mutagenic impurities

Cited by 45 publications

References 14 publications

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Genotoxic Impurities in Drugs for Human: Review

In silico ADME and Toxicity Prediction of Ceftazidime and Its Impurities

Contact Info

Product

Resources

About