Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities

The toxicological assessment of genotoxic impurities is important in the regulatory framework for pharmaceuticals. In this context, the application of promising computational methods (e.g. Quantitative Structure–Activity Relationships (QSARs), Structure–Activity Relationships (SARs) and/or expert systems) for the evaluation of genotoxicity is needed, especially when very limited information on impurities is available. To gain an overview of how computational methods are used internationally in the regulatory assessment of pharmaceutical impurities, the current regulatory documents were reviewed. The software recommended in the guidelines (e.g. MCASE, MC4PC, Derek for Windows) or used practically by various regulatory agencies (e.g. US Food and Drug Administration, US and Danish Environmental Protection Agencies), as well as other existing programs were analysed. Both statistically based and knowledge-based (expert system) tools were analysed. The overall conclusions on the available in silico tools for genotoxicity and carcinogenicity prediction are quite optimistic, and the regulatory application of QSAR methods is constantly growing. For regulatory purposes, it is recommended that predictions of genotoxicity/carcinogenicity should be based on a battery of models, combining high-sensitivity models (low rate of false negatives) with high-specificity ones (low rate of false positives) and in vitro assays in an integrated manner.

[1]  Naomi L Kruhlak,et al.  Comparison of MC4PC and MDL-QSAR rodent carcinogenicity predictions and the enhancement of predictive performance by combining QSAR models. , 2007, Regulatory toxicology and pharmacology : RTP.

[2]  E Kennepohl,et al.  A procedure for the safety evaluation of flavouring substances. Joint FAO/WHO Expert Committee on Food Additives. , 1999, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[3]  I. Tetko,et al.  Applicability domain for in silico models to achieve accuracy of experimental measurements , 2010 .

[4]  Naomi L Kruhlak,et al.  Combined Use of MC4PC, MDL-QSAR, BioEpisteme, Leadscope PDM, and Derek for Windows Software to Achieve High-Performance, High-Confidence, Mode of Action–Based Predictions of Chemical Carcinogenesis in Rodents , 2008, Toxicology mechanisms and methods.

[5]  Maykel Pérez González,et al.  The Prediction of Carcinogenicity from Molecular Structure , 2005 .

[6]  Nicola J Hewitt,et al.  A tiered approach to the use of alternatives to animal testing for the safety assessment of cosmetics: genotoxicity. A COLIPA analysis. , 2010, Regulatory toxicology and pharmacology : RTP.

[7]  S. Prabu IMPURITIES AND ITS IMPORTANCE IN PHARMACY , 2010 .

[8]  Ronald D Snyder,et al.  An update on the genotoxicity and carcinogenicity of marketed pharmaceuticals with reference to in silico predictivity , 2009, Environmental and molecular mutagenesis.

[9]  J. Contrera,et al.  Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices. , 2003, Regulatory toxicology and pharmacology : RTP.

[10]  T. McGovern,et al.  Regulation of genotoxic and carcinogenic impurities in drug substances and products , 2006 .

[11]  Fuart Gatnik Mojca,et al.  Review of QSAR Models and Software Tools for Predicting of Genotoxicity and Carcinogenicity , 2010 .

[12]  Lutz Müller,et al.  A rationale for determining, testing, and controlling specific impurities in pharmaceuticals that possess potential for genotoxicity. , 2006, Regulatory toxicology and pharmacology : RTP.

[13]  Wolfgang Schwack,et al.  Nontargeted multicomponent analytical screening of plastic food contact materials using fast interpretation of deliverables via expert structure-activity relationship software. , 2009, Journal of AOAC International.

[14]  Naomi L. Kruhlak,et al.  In Silico Screening of Chemicals for Genetic Toxicity Using MDL-QSAR, Nonparametric Discriminant Analysis, E-State, Connectivity, and Molecular Property Descriptors , 2008, Toxicology mechanisms and methods.

[15]  D. Snodin Genotoxic Impurities: From Structural Alerts to Qualification , 2010 .

[16]  Naomi L Kruhlak,et al.  Progress in QSAR toxicity screening of pharmaceutical impurities and other FDA regulated products. , 2007, Advanced drug delivery reviews.

[17]  I C Munro,et al.  Thresholds of toxicological concern based on structure-activity relationships. , 1996, Drug metabolism reviews.

[18]  Ann M Richard,et al.  A novel approach: chemical relational databases, and the role of the ISSCAN database on assessing chemical carcinogenicity. , 2008, Annali dell'Istituto superiore di sanita.

[19]  David K. Robbins,et al.  Risk Assessment of Genotoxic Impurities in Marketed Compounds Administered over a Short-Term Duration: Applications to Oncology Products and Implications for Impurity Control Limits , 2010 .

[20]  Milan Randic,et al.  Chemical structure---What is , 1992 .

[21]  E. Matthews,et al.  Prediction of drug-related cardiac adverse effects in humans--B: use of QSAR programs for early detection of drug-induced cardiac toxicities. , 2010, Regulatory toxicology and pharmacology : RTP.

[22]  M T D Cronin,et al.  A review of the electrophilic reaction chemistry involved in covalent DNA binding , 2010, Critical reviews in toxicology.

[23]  Derek Robinson,et al.  Control of Genotoxic Impurities in Active Pharmaceutical Ingredients: A Review and Perspective , 2010 .

[24]  S A Kulkarni,et al.  Integrated approach to assess the domain of applicability of some commercial (Q)SAR models , 2008, SAR and QSAR in environmental research.

[25]  R Posthumus,et al.  Validity and validation of expert (Q)SAR systems. , 2005, SAR and QSAR in environmental research.

[26]  N. Kruhlak,et al.  In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL QSAR software. , 2005, Regulatory toxicology and pharmacology : RTP.

[27]  Ronald D Snyder,et al.  DNA intercalative potential of marketed drugs testing positive in in vitro cytogenetics assays. , 2006, Mutation research.

[28]  R. Snyder,et al.  Toward a greater appreciation of noncovalent chemical/DNA interactions: Application of biological and computational approaches , 2005, Environmental and molecular mutagenesis.

[29]  R. Benigni Structure-activity relationship studies of chemical mutagens and carcinogens: mechanistic investigations and prediction approaches. , 2005, Chemical reviews.

[30]  Ann Thayer GENOTOXIC IMPURITIES: Faced with new guidelines that many find constraining, pharmaceutical manufacturers are seeking ways to avoid or reduce HARMFUL CONTAMINANTS in drugs , 2010 .

[31]  G. Klopman Artificial intelligence approach to structure-activity studies. Computer automated structure evaluation of biological activity of organic molecules , 1985 .

[32]  L. Hall,et al.  QSAR Modeling Based on Structure-Information for Properties of Interest in Human Health , 2005, SAR and QSAR in environmental research.

[33]  Ronald D Snyder,et al.  Computational prediction of genotoxicity: room for improvement. , 2005, Drug discovery today.

[34]  R Serafimova,et al.  Identification of the structural requirements for mutagencitiy, by incorporating molecular flexibility and metabolic activation of chemicals. II. General Ames mutagenicity model. , 2007, Chemical research in toxicology.

[35]  R. Didziapetris,et al.  Estimation of reliability of predictions and model applicability domain evaluation in the analysis of acute toxicity (LD 50) , 2010, SAR and QSAR in environmental research.

[36]  Romualdo Benigni,et al.  Predictivity and Reliability of QSAR Models: The Case of Mutagens and Carcinogens , 2008, Toxicology mechanisms and methods.

[37]  G Würtzen,et al.  Threshold of toxicological concern for chemical substances present in the diet. Report of a workshop, 5-6 October 1999, Paris, France. , 2001, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[38]  S. Vasanti,et al.  Impurity profile- A review , 2009 .

[39]  Mark Whittaker,et al.  An in Silico Method for Predicting Ames Activities of Primary Aromatic Amines by Calculating the Stabilities of Nitrenium Ions , 2010, J. Chem. Inf. Model..

[40]  R. Watkins,et al.  In silico assessment of toxicity of heat-generated food contaminants. , 2008, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[41]  R. Tennant,et al.  Chemical structure, Salmonella mutagenicity and extent of carcinogenicity as indicators of genotoxic carcinogenesis among 222 chemicals tested in rodents by the U.S. NCI/NTP. , 1988, Mutation research.

[42]  Custer Ll,et al.  The role of genetic toxicology in drug discovery and optimization. , 2008 .

[43]  G. Klopman MULTICASE 1. A Hierarchical Computer Automated Structure Evaluation Program , 1992 .

[44]  Remigijus Didziapetris,et al.  Trainable QSAR model of Ames genotoxicity , 2008 .

[45]  Paolo Mazzatorta,et al.  Integration of Structure-Activity Relationship and Artificial Intelligence Systems To Improve in Silico Prediction of Ames Test Mutagenicity , 2007, J. Chem. Inf. Model..

[46]  R Daniel Benz,et al.  Toxicological and clinical computational analysis and the US FDA/CDER , 2007, Expert opinion on drug metabolism & toxicology.

[47]  Ovanes Mekenyan,et al.  Identification of the structural requirements for mutagenicity by incorporating molecular flexibility and metabolic activation of chemicals I: TA100 model. , 2004, Chemical research in toxicology.

[48]  Erwin Annys The functioninq of SIEFs , 2009 .

[49]  Lapenna Silvia,et al.  The Applicability of Software Tools for Genotoxicity and Carcinogenicity Prediction: Case Studies relevant to the Assessment of Pesticides , 2010 .

[50]  Nigel Greene,et al.  The application of structure-based assessment to support safety and chemistry diligence to manage genotoxic impurities in active pharmaceutical ingredients during drug development. , 2006, Regulatory toxicology and pharmacology : RTP.

[51]  R Benigni,et al.  Understanding Genetic Toxicity Through Data Mining: The Process of Building Knowledge by Integrating Multiple Genetic Toxicity Databases , 2008, Toxicology mechanisms and methods.

[52]  S A Kulkarni,et al.  Influence of structural and functional modifications of selected genotoxic carcinogens on metabolism and mutagenicity – a review , 2007, SAR and QSAR in environmental research.

[53]  Romualdo Benigni,et al.  Structure alerts for carcinogenicity, and the Salmonella assay system: a novel insight through the chemical relational databases technology. , 2008, Mutation research.

[54]  A. Jacobs Prediction of 2-year carcinogenicity study results for pharmaceutical products: how are we doing? , 2005, Toxicological sciences : an official journal of the Society of Toxicology.

[55]  A. Bailey,et al.  The use of structure-activity relationship analysis in the food contact notification program. , 2005, Regulatory toxicology and pharmacology : RTP.

[56]  Romualdo Benigni,et al.  Prediction of the Rodent Carcinogenicity of 60 Pesticides by the DEREKfW Expert System , 2005, J. Chem. Inf. Model..

[57]  Romualdo Benigni,et al.  Predictivity of QSAR , 2008, J. Chem. Inf. Model..

[58]  Raghuraman Venkatapathy,et al.  Development of quantitative structure-activity relationship (QSAR) models to predict the carcinogenic potency of chemicals. II. Using oral slope factor as a measure of carcinogenic potency. , 2011, Regulatory toxicology and pharmacology : RTP.

[59]  Emilio Benfenati,et al.  The Expanding Role of Predictive Toxicology: An Update on the (Q)SAR Models for Mutagens and Carcinogens , 2007, Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews.

[60]  J. Kazius,et al.  Derivation and validation of toxicophores for mutagenicity prediction. , 2005, Journal of medicinal chemistry.

[61]  Akihiko Hirose,et al.  In silico assessment of chemical mutagenesis in comparison with results of Salmonella microsome assay on 909 chemicals. , 2005, Mutation research.

[62]  N. R. Rao,et al.  Pharmaceutical Impurities: An Overview , 2010 .

[63]  Romualdo Benigni,et al.  Structure-activity models of chemical carcinogens: state of the art, and new directions. , 2006, Annali dell'Istituto superiore di sanita.

[64]  R. Kroes Structure-Based Thresholds of Toxicological Concern (TTC): Guidance for Application to Substances Present at Low Levels in the Diet , 2004, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[65]  M. Cheeseman,et al.  Structure-activity relationship analysis tools: validation and applicability in predicting carcinogens. , 2008, Regulatory toxicology and pharmacology : RTP.

[66]  M Natália D S Cordeiro,et al.  A topological substructural molecular design approach for predicting mutagenesis end-points of alpha, beta-unsaturated carbonyl compounds. , 2010, Toxicology.

[67]  E. Miller,et al.  Mechanisms of chemical carcinogenesis , 1981, Cancer.

[68]  Joseph F Contrera,et al.  Improved in silico prediction of carcinogenic potency (TD50) and the risk specific dose (RSD) adjusted Threshold of Toxicological Concern (TTC) for genotoxic chemicals and pharmaceutical impurities. , 2011, Regulatory toxicology and pharmacology : RTP.

[69]  J. Ashby Fundamental structural alerts to potential carcinogenicity or noncarcinogenicity. , 1985, Environmental mutagenesis.

[70]  Joseph F Contrera,et al.  Genetic toxicity assessment: employing the best science for human safety evaluation. Part I: Early screening for potential human mutagens. , 2006, Toxicological sciences : an official journal of the Society of Toxicology.

[71]  Luis G Valerio,et al.  The in silico prediction of human-specific metabolites from hepatotoxic drugs. , 2010, Current drug discovery technologies.

[72]  Klaus-Robert Müller,et al.  Benchmark Data Set for in Silico Prediction of Ames Mutagenicity , 2009, J. Chem. Inf. Model..

[73]  K. Sweder,et al.  The role of genetic toxicology in drug discovery and optimization. , 2008, Current drug metabolism.

[74]  Vijay K Gombar,et al.  In silico approaches to predicting cancer potency for risk assessment of genotoxic impurities in drug substances. , 2010, Regulatory toxicology and pharmacology : RTP.

[75]  Edwin J Matthews,et al.  In silico approaches to explore toxicity end points: issues and concerns for estimating human health effects , 2007, Expert opinion on drug metabolism & toxicology.