Review of QSAR Models and Software Tools for Predicting of Genotoxicity and Carcinogenicity

This review of QSARs for genotoxicity and carcinogenicity was performed in a broad sense, considering both models available in software tools and models that are published in the literature. The review considered the potential applicability of diverse models to pesticides as well as to other types of regulated chemicals and pharmaceuticals. The availability of models and information on their applicability is summarised in tables, and a range of illustrative or informative examples are described in more detail in the text. In many cases, promising models were identified but they are still at the research stage. For routine application in a regulatory setting, further efforts will be needed to explore the applicability of such models for specific purposes, and to implement them in a practically useful form (i.e. user-friendly software). It is also noted that a range of software tools are research tools suitable for model development, and these require more specialised expertise than other tools that are aimed primarily at end-users such as risk assessors. It is concluded that the most useful models are those which are implemented in software tools and associated with transparent documentation on the model development and validation process. However, it is emphasised that the assessment of model predictions requires a reasonable amount of QSAR knowledge, even if it is not necessary to be a QSAR practitioner.JRC.DG.I.6-Systems toxicolog

Collection and Evaluation of (Q)SAR Models for Mutagenicity and Carcinogenicity

This evaluation of the non-commercial (Q)SARs for mutagenicity and carcinogenicity consisted of a preliminary survey (Phase I), and then of a more detailed analysis of short listed models (Phase II). In Phase I, the models were collected from the literature, and then assessed according to the OECD principles based on the information provided by the authors-. Phase I provided the support for short listing a number of promising models, that were analyzed more in depth in Phase II. In Phase II, the information provided by the authors was completed and complemented with a series of analyses aimed at generating an overall profile of each of the short listed models. The models can be divided into two families based on their target: a) congeneric; and b) non-congeneric sets of chemicals. The QSARs for congeneric chemicals include most of the chemical classes top ranking in the EU High Production Volume list, with the notable exception of the halogenated aliphatics. They almost exclusively aim at modeling Salmonella mutagenicity and rodent carcinogenicity, which are crucial toxicological endpoints in the regulatory context. The lack of models for in vivo genotoxicity should be remarked. Overall the short listed models can be interpreted mechanistically, and agree with, and/or support the available scientific knowledge, and most of the models have good statistics. Based on external prediction tests, the QSARs for the potency of congeneric chemicals are 30 to 70 % correct, whereas the models for discriminating between active and inactive chemicals have considerably higher accuracy (63 to 100 %), thus indicating that predicting intervals is more reliable than predicting individual data points. The internal validation procedures (e.g., cross-validation, etc...) did not seem to be a reliable measure of external predictivity. Among the non-local, or global approaches for non-congeneric data sets, four models based on the use of Structural Alerts (SA) were short listed and investigated in more depth. The four sets did not differ to a large extent in their performance. In the general databases of chemicals the SAs appear to agree around 65% with rodent carcinogenicity data, and 75% with Salmonella mutagenicity data. The SAs based models do not seem to work equally efficiently in the discrimination between active and inactive chemicals within individual chemical classes. Thus, their main role is that of preliminary, or large-scale screenings. A priority for future research on the SAs is their expansion to include alerts for nongenotoxic carcinogens. A general indication of this study, valid for both congeneric and noncongeneric models, is that there is uncertainty associated with (Q)SARs; the level of uncertainty has to be considered when using (Q)SAR in a regulatory context. However, (Q)SARs are not meant to be black-box machines for predictions, but have a much larger scope including organization and rationalization of data, contribution to highlight mechanisms of action, complementation of other data from different sources (e.g., experiments). Using only non-testing methods, the larger the evidence from QSARs (several different models, if available) and other approaches (e.g. chemical categories, read across) the higher the confidence in the prediction.JRC.I.3-Toxicology and chemical substance

Air Quality Monitoring, Assessment and Management

Human beings need to breathe oxygen diluted in certain quantity of inert gas for living. In the atmosphere, there is a gas mixture of, mainly, oxygen and nitrogen, in appropriate proportions. However, the air also contains other gases, vapours and aerosols that humans incorporate when breathing and whose composition and concentration vary spatially. Some of these are physiologically inert. Air pollution has become a problem of major concern in the last few decades as it has caused negative effects on human health, nature and properties. This book presents the results of research studies carried out by international researchers in seventeen chapters which can be grouped into two main sections: a) air quality monitoring and b) air quality assessment and management, and serves as a source of material for all those involved in the field, whether as a student, scientific researcher, industrialist, consultant, or government agency with responsibility in this area

Screening, quantitative Analyse und Toxikologie organischer Verbindungen in Sedimenten und Schwebstoffen der Saar und des Rheins (Deutschland)

River sediments and suspended particulate matter (SPM) are sinks as well as secondary sources for nonpolar organic compounds that might pose a risk to aquatic ecosystems’ goods and services. Sources of these pollutants are for example wastewater treatment plants effluents or direct discharges as well as dry and wet atmospheric deposition. Surface run-off of contaminated soils and dust from streets are other important origins. The particularly bound substances with different physical and chemical properties are constrained to partitioning processes between the solids and the water phase. Hence, they might get bioavailable and thus pose an ecotoxicological risk for water organisms. During flood events, contaminated sediments could be remobilized and transported to riparian lands. Consequently, there are concerns regarding risks for terrestrial ecosystems’ goods and services. In the first part of this thesis, sediments and SPM samples of the Saar and the Rhine were investigated regarding organic compounds using target, suspect and nontarget screening analysis with gas chromatography – mass spectrometry (GC-MS). Sediment core and suspended particulate matter samples were collected at representative sampling sites along the both rivers. This study was conducted, among other things, to improve information regarding nonprioritized organic compounds in sediments and suspended particulate matter of the Saar and the Rhine. In the second part, the extractability and potential toxicity of particularly bound organic compounds was investigated. Sediment samples from the Saar as well as the Elbe and the Bílina in Czech Republic was extracted with different exhaustive and biomimetic extraction approaches. Soxhlet, ultrasonic and accelerated solvent extraction as well as membrane dialysis extraction were used as exhaustive methods. Extractions with Tenax®-TA as well as mixtures of water with methanol or 2-hydroxypropyl-β-cyclodextrin were applied as biomimetic approaches. The main objective of these investigations was the generation of comprehensive knowledge concerning the relationship between the physical-chemical properties of compounds and sediments as well as extractability and resulting toxicity. Recommendations for the integrated risk assessment of sediments including exhaustive extraction as well as biomimetic methods and dosing were compiled. In the third part, potentially adverse effects of contaminated sediments and SPM for riparian lands were investigated. A main aim was the investigation of two exposition pathways in the contact tests – native sediment versus acetonic extract. Effect-directed analysis was used to examine selected soil and SPM samples regarding effect potentials in vitro and to unravel responsible compound classes or substances, respectively.Fluviale Sedimente und Schwebstoffe bilden sowohl eine Senke als auch eine sekundäre Quelle für hydrophobe organische Verbindungen mit ökotoxikologischem Potential. Der Eintrag dieser Substanzen in die Gewässer erfolgt beispielsweise durch Klär- und Direkteinleitung, trockene und nasse atmosphärische Deposition, oder den Eintrag von Bodenpartikeln und Oberflächenabfluss bei Niederschlagsereignissen. Die partikulär gebundenen Stoffe mit unterschiedlichen physiko-chemischen Eigenschaften können aufgrund von Verteilungsprozessen zwischen Sediment bzw. Schwebstoff und der Wasserphase für Wasserorganismen verfügbar werden und bilden damit ein ökotoxikologisches Gefährdungspotential. Während Flutereignissen besteht die Gefahr, dass belastete Sedimente remobilisiert und diese in Auengebiete eingetragen werden, somit die Besorgnis einer Gefährdung terrestrischer Schutzgüter besteht. Der erste Teil der vorliegenden Arbeit befasst sich mit der chemischen Analyse und Identifizierung von organischen Verbindungen in Sedimenten und Schwebstoffen des Rheins und der Saar. An verschiedenen repräsentativen Standorten des Rheins und der Saar wurden Sedimentkerne mit einem Gefrierkernverfahren bzw. einem Kernstechverfahren sowie Schwebstoffe gewonnen. Diese Studie wurde unter anderem durchgeführt, um die Datenlage hinsichtlich nichtregulierter organischer Substanzen in Sedimenten und Schwebstoffen der Saar und des Rheins zu verbessern. Der zweite Teil dieser Arbeit umfasste die Frage nach der Extrahierbarkeit und potentiellen Toxizität partikulär gebundener organischer Verbindungen. Sedimentproben wurden mit unterschiedlichen erschöpfenden und nichterschöpfenden Extraktionsverfahren (Soxhlet-, Ultraschall- und Beschleunigte Lösungsmittelextraktion, Membran- Dialyse-Extraktion sowie Extraktion mit dem Polymer TENAX®-TA und Methanol- bzw. 2-Hydroxypropyl-β-Cyclodextrin-Wassergemischen). Das Ziel dieser Untersuchung war es unter der Anwendung chemischer und bioanalytischer Methoden neue Erkenntnisse zum Zusammenhang zwischen Extrahierbarkeit, Stoff- und Sedimenteigenschaften und resultierender Sedimenttoxizität zu erlangen. Aus den Ergebnissen wurden Empfehlungen für eine umfassende Risikobewertung von Sedimenten unter der Berücksichtigung von Verfahren zur Bestimmung des bioverfügbaren Anteils abgeleitet sowie weiterer Forschungsbedarf aufgezeigt. Der dritte Teil dieser Abhandlung untersucht potentielle adverse Effekte des Eintrages von Schwebstoffen und remobilierten Sedimenten des Rheins in ein Auengebiet am Oberrhein. Ein wichtiger Aspekt war die Untersuchung unterschiedlicher Expositionspfade in Sediment- bzw. Bodenkontakttests (natives Sediment versus acetonischer Extrakt). Desweiteren wurden ausgewählte Proben einer wirkungsorientierten Analytik unterzogen um biologische Effekte in vitro zu untersuchen sowie für die Effekte verantwortlichen Substanzklassen bzw. Verbindungen zu identifizieren

Source apportiment, multimedia fate, key emmission sectors and global health impacts of polycyclic aromatic hydrocarbons

Polyzyklische aromatische Kohlenwasserstoffe (PAK) sind eine Klasse krebserregender Schadstoffe. Aufgrund ihres weit verbreiteten Vorkommens und der toxischen Risiken für die menschliche Gesundheit und das Ökosystem ist es unerlässlich, durch systematische Forschung wirksame Minderungsstrategien auf verschiedenen Ebenen zu etablieren. In dieser Dissertation wurden Quellenzuordnung, Multimedia-Schicksal, Schlüsselemis-sionssektoren und globale gesundheitliche Auswirkungen von PAK-Belastungen unter-sucht. Diese Forschung wurde durchgeführt, um Daten zur Verfügung zu stellen, die po-tenzielle Minderungsstrategien unterstützen, um PAK-Verschmutzungen und damit ver-bundene gesundheitliche Auswirkungen auf regionaler, nationaler und globaler Ebene zu reduzieren. Zunächst wurde die Quellenzuordnung von Langzeit-PAH in acht Flüssen untersucht. Diese Studie untersuchte systematisch die zeitlichen und saisonalen Trends, die peri-odische Oszillation, die Quellenzuordnung und die Risikobewertung von PAKs für die menschliche Gesundheit in acht Flüssen, die eine quellenorientierte PAK-Minderung in der Region unterstützen können. Zweitens ist das Multimedia-Schicksal von PAKs entscheidend für eine bessere Umwelt-politik. Diese Studie bewertete systematisch die räumlich-zeitliche Verteilung, die Quellenzuordnung, den multimedialen Transport und den Verbleib von PAK, die an Schwebstaub (SPM) in Rhein und Elbe adsorbiert sind, was die Stadtplanung unterstützen kann, um PAK in den Regionen zu lindern. Drittens wurden in dieser Studie die wichtigsten Emissionssektoren von PAK bestimmt, indem die langfristigen verkörperten und ermöglichten PAK-Emissionen in verschiedenen Sektoren abgeschätzt und die Beiträge sozioökonomischer Determinanten quantifiziert wurden. Die Ergebnisse können wirksame Strategien zur Verringerung der PAK-Emissionen in verschiedenen Sektoren aus der Perspektive des Endverbrauchs und des primären Inputverhaltens auf nationaler Ebene unterstützen. Schließlich wurden in dieser Studie die globalen Triebkräfte der gesundheitlichen Auswir-kungen von PAH untersucht, indem ein integrierender Rahmen angewendet wurde, der das globale PAH-Emissionsinventar, das um die Umwelt erweiterte multiregionale Input-Output-Modell, das GEOS-Chem-Chemikalientransportmodell und das lebenslange Lung-enkrebsrisiko verknüpfte Bewertung und Analyse der Strukturzerlegung. Die Ergebnisse können politische Entscheidungen zur Optimierung von Minderungsstrategien aus verschiedenen Perspektiven unterstützen, um PAK-Emissionen und gesundheitliche Aus-wirkungen weltweit effektiv zu reduzieren.Polycyclic aromatic hydrocarbons (PAHs) are a class of carcinogenic pollutants. Due to their widespread occurrence and toxic risks to human health and ecosystem, it is essen-tial to establish effective mitigation strategies at different scales through systematic re-search. In this dissertation, source apportionment, multimedia fate, key emission sectors and global health impacts of PAH pollutions have been investigated. This research was conducted to provide data to assist potential mitigation strategies to reduce PAH pollu-tions and related health impacts at regional, national, and global scales. Firstly, the source apportionment of long-term PAHs in eight rivers were investigated. This study systematically investigated the temporal and seasonal trends, periodic oscilla-tion, source apportionment, and human health risk assessment of PAHs in eight rivers, which can assist source-oriented PAH mitigation in the region. Secondly, the multimedia fate of PAHs is critical for achieving better environmental poli-cies. This study systematically evaluated the spatiotemporal distribution, source appor-tionment, multimedia transport and fate of PAHs adsorbed on suspended particulate matter (SPM) in Rhine and Elbe Rivers, which can assist urban planning to alleviate PAHs in the regions. Thirdly, the key emission sectors of PAHs were determined in this study through estimat-ing the long-term embodied and enabled PAH emissions in various sectors and quantify-ing the contributions of socioeconomic determinants. The results can assist effective strategies for mitigating PAH emissions in different sectors from the perspectives of final consumption and primary input behaviors at a national scale. Finally, the global driving forces of PAH health impacts were investigated in this study through applying an integrating framework, linking global PAH emission inventory, envi-ronmentally extended multi-regional input-output model, GEOS-Chem chemical transport model, lifetime lung cancer risk assessment, and structure decomposition analysis. The results can assist policy decisions to optimize mitigation strategies from different per-spectives for effectively reducing PAH emissions and health impacts in the world

Integration of Toxicity Data from Experiments and Non-Testing Methods within a Weight of Evidence Procedure

Assessment of human health and environmental risk is based on multiple sources of information, requiring the integration of the lines of evidence in order to reach a conclusion. There is an increasing need for data to fill the gaps and new methods for the data integration. From a regulatory point of view, risk assessors take advantage of all the available data by means of weight of evidence (WOE) and expert judgement approaches to develop conclusions about the risk posed by chemicals and also nanoparticles. The integration of the physico-chemical properties and toxicological effects shed light on relationships between the molecular properties and biological effects, leading us to non-testing methods. (Quantitative) structure-activity relationship ((Q)SAR) and read-across are examples of non-testing methods. In this dissertation, (i) two new structure-based carcinogenicity models, (ii) ToxDelta, a new read-across model for mutagenicity endpoint and (iii) a genotoxicity model for the metal oxide nanoparticles are introduced. Within the latter section, best professional judgement method is employed for the selection of reliable data from scientific publications to develop a data base of nanomaterials with their genotoxicity effect. We developed a decision tree model for the classification of these nanomaterials. The (Q)SAR models used in qualitative WOE approaches mainly lack transparency resulting in risk estimates needing quantified uncertainties. Our two structure-based carcinogenicity models, provide transparent reasoning in their predictions. Additionally, ToxDelta provides better supported techniques in read-across terms based on the analysis of the differences of the molecules structures. We propose a basic qualitative WOE framework that couples the in silico models predictions with the inspections of the similar compounds. We demonstrate the application of this framework to two realistic case studies, and discuss how to deal with different and sometimes conflicting data obtained from various in silico models in qualitative WOE terms to facilitate structured and transparent development of answers to scientific questions

The prediction of mutagenicity and pKa for pharmaceutically relevant compounds using 'quantum chemical topology' descriptors

Quantum Chemical Topology (QCT) descriptors, calculated from ab initio wave functions, have been utilised to model pKa and mutagenicity for data sets of pharmaceutically relevant compounds. The pKa of a compound is a pivotal property in both life science and chemistry since the propensity of a compound to donate or accept a proton is fundamental to understanding chemical and biological processes. The prediction of mutagenicity, specifically as determined by the Ames test, is important to aid medicinal chemists select compounds avoiding this potential pitfall in drug design. Carbocyclic and heterocyclic aromatic amines were chosen because this compounds class is synthetically very useful but also prone to positive outcomes in the battery of genotoxicity assays.The importance of pKa and genotoxic characteristics cannot be overestimated in drug design, where the multivariate optimisations of properties that influence the Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) profiles now features very early on in the drug discovery process.Models were constructed using carboxylic acids in conjunction with the Quantum Topological Molecular Similarity (QTMS) method. The models produced Root Mean Square Error of Prediction (RMSEP) values of less than 0.5 pKa units and compared favourably to other pKa prediction methods. The ortho-substituted benzoic acids had the largest RMSEP which was significantly improved by splitting the compounds into high-correlation subsets. For these subsets, single-term equations containing one ab initio bond length were able to accurately predict pKa. The pKa prediction equations were extended to phenols and anilines.Quantitative Structure Activity Relationship (QSAR) models of acceptable quality were built based on literature data to predict the mutagenic potency (LogMP) of carbo- and heterocyclic aromatic amines using QTMS. However, these models failed to predict Ames test values for compounds screened at GSK. Contradictory internal and external data for several compounds motivated us to determine the fidelity of the Ames test for this compound class. The systematic investigation involved recrystallisation to purify compounds, analytical methods to measure the purity and finally comparative Ames testing. Unexpectedly, the Ames test results were very reproducible when 14 representative repurified molecules were tested as the freebase and the hydrochloride salt in two different solvents (water and DMSO). This work formed the basis for the analysis of Ames data at GSK and a systematic Ames testing programme for aromatic amines. So far, an unprecedentedly large list of 400 compounds has been made available to guide medicinal chemists. We constructed a model for the subset of 100 meta-/para-substituted anilines that could predict 70% of the Ames classifications. The experimental values of several of the model outliers appeared questionable after closer inspection and three of these have been retested so far. The retests lead to the reclassification of two of them and thereby to improved model accuracy of 78%. This demonstrates the power of the iterative process of model building, critical analysis of experimental data, retesting outliers and rebuilding the model.EThOS - Electronic Theses Online ServiceEPSRCGlaxoSmithKlineGBUnited Kingdo