Identification and Description of the Uncertainty, Variability, Bias and Influence in Quantitative Structure-Activity Relationships (QSARs) for Toxicity Prediction

Improving regulatory confidence in, and acceptance of, a prediction of toxicity from a quantitative structure-activity relationship (QSAR) requires assessment of its uncertainty and determination of whether the uncertainty is acceptable. Thus, it is crucial to identify potential uncertainties fundamental to QSAR predictions. Based on expert review, sources of uncertainties, variabilities and biases, as well as areas of influence in QSARs for toxicity prediction were established. These were grouped into three thematic areas: uncertainties, variabilities, potential biases and influences associated with 1) the creation of the QSAR, 2) the description of the QSAR, and 3) the application of the QSAR, also showing barriers for their use. Each thematic area was divided into a total of 13 main areas of concern with 49 assessment criteria covering all aspects of QSAR development, documentation and use. Two case studies were undertaken on different types of QSARs that demonstrated the applicability of the assessment criteria to identify potential weaknesses in the use of a QSAR for a specific purpose such that they may be addressed and mitigation strategies can be proposed, as well as enabling an informed decision on the adequacy of the model in the considered context

In silico toxicology protocols

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

Speciation analysis of protein-bound elements in cytosols as biological markers for metabolic processes with special emphasis on metallothioneins in the brain

Bei der Aufklärung der Rolle von Spurenelementen in komplexen physiologischen oder pathologischen Stoffwechselvorgängen erlaubt die Speziationsanalyse tiefere Einblicke in die im Organismus ablaufenden Prozesse als die Bestimmung von Gesamtelementgehalten. In der vorliegenden Arbeit wurden die an unterschiedliche Proteine im Cytosol von menschlichen Geweben gebundenen Elemente untersucht. Im Vordergrund standen dabei die Metallothioneine (MT) - niedermolekulare, cysteinreiche, metallbindende Proteine, welche als an zahlreichen vitalen Stoffwechselprozessen beteiligt angesehen werden. Die Isoform MT-3 wurde vor allem im Gehirn gefunden und seit ihrer Entdeckung in Zusammenhang mit Morbus Alzheimer (AD) diskutiert. Zur Speziationsanalyse wurden Verbundverfahren aus chromatographischer bzw. kapillarelektrophoretischer Trennung der Biomoleküle und on-line gekoppelter Elementdetektion mittels Plasmamassenspektrometrie (ICP-MS) eingesetzt. Die Abtrennung des MT-3 von den anderen Isoformen war dabei für eine gesonderte Betrachtung wichtig. Die einzelnen Signale wurden verschiedenen Proteinen mittels spezifischer Nachweise im Eluat der Trennungen zugeordnet. Die Identität des MT-3-Peaks konnte sicher bestätigt werden. Neben der Größenausschlußchromatographie wurden weitere Trennverfahren verwendet, welche je nach dem Ziel der durchzuführenden Untersuchung ausgewählt werden müssen. In Kooperation mit dem GKSS Forschungszentrum, Geesthacht, wurde die dort entwickelte Kapillarzonenelektrophorese-ICP-MS-Kopplung für die Anwendung auf komplexe biologische Proben optimiert. Auftretende Probleme der Vergleichbarkeit von Signalen durch Variationen der Migrationszeiten wurden durch eine rechnerische Anpassung der Zeitachsen mittels mitlaufender Markersubstanzen gelöst. Zusätzliche Informationen wurden durch die Hintereinanderschaltung unterschiedlicher Trennmethoden erhalten. Die Betrachtung der Elementprofile von verschiedenen Organen bestätigte die Hypothese, daß unterschiedliche Organe mit auf unterschiedliche Aufgaben spezialisierten Zellarten auch verschiedene Metalloprotein-Zusammensetzungen aufweisen. Die Verteilung der proteingebundenen Elemente in einem Organ von verschiedenen Patienten zeigte ebenfalls deutliche, auf unterschiedliche pathologische Prozesse zurückzuführende Unterschiede. Um die in der Literatur uneinheitlichen Angaben zur Metallbeladung von MT-3 zu klären, wurde in einem Projekt am Center for Biochemical and Biophysical Sciences and Medicine an der Harvard Medical School, Boston, natives MT-3 aus Schweinegehirn untersucht. Es zeigte sich, daß im Cytosol mehrere, nicht trennbare Formen von MT-3 existieren, wobei es sich wahrscheinlich um unterschiedliche Metallbeladungen handelt, welche auch vom individuellen physiologischen Zustand abhängen. Die Betrachtung eines größeren Probenkollektives ist demnach aussagekräftiger. Bei der Untersuchung eines Kollektives von AD- und Kontroll-Gehirnproben wurde ein signifikanter Unterschied von Elementgehalten in weißer und grauer Masse, jedoch nicht zwischen AD- und Kontrollproben gefunden. Das Hauptaugenmerk lag auf dem Vergleich der MT-Signale in den Elementprofilen, wobei die wenig variierenden Signale der Superoxid Dismutase sich als nützlicher Bezugspunkt erwiesen. Die MT-Metall-Signale waren bei den AD-Proben niedriger. Es zeigte sich jedoch, daß der größere Anteil an oxidierten MT im Cytosol der AD-Gehirne ein entscheidenderer Unterschied zu den Kontrollen war. Dies wies auf verstärkte oxidative Prozesse im Laufe der Erkrankung hin

Integration of alternative methods for an ab initio chemical safety assessment

Assessing chemical safety using only non-animal methods is a major challenge within the European Union, especially considering the ban to market cosmetics with ingredients tested on animals (Regulation 1223/2009). One of the outcomes of the SEURAT-1 initiative (http://www.seurat-1.eu/), co-sponsored by the European Commission 7thFP and Cosmetics Europe, was to develop case studies addressing that issue. Besides a read-across case-study, where "new approach" data was used to strengthen the confidence in reading across data from an already assessed chemical to a structural analogue, an ab initio case study was carried out and is presented here. The ab initio case study was an attempt to structure knowledge and data in a logic workflow which could be used for decision making to predict whether the intended exposure could be considered safe based on data solely from alternative methods. The workflow is includes the following steps: i) identification of the exposure/use scenario; ii) data collection on the chemical; iii) toxicokinetic and toxicodynamic modeling; iv) evaluation of other alternative methods (in vitro or in silico) which are available and could provide evidence for a hypothesis on the chemicals' mode of action; v) confirmation of the hypothesis with targeted testing using selected in vitro or in silico methods; vi) propose a risk valuation, as well as estimating uncertainties and identifying data gaps. The exposure scenario is an initial and essential step in this workflow. Whether exposure is intentional or not it should be considered, and in both cases estimates of the doses, expected routes of exposure, frequency and length of exposure should be made. The ab initio workflow was applied to the piperonyl butoxide (PBO), as a hypothetical case, for which the mode-of-action was assumed to be unknown. The only data on the compound was the molecular structure and a concentration of PBO in a consumer product formulation. An exposure scenario was set up and data were generated for simulation of internal exposure for a “healthy human” using PBPK modeling. The concentration in blood and liver predicted by the model were then used to design in vitro tests (performed by SEURAT-1 partners). The test results were then evaluated and used to estimate whether PBO would be safe to use for the selected exposure scenario. To our knowledge, the SEURAT-1 ab initio case study is a first attempt to shift our minds to a fully non-animal based chemical risk assessment relying only on alternative methods

Ab Initio safety assessment case study : Integration of alternative methods in an applied risk assessment for repeated-dose toxicity

The SEURAT-1 ("Safety Evaluation Ultimately Replacing Animal Testing") Research Initiative aimed at finding alternative approaches for the safety assessment for repeated-dose toxicity (Gocht et al 2013). Within the SEURAT-1 framework of proof-of-concept case studies for applied safety assessment, the ab initio case study set out to identify and subsequently quantify relevant biological pathway concentration effect levels of a cosmetic ingredient for specific exposure scenarios. Based on the SEURAT-1 conceptual framework for safety assessment (White, Knight 2014), a general workflow was developed in an attempt to structuring knowledge and data in a logical sequence for an integrated safety assessment relying specifically on alternative methods. Considerations included the possible application of the Threshold of Toxicological Concern (TTC) approach and read-across assessment. Physiologically-based pharmacokinetic modelling was applied to identify target organs and internal concentrations. In silico structural alerts and QSAR profilers as well as in vitro information including high throughput assays were used to build a weight of evidence, based on an AOP-anchored mode-of-action hypothesis and supported by in vitro to in vivo extrapolation (IVIVE) modelling and refinement, with the aim of concluding on the safety of use regarding repeated-dose toxicity, focusing on liver toxicity. Piperonyl butoxide (PBO) was selected to illustrate the case study in fictional exposure scenarios as a new ingredient introduced in a shampoo and a daily applied body lotion. The supportive alternative data (in vitro and in silico) were generated in the SEURAT-1 projects or obtained from ToxCast. The case study focusing on alternative approaches highlights the challenge in integrating multiple data streams for safety assessment decisions, points out knowledge gaps and proposes a way forward

COSMOS : An International Cooperative Project Developing Computational Models for Repeated Dose Toxicity

The COSMOS (Integrated In Silico Models for the Prediction of Human Repeated Dose Toxicity of COSMetics to Optimise Safety) Project is a unique international collaboration developing computational approaches for the prediction of repeated dose toxicity. The project comprises 15 partners from academia, industry, regulatory agencies and SMEs from across Europe and the US. Moreover, COSMOS is part of a cluster of six research projects within the SEURAT-1 (Safety Evaluation Ultimately Replacing Animal Testing) Research Initiative. Organ level toxicity involves complex mechanisms, thus it cannot be predicted by a single simplified in silico model. Therefore COSMOS is taking an innovative approach integrating different technologies, e.g. the threshold of toxicological concern approach, grouping of chemicals, (Q)SARs for toxicity prediction and modelling of biokinetics. All are being developed with a special emphasis on the mechanistic basis of the models considered. Computational workflows as well as a new comprehensive database with reliable structures and repeated dose toxicity data will be freely available to support safety assessment without the use of animals and will thus contribute to the 3Rs. The international dimension is important for the development and especially regulatory acceptance of the models proposed, the international companies having to assure the safety of their products on a global scale. Therefore industry, regulatory agencies and NGOs in Europe and the US are involved either as project partners or as external experts

Computational chemistry solutions supporting chemical safety assessment: Lessons learned for using in silico approaches

Computational methods have become increasingly important for evaluating consumer safety to chemicals. Approaches to predict complex endpoints such as chronic toxicity require a robust mechanistic basis, such as anchoring to relevant Adverse Outcome Pathways (AOPs). The EU COSMOS Project (www.cosmostox.eu) within the SEURAT-1 cluster of projects (www.seurat-1.eu) has developed computational in silico tools to support safety assessment for repeated dose toxicity for cosmetics-related substances. A number of fundamental issues for computational toxicology have been identified from the COSMOS Project which can be applied beyond the field of cosmetics: (1) Knowledge creation requires high quality data. A well curated database associated with highly defined chemical structures has been created in the freely available COSMOS Database (http://cosmosdb.cosmostox.eu). Importantly, it provides not only access to existing test data, but can facilitate the creation of new knowledge through data mining, e.g. new chemotypes for organ level toxicity and the development of thresholds of toxicological concern. (2) Biokinetic processes must be taken into account. Biokinetic models are essential to extrapolate from in vitro experiments to in vivo target organ concentrations (IVIVE) and in vivo bioavailability. Physiologically based kinetic (PBK) models can assist in extrapolating route-to-route exposures. (3) Established modelling techniques can be modified for use in risk assessment. Molecular modelling approaches, from drug discovery, have been successfully transferred to predictive toxicology, changing from hit identification with a minimum of false positives to screening chemicals to evaluate potential effects with a minimum of false negatives. (4) It is essential to make models easily accessible and usable. To facilitate the uptake of computational modelling methods, COSMOS models were implemented in a user-friendly, transparent and freely available form as KNIME workflows. In this way they are useful to support safety assessment, not as black box software approaches, but also available for adaption to the specific applications. The funding from the European Community's 7th Framework Program (FP7/2007-2013) COSMOS Project (Grant Agreement N° 266835) and Cosmetics Europe is gratefully acknowledged

New computational approaches for repeated dose toxicity prediction in view of the safety assessment of cosmetic ingredients

Since the full EU ban of marketing cosmetics containing ingredients tested on animals entered into force on 11 March 2013, alternatives have become necessary to evaluate the consumer safety of cosmetics. The EU COSMOS Project within the SEURAT-1 Research Initiative is developing computational modelling approaches, focusing on repeated dose toxicity, to support the safety assessment of cosmetics-related chemicals, without relying on animal testing. Efficient storage of relevant information in flexibly searchable databases is needed to allow for development of structure-based models for toxicity prediction. A comprehensive database has been developed and made publicly available (COSMOS DB ver1.0; http://cosmosdb. cosmostox. eu). It includes an inventory of over 5,500 cosmetics-related substances with high quality structures linked to data compiled from over 12,000 toxicological studies for over 1,660 compounds with data across 27 endpoints, including in vitro and in vivo genetic toxicity and oral repeated dose toxicity. Based on a new oral repeated-dose toxicity database within COSMOS DB, a new COSMOS non-cancer TTC database has been established enriched by cosmetic ingredients. This has been developed to evaluate the potential of applying the threshold of toxicological concern (TTC) concept to risk assessment of cosmetics, with particular consideration given to the dermal route of exposure. Moreover, grouping approaches for toxicity prediction have been developed and applied, e.g. for hair dyes. Data mining of the oRepeatTox DB has identified structural fragments capable of inducing hepatotoxicity (steatosis/steatohepatitis/fibrosis). This knowledge has been captured in the form of “chemotypes” relevant for liver toxicity of cosmetics-related chemicals. The studies were supported by molecular modelling to predict binding to two nuclear receptors (LXR and PPARy) considered to be involved in steatosis. Elucidating the mechanisms underlying toxic events can be used to inform the development of Adverse Outcome Pathways. In order to support oral-to-dermal extrapolation a new database of skin permeability values has been developed along with QSAR models for dermal absorption, skin and liver metabolism and hepatic clearance. Furthermore, to support in vitro to in vivo extrapolations, physiologically-based toxicokinetic (PBTK) models have been developed and calibrated. Combined with cell based assays, incorporating aspects of chemical fate, cell growth, toxicity and feedback, they enable realistic estimates of in vivo concentration at the organ level to be extrapolated from in vitro data. COSMOS models are being coded using open access KNIME workflow software. Workflows can be executed from locally installed KNIME software or via a web browser using the KNIME WebPortal (http://knimewebportal.cosmostox.eu)