Integrated decision-tree testing strategies for acute systemic toxicity and toxicokinetics with respect to the requirements of the EU REACH legislation

Quantitative Structure-Activity Relationship (QSAR) Studies on the Toxic Effects of Nitroaromatic Compounds (NACs): A Systematic Review

Nitroaromatic compounds (NACs) are ubiquitous in the environment due to their extensive industrial applications. The recalcitrance of NACs causes their arduous degradation, subsequently bringing about potential threats to human health and environmental safety. The problem of how to effectively predict the toxicity of NACs has drawn public concern over time. Quantitative structure-activity relationship (QSAR) is introduced as a cost-effective tool to quantitatively predict the toxicity of toxicants. Both OECD (Organization for Economic Co-operation and Development) and REACH (Registration, Evaluation and Authorization of Chemicals) legislation have promoted the use of QSAR as it can significantly reduce living animal testing. Although numerous QSAR studies have been conducted to evaluate the toxicity of NACs, systematic reviews related to the QSAR modeling of NACs toxicity are less reported. The purpose of this review is to provide a thorough summary of recent QSAR studies on the toxic effects of NACs according to the corresponding classes of toxic response endpoints.

A decision tree-based integrated testing strategy for tailor-made carcinogenicity evaluation of test substances using genotoxicity test results and chemical spaces

Genotoxicity evaluation has been widely used to estimate the carcinogenicity of test substances during safety evaluation. However, the latest strategies using genotoxicity tests give more weight to sensitivity; therefore, their accuracy has been very low. For precise carcinogenicity evaluation, we attempted to establish an integrated testing strategy for the tailor-made carcinogenicity evaluation of test materials, considering the relationships among genotoxicity test results (Ames, in vitro mammalian genotoxicity and in vivo micronucleus), carcinogenicity test results and chemical properties (molecular weight, logKow and 179 organic functional groups). By analyzing the toxicological information and chemical properties of 230 chemicals, including 184 carcinogens in the Carcinogenicity Genotoxicity eXperience database, a decision tree for carcinogenicity evaluation was optimised statistically. A decision forest model was generated using a machine-learning method-random forest-which comprises thousands of decision trees. As a result, balanced accuracies in cross-validation of the optimised decision tree and decision forest model, considering chemical space (71.5% and 75.5%, respectively), were higher than balanced accuracy of an example regulatory decision tree (54.1%). Moreover, the statistical optimisation of tree-based models revealed significant organic functional groups that would cause false prediction in standard genotoxicity tests and non-genotoxic carcinogenicity (e.g., organic amide and thioamide, saturated heterocyclic fragment and aryl halide). In vitro genotoxicity tests were the most important parameters in all models, even when in silico parameters were integrated. Although external validation is required, the findings of the integrated testing strategies established herein will contribute to precise carcinogenicity evaluation and to determine new mechanistic hypotheses of carcinogenicity.

QSAR and Classification Study on Prediction of Acute Oral Toxicity of N-Nitroso Compounds

To better understand the mechanism of in vivo toxicity of N-nitroso compounds (NNCs), the toxicity data of 80 NNCs related to their rat acute oral toxicity data (50% lethal dose concentration, LD50) were used to establish quantitative structure-activity relationship (QSAR) and classification models. Quantum chemistry methods calculated descriptors and Dragon descriptors were combined to describe the molecular information of all compounds. Genetic algorithm (GA) and multiple linear regression (MLR) analyses were combined to develop QSAR models. Fingerprints and machine learning methods were used to establish classification models. The quality and predictive performance of all established models were evaluated by internal and external validation techniques. The best GA-MLR-based QSAR model containing eight molecular descriptors was obtained with Q²loo = 0.7533, R² = 0.8071, Q²ext = 0.7041 and R²ext = 0.7195. The results derived from QSAR studies showed that the acute oral toxicity of NNCs mainly depends on three factors, namely, the polarizability, the ionization potential (IP) and the presence/absence and frequency of C⁻O bond. For classification studies, the best model was obtained using the MACCS keys fingerprint combined with artificial neural network (ANN) algorithm. The classification models suggested that several representative substructures, including nitrile, hetero N nonbasic, alkylchloride and amine-containing fragments are main contributors for the high toxicity of NNCs. Overall, the developed QSAR and classification models of the rat acute oral toxicity of NNCs showed satisfying predictive abilities. The results provide an insight into the understanding of the toxicity mechanism of NNCs in vivo, which might be used for a preliminary assessment of NNCs toxicity to mammals.

The virtual cell based assay: Current status and future perspectives

In order to replace the use of animals in toxicity testing, there is a need to predict in vivo toxic doses from concentrations that cause toxicological effects in relevant in vitro systems. The Virtual Cell Based Assay (VCBA) estimates time-dependent concentration of a test chemical in the cell and cell culture for a given in vitro system. The concentrations in the different compartments of the cell and test system are derived from ordinary differential equations, physicochemical parameters of the test chemical and properties of the cell line. The VCBA has been developed for a range of cell lines including BALB/c 3T3 cells, HepG2, HepaRG, lung A459 cells, and cardiomyocytes. The model can be used to design and refine in vitro experiments and extrapolate in vitro effective concentrations to in vivo doses that can be applied in risk assessment. In this paper, we first discuss potential applications of the VCBA: i) design of in vitro High Throughput Screening (HTS) experiments; ii) hazard identification (based on acute systemic toxicity); and iii) risk assessment. Further extension of the VCBA is discussed in the second part, exploring potential application to i) manufactured nanomaterials, ii) additional cell lines and endpoints, and considering iii) other opportunities.

•

VCBA as an alternative approach can be applied in the domain of nanotoxicology.

•

VCBA can support better testing strategies in acute toxicity.

•

Refinement of the VCBA taking into account biological oscillators could improve toxicity prediction.

•

Extensions of the VCBA can capture effects related to additional subcellular compartments.

Design of a testing strategy using non-animal based test methods: lessons learnt from the ACuteTox project

In the framework of toxicology, a testing strategy can be viewed as a series of steps which are taken to come to a final prediction about a characteristic of a compound under study. The testing strategy is performed as a single-step procedure, usually called a test battery, using simultaneously all information collected on different endpoints, or as tiered approach in which a decision tree is followed. Design of a testing strategy involves statistical considerations, such as the development of a statistical prediction model. During the EU FP6 ACuteTox project, several prediction models were proposed on the basis of statistical classification algorithms which we illustrate here. The final choice of testing strategies was not based on statistical considerations alone. However, without thorough statistical evaluations a testing strategy cannot be identified. We present here a number of observations made from the statistical viewpoint which relate to the development of testing strategies. The points we make were derived from problems we had to deal with during the evaluation of this large research project. A central issue during the development of a prediction model is the danger of overfitting. Procedures are presented to deal with this challenge.

The use of integrated and intelligent testing strategies in the prediction of toxic hazard and in risk assessment

There is increasing concern that insurmountable differences between humans and laboratory animals limit the relevance and reliability for hazard identification and risk assessment purposes of animal data produced by traditional toxicity test procedures. A way forward is offered by the emerging new technologies, which can be directly applied to human material or even to human beings themselves. This promises to revolutionise the evaluation of the safety of chemicals and chemical products of various kinds and, in particular, pharmaceuticals. The available and developing technologies are summarised and it is emphasised that they will need to be used selectively, in integrated and intelligent testing strategies, which, in addition to being scientifically sound, must be manageable and affordable. Examples are given of proposed testing strategies for general chemicals, cosmetic ingredients, candidate pharmaceuticals, inhaled substances, nanoparticles and neurotoxicity.

Anti-Oxidative Abilities of Essential Oils from Atractylodes ovata Rhizome

The rhizome of Atractylodes ovata De Candolle is rich in essential oils, which are usually removed by processing. In this study, anti-oxidative abilities of essential oils and aqueous extracts of A. ovata rhizome were explored, and the influence of processing on the anti-oxidative abilities was examined. Essential oils and aqueous extracts of A. ovata were extracted by boiling water and steam distillation, respectively. Quality of these two A. ovata samples was controlled by HPLC and GC-MS system, and anti-oxidative abilities were then evaluated. Results showed that surface color of A. ovata turned to brown and chemical components were changed by processing. Contents of both atractylon and atractylenolide II decreased in the essential oils, but only the contents of atractylon decreased by processing. Atractylenolide III increased in both A. ovata samples. However, A. ovata essential oils displayed stronger anti-oxidative abilities than aqueous extracts in DPPH-scavenging, TBH-induced lipid peroxidation and catalase activity assays. Moreover, the bioactivity of essential oils from raw A. ovata was stronger than oils from processed A. ovata. On the other hand, cytotoxicity of A. ovata essential oils was stronger than that of aqueous extracts, and was more sensitive on H9C2 cell than NIH-3T3 and WI-38 cells. In contrast, stir-frying processing method increased cytotoxicity of essential oils, but the cytotoxicity was ameliorated when processed with assistant substances. The results suggested that phytochemical components and bioactivity of A. ovata were changed after processing and the essential oils from raw A. ovata showed better anti-oxidative and fewer cytotoxicity effects.

ECVAM's ongoing activities in the area of acute oral toxicity

The 7th Amendment of the Cosmetics Directive (2003/15/EC) set up timelines for banning animal testing and marketing of cosmetic products and their ingredients tested on animals. For most of the human health effects, including acute toxicity, the deadline for these bans was in March 2009. Moreover, the new Regulation EC 1907/2006 on Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) provided a strong impetus towards the application of alternative approaches to reduce the number of animals used for toxicological testing. Therefore, the European Centre for the Validation of Alternative Methods (ECVAM) is currently putting considerable effort into developing and validating alternative methods in the field of acute toxicity. The main activities in this area include: (1) the Integrated Project ACuteTox, funded by the European Commission's 6th Framework Programme in 2005 with the aim to develop and pre-validate a testing strategy to fully replace acute oral toxicity testing in vivo; (2) a follow-up validation study to assess the predictive capacity of the validated BALB/3T3 Neutral Red Uptake cytotoxicity assay to discriminate between toxic/hazardous (LD(50)<2,000 mg/kg) substances and substances not classified for acute toxicity (LD(50)>2,000 mg/kg); (3) an approach to identify compounds with LD(50)>2,000 mg/kg using information from 28-days repeated dose toxicity studies.