Use of In Silico Methods for Regulatory Toxicological Assessment of Pharmaceutical Impurities.

The use of novel non-testing methodologies to support the toxicological assessment of drug impurities is having a growing impact in the regulatory framework for pharmaceutical development and marketed products. For DNA reactive (mutagenic) impurities specific recommendations for the use of in silico structure-based approaches (namely (Q)SAR methodologies) are provided in the ICH M7 guideline. In 2018 a draft reflection paper has been published by EMA addressing open issues in the qualification approach of non-genotoxic impurities (NGI) according to the ICH Q3A/Q3B guidelines, and proposing the use of alternative testing strategies, including TTC, (Q)SAR, read-across, and in vitro approaches, to gather impurity-specific safety information.

New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments.

To assess the impact of chemicals on an aquatic environment, toxicological data for three trophic levels are needed to address the chronic and acute toxicities. The use of non-testing methods, such as predictive computational models, was proposed to avoid or reduce the need for animal models and speed up the process when there are many substances to be tested. We developed predictive models for , , and fish for acute and chronic toxicities.

Prediction of the Partition Coefficient between Adipose Tissue and Blood for Environmental Chemicals: From Single QSAR Models to an Integrated Approach.

The adipose tissue:blood partition coefficient is a key-endpoint to predict the pharmacokinetics of chemicals in humans and animals, since other organ:blood affinities can be estimated as a function of this parameter. We performed a search in the literature to select all the available rat in vivo data. This approach resulted into two improvements to existing models: a homogeneous definition of the endpoint and an expanded data collection.

Ecosystem ecology: Models for acute toxicity of pesticides towards Daphnia magna.

Quantitative structure - activity relationships (QSARs) which are obtained with a representation of the molecular architecture via simplified molecular input-line entry system (SMILES) are applied to build up predictive models of acute toxicity of pesticides towards Daphnia magna. The acute toxicity towards Daphnia magna is an adequate measure of the ecological impact of various substances. The Monte Carlo technique is the basis to build up the above QSAR models.

CPANNatNIC software for counter-propagation neural network to assist in read-across.

Background: CPANNatNIC is software for development of counter-propagation artificial neural network models. Besides the interface for training of a new neural network it also provides an interface for visualisation of the results which was developed to aid in interpretation of the results and to use the program as a tool for read-across.

Results: The work presents the details of the program's interface.

Aquatic toxicity of several textile dye formulations: Acute and chronic assays with Daphnia magna and Raphidocelis subcapitata.

Dyes are widely used in various sectors and can be released into the environment where they persist for a long time because of their high stability to light or temperature and their resistance to environmental degradation. Dyes are often poorly characterized and toxicological/ecotoxicological data are available only for a few. These features, coupled with their toxicity, make dyes a possible source of ecological concern, particularly for freshwater aquatic ecosystems.

Integrated in silico strategy for PBT assessment and prioritization under REACH.

Chemicals may persist in the environment, bioaccumulate and be toxic for humans and wildlife, posing great concern. These three properties, persistence (P), bioaccumulation (B), and toxicity (T) are the key targets of the PBT-hazard assessment. The European regulation for the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) requires assessment of PBT-properties for all chemicals that are produced or imported in Europe in amounts exceeding 10 tonnes per year, checking whether the criteria set out in REACH Annex XIII are met, so the substance should therefore be considered to have properties of very high concern.

Evaluation of QSAR models for predicting the partition coefficient (log P) of chemicals under the REACH regulation.

The partition coefficient (log P) is a physicochemical parameter widely used in environmental and health sciences and is important in REACH and CLP regulations. In this regulatory context, the number of existing experimental data on log P is negligible compared to the number of chemicals for which it is necessary. There are many models to predict log P and we have selected a number of free programs to examine how they predict the log P of chemicals registered for REACH and to evaluate wheter they can be used in place of experimental data.

Validation of quantitative structure-activity relationship models to predict water-solubility of organic compounds.

Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.