Kim Z. Travis

Pharmacokinetic, Neurochemical, Stereological and Neuropathological Studies on the Potential Effects of Paraquat in the Substantia Nigra Pars Compacta and Striatum of Male C57BL/6J Mice

The pharmacokinetics and neurotoxicity of paraquat dichloride (PQ) were assessed following once weekly administration to C57BL/6J male mice by intraperitoneal injection for 1, 2 or 3 weeks at doses of 10, 15 or 25 mg/kg/week. Approximately 0.3% of the administered dose was taken up by the brain and was slowly eliminated, with a half-life of approximately 3 weeks. PQ did not alter the concentration of dopamine (DA), homovanillic acid (HVA) or 3,4-dihydroxyphenylacetic acid (DOPAC), or increase dopamine turnover in the striatum. There was inconsistent stereological evidence of a loss of DA neurons, as identified by chromogenic or fluorescent-tagged antibodies to tyrosine hydroxylase in the substantia nigra pars compacta (SNpc). There was no evidence that PQ induced neuronal degeneration in the SNpc or degenerating neuronal processes in the striatum, as indicated by the absence of uptake of silver stain or reduced immunolabeling of tyrosine-hydroxylase-positive (TH(+)) neurons. There was no evidence of apoptotic cell death, which was evaluated using TUNEL or caspase 3 assays. Microglia (IBA-1 immunoreactivity) and astrocytes (GFAP immunoreactivity) were not activated in PQ-treated mice 4, 8, 16, 24, 48, 96 or 168 h after 1, 2 or 3 doses of PQ. In contrast, mice dosed with the positive control substance, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP; 10mg/kg/dose×4 doses, 2 h apart), displayed significantly reduced DA and DOPAC concentrations and increased DA turnover in the striatum 7 days after dosing. The number of TH(+) neurons in the SNpc was reduced, and there were increased numbers of degenerating neurons and neuronal processes in the SNpc and striatum. MPTP-mediated cell death was not attributed to apoptosis. MPTP activated microglia and astrocytes within 4 h of the last dose, reaching a peak within 48 h. The microglial response ended by 96 h in the SNpc, but the astrocytic response continued through 168 h in the striatum. These results bring into question previous published stereological studies that report loss of TH(+) neurons in the SNpc of PQ-treated mice. This study also suggests that even if the reduction in TH(+) neurons reported by others occurs in PQ-treated mice, this apparent phenotypic change is unaccompanied by neuronal cell death or by modification of dopamine levels in the striatum.

Application of toxicokinetics to improve chemical risk assessment: implications for the use of animals.

While toxicokinetics has become an integral part of pharmaceutical safety assessment over the last two decades, its use in the chemical industry is relatively new. However, it is recognised as a potentially important tool in human health risk assessment and recent initiatives have advocated greater application of toxicokinetics as part of an improved assessment strategy for crop protection chemicals that could offer greater efficiency, use fewer animals and provide better data for risk assessment purposes. To explore the potential scientific and animal welfare benefits of increased use of toxicokinetic data across the chemical industry, an international workshop was held in 2008. Experts from a wide range of chemical industry sectors, including industrial chemicals, agrochemicals and consumer products, participated in the meeting as well as representatives from relevant regulatory authorities. Pharmaceutical industry experts were also invited, in order to share experiences from the extensive use of toxicokinetics in drug development. Given that increased generation of toxicokinetic data could potentially result in an increased number of animals undergoing testing, technologies and strategies to reduce and refine animal use for this purpose were also considered. This paper outlines and expands upon the key themes that emerged from the workshop.

Data governance in predictive toxicology: A review.

BackgroundDue to recent advances in data storage and sharing for further data processing in predictive toxicology, there is an increasing need for flexible data representations, secure and consistent data curation and automated data quality checking. Toxicity prediction involves multidisciplinary data. There are hundreds of collections of chemical, biological and toxicological data that are widely dispersed, mostly in the open literature, professional research bodies and commercial companies. In order to better manage and make full use of such large amount of toxicity data, there is a trend to develop functionalities aiming towards data governance in predictive toxicology to formalise a set of processes to guarantee high data quality and better data management. In this paper, data quality mainly refers in a data storage sense (e.g. accuracy, completeness and integrity) and not in a toxicological sense (e.g. the quality of experimental results).ResultsThis paper reviews seven widely used predictive toxicology data sources and applications, with a particular focus on their data governance aspects, including: data accuracy, data completeness, data integrity, metadata and its management, data availability and data authorisation. This review reveals the current problems (e.g. lack of systematic and standard measures of data quality) and desirable needs (e.g. better management and further use of captured metadata and the development of flexible multi-level user access authorisation schemas) of predictive toxicology data sources development. The analytical results will help to address a significant gap in toxicology data quality assessment and lead to the development of novel frameworks for predictive toxicology data and model governance.ConclusionsWhile the discussed public data sources are well developed, there nevertheless remain some gaps in the development of a data governance framework to support predictive toxicology. In this paper, data governance is identified as the new challenge in predictive toxicology, and a good use of it may provide a promising framework for developing high quality and easy accessible toxicity data repositories. This paper also identifies important research directions that require further investigation in this area.

Use of toxicokinetics to support chemical evaluation: Informing high dose selection and study interpretation

Toxicokinetic (TK) information can substantially enhance the value of the data generated from toxicity testing, and is an integral part of pharmaceutical safety assessment. It is less widely used in the chemical, agrochemical and consumer products industries, but recognition of its value is growing, as reflected by increased reference to the use of TK information in new and draft OECD test guidelines. To help promote increased consideration of the important role TK can play in chemical risk assessment, we have gathered practical examples from the peer-reviewed literature, as well as in-house industry data, that highlight opportunities for the use of TK in the selection of dose levels. Use of TK can help to ensure studies are designed to be of most relevance to assessing potential risk in humans, and avoid the use of excessively high doses that could result in unnecessary suffering in experimental animals. Greater emphasis on the potential contribution of TK in guiding study design and interpretation should be incorporated in regulatory data requirements and associated guidance.

Assessment of the Effects of MPTP and Paraquat on Dopaminergic Neurons and Microglia in the Substantia Nigra Pars Compacta of C57BL/6 Mice

The neurotoxicity of paraquat dichloride (PQ) was assessed in two inbred strains of 9- or 16-week old male C57BL/6 mice housed in two different laboratories and compared to the effects of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). PQ was administered by intraperitoneal injections; either once (20 mg/kg) or twice (10 mg/kg) weekly for 3 weeks, while MPTP-HCl was injected 4 times on a single day (20 mg/kg/dose). Brains were collected 8, 16, 24, 48, 96 or 168 hours after the last PQ treatment, and 48 or 168 hours after MPTP treatment. Dopamine neurons in the substantia nigra pars compacta (SNpc) were identified by antibodies to tyrosine hydroxylase (TH+) and microglia were identified using Iba-1 immunoreactivity. The total number of TH+ neurons and the number of resting and activated microglia in the SNpc at 168 hours after the last dose were estimated using model- or design-based stereology, with investigators blinded to treatment. In a further analysis, a pathologist, also blinded to treatment, evaluated the SNpc and/or striatum for loss of TH+ neurons (SNpc) or terminals (striatum), cell death (as indicated by amino cupric silver uptake, TUNEL and/or caspase 3 staining) and neuroinflammation (as indicated by Iba-1 and/or GFAP staining). PQ, administered either once or twice weekly to 9- or 16-week old mice from two suppliers, had no effect on the number of TH+ neurons or microglia in the SNpc, as assessed by two groups, each blinded to treatment, using different stereological methods. PQ did not induce neuronal cell loss or degeneration in the SNpc or striatum. Additionally, there was no evidence of apoptosis, microgliosis or astrogliosis. In MPTP-treated mice, the number of TH+ neurons in the SNpc was significantly decreased and the number of activated microglia increased. Histopathological assessment found degenerating neurons/terminals in the SNpc and striatum but no evidence of apoptotic cell death. MPTP activated microglia in the SNpc and increased the number of astrocytes in the SNpc and striatum.

Framework for integrating human and animal data in chemical risk assessment

Although regulatory agencies formally encourage the integration of all available data in chemical risk assessment, consistent implementation of this practice has been constrained by the lack of a clear, systematic method for doing so. In this paper, we describe a methodology for evaluating, classifying and integrating human and animal data into the risk assessment process that incorporates: (1) a balanced appraisal of human and animal data, (2) relevance to different stages of the risk assessment process, and (3) accommodation for different data quality requirements. The proposed framework offers a flexible, step-wise approach for determining which set of available data best support the chemical risk assessment that involves the rating and relative ranking of human and animal data quality. The evaluation of human data incorporates seven data quality elements, nature and specificity of the lead effect; evaluation of animal data incorporates data quality and relevance to humans. Results of simulations with selected chemicals previously evaluated in a formal risk assessment generally agreed with existing regulatory guidance. Application of the proposed framework across a wider range of chemical agents will improve transparency of the risk assessment process and validity of results, while informing continuous refinements to this evolving methodology.

Maximum Residue Levels: Fact or Fiction?

Maximum residue levels (MRLs) are trading standards that represent the maximum residue that could be found if a crop protection product (CPP) is applied according to critical good agricultural practice (cGAP). Foodstuffs are monitored for MRL compliance and exceedence can have economic, social and political consequences. There is a trade-off when calculating MRLs, as low MRLs prevent misuse of CPPs and high MRLs prevent an ‘unlucky’ farmer exceeding the MRL by chance. Chance exceedence has not been previously investigated despite the high probability of exceedence due to small data sets and calculation method. In this study, MRL calculation methods were investigated and policy for using these methods to control chance exceedence was defined. The shape and parameters of the residue distribution, LOQ and number of trials all affected the accuracy and precision of the estimated MRL. The two European methods were least accurate and precise at small numbers of trials and high CVs, with up to four different MRLs possible. Eight to 16 trials gave the best estimate of the MRL, but exceedence by chance could occur in up to 45% of samples. Policy was defined for using existing methods, and involved calculation of the MRL by both methods and taking the highest.

Neurotoxicity of paraquat and paraquat-induced mechanisms of developing Parkinson’s disease

Neurotoxicity of paraquat and paraquat-induced mechanisms of developing Parkinson’s disease

Fuzzy complex number aided evaluation of predictive toxicology models

There is a growing interest in applying computational intelligence in the predictive toxicology (PT) domain, where a large number of predictive models are becoming available. Evaluation of such models is therefore considered to be a crucial part of their development and potential use, especially for regulatory purposes. The current evaluation approaches mainly focus on statistical measures of model performance, and few of them have taken data quality into consideration. However, it has been well recognised that datasets and models should not be considered in isolation. This paper proposes a new confidence index for evaluating PT models. A fuzzy complex number (FCN) framework is expanded in an effort to represent and evaluate dataset and regression-based model quality in a two-dimensional manner, thereby ensuring the linguistic evaluation is transparent and explainable. The utility and applicability of this research is illustrated by an experiment which evaluates 17 regression-based PT models. The experimental results have been compared and analysed against existing methods, and show that the FCN-based approach provides a consistent and interpretable means of model assessment. The proposed indexing mechanism can be used, together with customised statistical measures, in assisting PT model selection. This approach also helps to capture the relationships between datasets and models, and contributes to the development of data and model governance in PT.