Practical Aspects of Designing and Conducting Validation Studies Involving Multi-study Trials.

This chapter focuses on practical aspects of conducting prospective in vitro validation studies, and in particular, by laboratories that are members of the European Union Network of Laboratories for the Validation of Alternative Methods (EU-NETVAL) that is coordinated by the EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM). Prospective validation studies involving EU-NETVAL, comprising a multi-study trial involving several laboratories or "test facilities", typically consist of two main steps: (1) the design of the validation study by EURL ECVAM and (2) the execution of the multi-study trial by a number of qualified laboratories within EU-NETVAL, coordinated and supported by EURL ECVAM. The approach adopted in the conduct of these validation studies adheres to the principles described in the OECD Guidance Document on the Validation and International Acceptance of new or updated test methods for Hazard Assessment No. 34 (OECD 2005). The context and scope of conducting prospective in vitro validation studies is dealt with in Chap. 4 . Here we focus mainly on the processes followed to carry out a prospective validation of in vitro methods involving different laboratories with the ultimate aim of generating a dataset that can support a decision in relation to the possible development of an international test guideline (e.g. by the OECD) or the establishment of performance standards.

Metabolism-mediated neurotoxicity: the significance of genetically engineered cell lines and new three-dimensional cell cultures.

Until now, no in vitro methods for determining neurotoxic effects, on Phase I and Phase II biotransformation-driven metabolite formation or for the evaluation of the metabolism-mediated hazard of a chemical, have been validated. The current test guidelines are based on studies in vivo, involving animals exposed to the test substance. Novel in vitro testing instead of animal testing is required by Directive 86/609/EEC. In the EU White Paper on a Strategy for a Future Chemicals Policy, which may result in up to 20,000 chemicals being screened for toxicity, the use of non-animal test methods is seen as essential and is encouraged. The aim of the present work was to demonstrate the significance of novel technologies, including the use of genetically engineered cell lines and three-dimensional cell culture techniques for direct application in the regulatory hazard-assessment process. Furthermore, attempts were made to make in vitro toxicity tests for specific applications more-readily available for inclusion in the chemical hazard-assessment process, by exploiting advances made in the life sciences.

Automation of an in vitro cytotoxicity assay used to estimate starting doses in acute oral systemic toxicity tests.

Application of High Throughput Screening (HTS) to the regulatory safety assessment of chemicals is still in its infancy but shows great promise in terms of facilitating better understanding of toxicological modes-of-action, reducing the reliance on animal testing, and allowing more data-poor chemicals to be assessed at a reasonable cost. To promote the uptake and acceptance of HTS approaches, we describe in a stepwise manner how a well known cytotoxicity assay can be automated to increase throughput while maintaining reliability. Results generated with selected reference chemicals compared very favourably with data obtained from a previous international validation study concerning the prediction of acute systemic toxicity in rodents. The automated assay was then included in a formal ECVAM validation study to determine if the assay could be used for binary classification of chemicals with respect to their acute oral toxicity, using a threshold equivalent to a dose of 2000 mg/kg b.w. in a rodent bioassay (LD50). This involved the blind-testing of 56 reference chemicals on the HTS platform to produce concentration-response and IC50 data. Finally, the assay was adapted to a format more suited to higher throughput testing without compromising the quality of the data obtained.