The majority of risk assessments are performed on individual chemicals. Most high production volume chemicals will have a basic set of data to identify the main hazards for a risk assessment. However, by intelligent data generation in similar groups of high production volume chemicals it is possible to avoid extensive use of resources, including experimental animals. A key to such an approach is to use expert tools such as quantitative structure actions relationship (QSAR) models. Such tools are not only useful in maximising the applicability of data when undertaking tests for groups of chemicals but they can be used to predict effects and possible dose-response relationships in endpoints beyond a base data set. Furthermore, chemicals that are produced in amounts lower than ”high production volumes” may not have sufficient data to assess hazards. In such cases, modelling schemes are a useful initial tool to predict hazards for a health hazard assessment as well as highlighting specific areas of toxicological concern by virtue of the chemical's structure.
Proposals submitted for consideration should follow the format of the application from'Application for a CEFIC-LRI Grant' and should address the following areas under individual subheadings:
The title of the research proposal.
The name and affiliation of the principal investigator and the laboratory or laboratories in which the research will be conducted.
Evidence of the principal investigator's knowledge of, and contribution to, current understandings of the role QSARs in toxicology, in particular dose-response relationships at low levels of exposure.
A clear definition of the research objectives, including a description of the mechanistic basis for the proposed research.
A clear plan of investigation, including a clearly defined milestone plan that identifies all critical decision points in the research programme.
A detailed breakdown of costs.
The successful applicant(s) will be required to submit a progress report every 6 months during the course of the programme. At the end of the project, a detailed review of the project and the achievements made will be provided by the principal investigator. The successful applicant(s) will also be required to prepare for publication a manuscript describing the work undertaken and the results achieved.
For chemicals having low NOELs, sponsor a research project to (i) classify them into combinations of chemical functional groups and toxic endpoints; and (ii) to analyse for possible general conclusions.
Phase (i): Utilising the data available within existing effects databases, e.g. the Gold database on carcinogens, and from the literature, classify those chemicals having low NOELs into combinations of chemical functional groups and toxic endpoints.
Phase (i): Analyse the resultant listings for possible general conclusions (generic groupings), in order these may reliably be used in developing risk assessment approaches.
Phase (ii): Analyse the available data for quality and identify uncertainties for the conclusions made under Phase (i).