The Pollution Prevention
Assessment Framework : 
Of the approximately 80,000 chemicals used in the U.S. commerce relatively few have been tested with respect to human health and environment. For an even smaller fraction of chemicals has there been established sufficient test data to allow for a thorough evaluation of all risks involved. Thus, businesses, governmental organizations, and other stakeholders often do not have the necessary data to identify problem chemicals or to revise safer substitutes or to develop options that are less risky, that prevent pollution, and that are economically and environmentally sound. At times, companies have to make product and process decisions ahead of time without any data regarding the risk tradeoffs.
The Pollution Prevention Assessment Framework (P2 Framework) is a U.S. Environmental Protection Agency (EPA) developed software package that contains many of the Office of Pollution Prevention and Toxics (OPPT) internally applied computer-based methods for assessing risks based on chemical structure. The P2 Framework calculates many important risk-related details not previously available for new substances. These tools can provide information on carcinogenicity, toxicity to aquatic organisms, exposures to workers and the general public, bioconcentration, and environmental fate, among several other aspects. OPPT routinely uses these methods to highlight chemicals of concern, to identify safer substitutes, and to reduce or eliminate risks. These tools are also used by EPA for the evaluation of Pre-Manufacturing Notices (PMN).
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Example: The Eastman Kodak Study
EPA conducted a pilot project with the Eastman Kodak Company,
Rochester, NY, to evaluate the utility of the P2 Assessment Framework. The purpose
of this study was to learn how others might use the P2 Assessment Framework to make more
informed decisions about the health and ecological risks from industrial chemicals,
especially under the lack of actual test data. The following citations are from
Eastman Kodak's report concluding their experience with these decision-making software
tools: