Structured frameworks are extremely useful in promoting transparent, harmonized approaches to the risk assessment of chemicals. One area where this has been particularly successful is in the analysis of modes of action (MOAs) for chemical carcinogens in experimental animals and their relevance to humans. The International Programme on Chemical Safety (IPCS) recently published an updated version of its MOA framework in animals to address human relevance (cancer human relevance framework, or HRF). This work has now been extended to noncancer effects, with the eventual objective of harmonizing framework approaches to both cancer and noncancer endpoints. As in the cancer HRF, the first step is to determine whether the weight of evidence based on experimental observations is sufficient to establish a hypothesized MOA. This comprises a series of key events causally related to the toxic effect, identified using an approach based on the Bradford Hill criteria. These events are then compared qualitatively and, next, quantitatively between experimental animals and humans. The output of the analysis is a clear statement of conclusions, together with the confidence, analysis, and implications of the findings. This framework provides a means of ensuring a transparent evaluation of the data, identification of key data gaps and of information that would be of value in the further risk assessment of the compound, such as on dose-response relationships, and recognition of potentially susceptible subgroups, for example, based on life-stage considerations.

The RISK21 integrated evaluation strategy is a problem formulation-based exposure-driven risk assessment roadmap that takes advantage of existing information to graphically represent the intersection of exposure and toxicity data on a highly visual matrix. This paper describes in detail the process for using the roadmap and matrix. The purpose of this methodology is to optimize the use of prior information and testing resources (animals, time, facilities, and personnel) to efficiently and transparently reach a risk and/or safety determination. Based on the particular problem, exposure and toxicity data should have sufficient precision to make such a decision. Estimates of exposure and toxicity, bounded by variability and/or uncertainty, are plotted on the X-and Y-axes of the RISK21 matrix, respectively. The resulting intersection is a highly visual representation of estimated risk. Decisions can then be made to increase precision in the exposure or toxicity estimates or declare that the available information is sufficient. RISK21 represents a step forward in the goal to introduce new methodologies into 21st century risk assessment. Indeed, because of its transparent and visual process, RISK21 has the potential to widen the scope of risk communication beyond those with technical expertise.

The Health and Environmental Sciences Institute (HESI)-coordinated Risk Assessment in the 21st Century (RISK21) project was initiated to develop a scientific, transparent, and efficient approach to the evolving world of human health risk assessment, and involved over 120 participants from 12 countries, 15 government institutions, 20 universities, 2 non-governmental organizations, and 12 corporations. This paper provides a brief overview of the tiered RISK21 framework called the roadmap and risk visualization matrix, and articulates the core principles derived by RISK21 participants that guided its development. Subsequent papers describe the roadmap and matrix in greater detail. RISK21 principles include focusing on problem formulation, utilizing existing information, starting with exposure assessment (rather than toxicity), and using a tiered process for data development. Bringing estimates of exposure and toxicity together on a two-dimensional matrix provides a clear rendition of human safety and risk. The value of the roadmap is its capacity to chronicle the stepwise acquisition of scientific information and display it in a clear and concise fashion. Furthermore, the tiered approach and transparent display of information will contribute to greater efficiencies by calling for data only as needed (enough precision to make a decision), thus conserving animals and other resources.

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