A Universal Framework for the Benefit-Risk Assessment of Medicines: Is This the Way Forward?
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In 2009, the National Research Council (NRC) released the latest in a series of advisory reports on human health risk assessment, titled Science and Decisions: Advancing Risk Assessment. This wide-ranging report made a number of recommendations related to risk assessment practice at the U.S. Environmental Protection Agency that could both influence and be influenced by evolving toxicological practice. In particular, Science and Decisions emphasized the scientific and operational necessity of a new approach for dose-response modeling; addressed the recurring challenge of defaults in risk assessment and the question of when research results can be used in place of defaults; and reinforced the value of cumulative risk assessment, which would require enhanced understanding of the joint influence of chemical and nonchemical stressors on health outcomes. The objective of this article is to summarize key messages from Science and Decisions, both as a stand-alone report and in comparison with another recent NRC report, Toxicity Testing in the 21st Century: A Vision and a Strategy. Although these reports have many conclusions in common and reinforce similar themes, there are important differences that merit careful consideration, such as the move away from apical endpoints in Toxicity Testing and the emphasis on benefit-cost analyses and related decision tools in Science and Decisions that would be strengthened by quantification of apical endpoints. Moving risk assessment forward will require toxicologists to wrestle with the implications of Science and Decisions from a toxicological perspective.
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Most computational soundness theorems deal with a limited number of primitives, thereby limiting their applicability. The notion of deduction soundness of Cortier and Warinschi (CCS'11) aims to facilitate soundness theorems for richer frameworks via composition results: deduction soundness can be extended, generically, with asymmetric encryption and public data structures. Unfortunately, that paper also hints at rather serious limitations regarding further composition results: composability with digital signatures seems to be precluded.
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We present a method for hierarchically generating sound workflow nets by substitution of nets with multiple inputs and outputs. We show that this method is correct and generalizes the class of nets generated by other hierarchical approaches. The method involves a new notion of soundness which is preserved by the generalized type of substitution that is presented in this paper. We show that this notion is better suited than *-soundness for use with the presented type of generalized substitution, since {*}-soundness is not preserved by it. It is moreover shown that it is in some sense the optimal notion of soundness for the purpose of generating sound nets by the presented type of substitution.
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