The Cost of US Pharmaceutical Price Reductions: A Financial Simulation Model of R&D Decisions

Previous empirical studies that have examined the links between pharmaceutical price controls, profits, cash flows, and investment in research and development (R&D) have been largely based on retrospective statistical analyses of firm- and/or industry-level data. These studies, which have contributed numerous insights and findings to the literature, relied upon ad hoc reduced-form model specifications. In the current paper we take a very different approach: a prospective micro-simulation approach. Using Monte Carlo techniques we model how future price controls in the U.S. will impact early-stage product development decisions in the pharmaceutical industry. This is done within the context of a net present value (NPV) framework that appropriately reflects the uncertainty associated with R&D project technical success, development costs, and future revenues. Using partial-information estimators calibrated with the most contemporary clinical and economic data available, we demonstrate how pharmaceutical price controls will significantly diminish the incentives to undertake early-stage R&D investment. For example, we estimate that cutting prices by 40 to 50 percent in the U.S. will lead to between 30 to 60 percent fewer R&D projects being undertaken (in early-stage development). Given the recent legislative efforts to control prescription drug prices in the U.S., and the likelihood that price controls will prevail as a result, it is important to better understand the firm response to such a regulatory change.

The Background Field Method as a Canonical Transformation

We construct explicitly the canonical transformation that controls the full dependence (local and non-local) of the vertex functional of a Yang-Mills theory on a background field. After showing that the canonical transformation found is nothing but a direct field-theoretic generalization of the Lie transform of classical analytical mechanics, we comment on a number of possible applications, and in particular the non perturbative implementation of the background field method on the lattice, the background field formulation of the two particle irreducible formalism, and, finally, the formulation of the Schwinger-Dyson series in the presence of topologically non-trivial configurations.Comment: 11 pages, REVTeX. References added, some explanations extended. Final version to appear in the journa

Parrondo's games with chaotic switching

This paper investigates the different effects of chaotic switching on Parrondo's games, as compared to random and periodic switching. The rate of winning of Parrondo's games with chaotic switching depends on coefficient(s) defining the chaotic generator, initial conditions of the chaotic sequence and the proportion of Game A played. Maximum rate of winning can be obtained with all the above mentioned factors properly set, and this occurs when chaotic switching approaches periodic behavior.Comment: 11 pages, 9 figure

On the definition and characterisation of multipartite causal (non)separability

The concept of causal nonseparability has been recently introduced, in opposition to that of causal separability, to qualify physical processes that locally abide by the laws of quantum theory, but cannot be embedded in a well-defined global causal structure. While the definition is unambiguous in the bipartite case, its generalisation to the multipartite case is not so straightforward. Two seemingly different generalisations have been proposed, one for a restricted tripartite scenario and one for the general multipartite case. Here we compare the two, showing that they are in fact inequivalent. We propose our own definition of causal (non)separability for the general case, which---although a priori subtly different---turns out to be equivalent to the concept of "extensible causal (non)separability" introduced before, and which we argue is a more natural definition for general multipartite scenarios. We then derive necessary, as well as sufficient conditions to characterise causally (non)separable processes in practice. These allow one to devise practical tests, by generalising the tool of witnesses of causal nonseparability

Research on utilization of part task spatial orientation information in the dynamic simulator

Error and control efficiency analysis of pilots exposed to simulated pitch, roll, yaw, and altitude variation

Avian embryonic development in hyperdynamic environments

Embryos which developed for 24 hours in the oviduct of hens maintained at 2 G and which were subsequently incubated at Earth gravity had a 14% reduction in hatchability. Increased mortality during the first 4 days, and an increase in embryonic abnormalities were of the types usually found during the first mortality peak (2-3 days). Embryos in eggs that were produced at Earth gravity and continued their development on the centrifuge at fields of 2 G or less did not appear to be greatly affected by the treatment. At 4 G, 91% of the embryos died, mostly on the first and second days of incubation. Abnormalities prominent in the centrifuged eggs include: (a) a failure of the primitive streak to develop; (b) interference with the development of the axial skeleton; (c) multiple hemorrhages, mostly petechial which is consistent with capillary fragility; and (d) retardation of embryo growth, possibly caused by an interference with gaseous diffusion, the result of an acceleration-induced increase in gas density in the centrifuging incubator

A Non-Probabilistic Model of Relativised Predictability in Physics

Little effort has been devoted to studying generalised notions or models of (un)predictability, yet is an important concept throughout physics and plays a central role in quantum information theory, where key results rely on the supposed inherent unpredictability of measurement outcomes. In this paper we continue the programme started in [1] developing a general, non-probabilistic model of (un)predictability in physics. We present a more refined model that is capable of studying different degrees of "relativised" unpredictability. This model is based on the ability for an agent, acting via uniform, effective means, to predict correctly and reproducibly the outcome of an experiment using finite information extracted from the environment. We use this model to study further the degree of unpredictability certified by different quantum phenomena, showing that quantum complementarity guarantees a form of relativised unpredictability that is weaker than that guaranteed by Kochen-Specker-type value indefiniteness. We exemplify further the difference between certification by complementarity and value indefiniteness by showing that, unlike value indefiniteness, complementarity is compatible with the production of computable sequences of bits.Comment: 10 page