A Critical Examination of the FDA’s Efforts to Preempt Failure-to-Warn Claims

This article explores the legality and wisdom of the FDA’s effort to persuade courts to find most failure-to-warn claims preempted. The article first analyzes the FDA’s justifications for reversing its long-held views to the contrary and explains why the FDA’s position cannot be reconciled with its governing statute. The article then examines why the FDA’s position, if ultimately adopted by the courts, would undermine the incentives drug manufacturers have to change labeling to respond to newly-discovered risks. The background possibility of failure-to-warn litigation provides important incentives for drug companies to ensure that drug labels reflect accurate and up-to-date safety information. The article next explains why the agency’s view that it is capable of singlehandedly regulating the safety of drugs is unrealistic. The agency does not have the resources to perform the Herculean task of monitoring the performance of every drug on the market. Both the Institute of Medicine and the Government Accountability Office have explained the shortcomings in the FDA’s recent performance, and they express doubt that the FDA is in capable of facing an increasingly challenging future. The article then explains how state damages litigation helps uncover and assess risks that are not apparent to the agency during a drug’s approval process, and why this “feedback loop” enables the agency to better do its job. FDA approval of drugs is based on clinical trials that involve, at most, a few thousand patients and last a year or so. These trials cannot detect risks that are relatively rare, affect vulnerable sub-populations, or have long latency periods. For this reason, most serious adverse effects do not become evident until a drug is used in larger population groups for periods in excess of one year. Time and again, failure-to-warn litigation has brought to light information that would not otherwise be available to the FDA, to doctors, to other health care providers, and to consumers. And failure-to-warn litigation often has preceded and clearly influenced FDA decisions to modify labeling, and, at times, to withdraw drugs from the market

Front Propagation and Clustering in the Stochastic Nonlocal Fisher Equation

The nonlocal Fisher equation is a diffusion-reaction equation with a nonlocal quadratic competition, which describes the reaction between distant individuals. This equation arises in evolutionary biological systems, where the arena for the dynamics is trait space, diffusion accounts for mutations and individuals with similar traits compete, resulting in partial niche overlap. It has been found that the (non-cutoff) deterministic system gives rise to a spatially inhomogeneous state for a certain class of interaction kernels, while the stochastic system produces an inhomogeneous state for small enough population densities. Here we study the problem of front propagation in this system, comparing the stochastic dynamics to the heuristic approximation of this system by a deterministic system where the linear growth term is cut off below some critical density. Of particular interest is the nontrivial pattern left behind the front. For large population density, or small cutoff, there is a constant velocity wave propagating from the populated region to the unpopulated region. As in the local Fisher equation, the spreading velocity is much lower than the Fisher velocity which is the spreading velocity for infinite population size. The stochastic simulations give approximately the same spreading velocity as the deterministic simulation with appropriate birth cutoff. When the population density is small enough, there is a different mechanism of population spreading. The population is concentrated on clusters which divide and separate. This mode of spreading has small spreading velocity, decaying exponentially with the range of the interaction kernel

3D-2D transition in mode-I fracture microbranching in a perturbed hexagonal close-packed lattice

Mode-I fracture exhibits microbranching in the high velocity regime where the simple straight crack is unstable. For velocities below the instability, classic modeling using linear elasticity is valid. However, showing the existence of the instability and calculating the dynamics post-instability within the linear elastic framework is difficult and controversial. The experimental results give several indications that the microbranching phenomenon is basically a three-dimensional phenomenon. Nevertheless, the theoretical effort has been focused mostly in two-dimensional modeling. In this work we study the microbranching instability using three-dimensional atomistic simulations, exploring the difference between the 2D and 3D models. We find that the basic 3D fracture pattern shares similar behavior with the 2D case. Nevertheless, we exhibit a clear 3D-2D transition as the crack velocity increases, while as long as the microbranches are sufficiently small, the behavior is pure 3D-behavior, while at large driving, as the size of the microbranches increases, more 2D-like behavior is exhibited. In addition, in 3D simulations, the quantitative features of the microbranches, separating the regimes of steady-state cracks (mirror) and post-instability (mist-hackle) are reproduced clearly, consistent with the experimental findings.Comment: 9 pages, 11 figure