Drugs for exceptionally rare diseases: a commentary on Hughes et al

Recently in this journal, Hughes and colleagues discussed special funding status to ultra-orphan drugs. They concluded that there should be a uniform policy for the provision of orphan drugs across Europe; that complete restriction was impractical, and that UK policy should aspire to the values of the EU directive on orphan drugs. We critically assess these arguments, demonstrating that they failed to justify special status for treatments for rare diseases

Drugs for exceptionally rare diseases: a commentary on Hughes et al

Recently in this journal, Hughes and colleagues discussed special funding status to ultra-orphan drugs. They concluded that there should be a uniform policy for the provision of orphan drugs across Europe; that complete restriction was impractical, and that UK policy should aspire to the values of the EU directive on orphan drugs. We critically assess these arguments, demonstrating that they failed to justify special status for treatments for rare diseases

Reforming the cancer drug fund focus on drugs that might be shown to be cost effective

The Cancer Drug Fund was originally conceived as a temporary measure, until value based pricing for drugs was introduced, to give NHS cancer patients access to drugs not approved by NICE. Spending on these drugs rose from less than the £50m (€63m; $79m) budgeted for the first year in 2010-11 to well over £200m in 2013-14, and the budget for the scheme—now extended for a further two years—will reach £280m by 2016.1 The recent changes to the fund recognise the impossibility, within any sensible budget limit, of providing all the new cancer drugs that offer possible benefit to patients. More radical changes are needed to the working of the fund, given the failure to introduce value based pricing, so that it deals with the underlying problem of inadequate information on the effectiveness and cost effectiveness of new cancer drugs when used in the NHS

Suppression of photon shot noise dephasing in a tunable coupling superconducting qubit

We demonstrate the suppression of photon shot noise dephasing in a superconducting qubit by eliminating its dispersive coupling to the readout cavity. This is achieved in a tunable coupling qubit, where the qubit frequency and coupling rate can be controlled independently. We observe that the coherence time approaches twice the relaxation time and becomes less sensitive to thermal photon noise when the dispersive coupling rate is tuned from several MHz to 22 kHz. This work provides a promising building block in circuit quantum electrodynamics that can hold high coherence and be integrated into larger systems

A Proton Magnetic Resonance Study of the Association of Lysozyme with Monosaccharide Inhibitors

It has been shown that the acetamido methyl protons of N-acetyl-d-glucosamine undergo a chemical shift to higher fields in their proton magnetic resonance spectrum when the inhibitor is bound to lysozyme. The observed chemical shift in the presence of the enzyme is different for the agr- and ß-anomeric forms of 2-acetamido-2-deoxy-d-glucopyranose indicating either a difference in the affinity of the anomeric forms for lysozyme or different magnetic environments for the methyl protons in their enzyme-bound state. That the agr- and ß-anomeric forms of GlcAc bind to lysozyme in a competitive fashion was indicated by observing the proton magnetic resonance spectra in the presence of 2-acetamido-d3-2-deoxy-agr-d-glucopyranose. The methyl glycosides, methyl-agr-GlcAc and methyl-ß-GlcAc, were also shown to bind competitively with both anomers of GlcAc. Quantitative analysis of the chemical shift data observed for the association of GlcAc with lysozyme was complicated by the mutarotation of GlcAc between its agr- and ß-anomeric forms. However, in the case of the methyl glucosides, where the conformation of each anomer is frozen, it was possible to analyze the chemical shift data in a straightforward manner, and the dissociation constant as well as the chemical shift of the acetamido methyl protons of the enzyme-inhibitor complex was determined for both anomers. The results indicate that the two anomers of methyl-GlcAc bind to lysozyme with slightly different affinities but that the acetamido methyl groups of both anomers experience identical magnetic environments in the enzyme-inhibitor complex

Digital quantum simulators in a scalable architecture of hybrid spin-photon qubits

Resolving quantum many-body problems represents one of the greatest challenges in physics and physical chemistry, due to the prohibitively large computational resources that would be required by using classical computers. A solution has been foreseen by directly simulating the time evolution through sequences of quantum gates applied to arrays of qubits, i.e. by implementing a digital quantum simulator. Superconducting circuits and resonators are emerging as an extremely-promising platform for quantum computation architectures, but a digital quantum simulator proposal that is straightforwardly scalable, universal, and realizable with state-of-the-art technology is presently lacking. Here we propose a viable scheme to implement a universal quantum simulator with hybrid spin-photon qubits in an array of superconducting resonators, which is intrinsically scalable and allows for local control. As representative examples we consider the transverse-field Ising model, a spin-1 Hamiltonian, and the two-dimensional Hubbard model; for these, we numerically simulate the scheme by including the main sources of decoherence. In addition, we show how to circumvent the potentially harmful effects of inhomogeneous broadening of the spin systems

Choosing the Link Function and Accounting for Link Uncertainty in Generalized Linear Models using Bayes Factors

One important component of model selection using generalized linear models (GLM) is the choice of a link function. Approximate Bayes factors are used to assess the improvement in fit over a GLM with canonical link when a parametric link family is used. For this approximate Bayes factors are calculated using the approximations given in Raftery (1996), together with a reference set of prior distributions. This methodology can also be used to differentiate between different parametric link families, as well as allowing one to jointly select the link family and the independent variables. This involves comparing nonnested models. This is illustrated using parametric link families studied in Czado (1997) for two data sets involving binomial responses