The effect of rotavirus vaccine on diarrhoea mortality

Background Approximately 39% of the global diarrhoea deaths in children aged 5 years may be attributable to rotavirus infection. Two rotavirus vaccines were recently introduced to the market, with evidence of efficacy in the USA, Europe and Latin America. We sought to estimate the effectiveness of these vaccines against rotavirus morbidity and mortality

Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path

We consider the problem of finding a near-optimal policy in continuous space, discounted Markovian Decision Problems given the trajectory of some behaviour policy. We study the policy iteration algorithm where in successive iterations the action-value functions of the intermediate policies are obtained by picking a function from some fixed function set (chosen by the user) that minimizes an unbiased finite-sample approximation to a novel loss function that upper-bounds the unmodified Bellman-residual criterion. The main result is a finite-sample, high-probability bound on the performance of the resulting policy that depends on the mixing rate of the trajectory, the capacity of the function set as measured by a novel capacity concept that we call the VC-crossing dimension, the approximation power of the function set and the discounted-average concentrability of the future-state distribution. To the best of our knowledge this is the first theoretical reinforcement learning result for off-policy control learning over continuous state-spaces using a single trajectory

A systematic review and critical assessment of incentive strategies for discovery and development of novel antibiotics

Despite the growing threat of antimicrobial resistance, pharmaceutical and biotechnology firms are reluctant to develop novel antibiotics because of a host of market failures. This problem is complicated by public health goals that demand antibiotic conservation and equitable patient access. Thus, an innovative incentive strategy is needed to encourage sustainable investment in antibiotics. This systematic review consolidates, classifies and critically assesses a total of 47 proposed incentives. Given the large number of possible strategies, a decision framework is presented to assist with the selection of incentives. This framework focuses on addressing market failures that result in limited investment, public health priorities regarding antibiotic stewardship and patient access, and implementation constraints and operational realities. The flexible nature of this framework allows policy makers to tailor an antibiotic incentive package that suits a country’s health system structure and needs

BoostingTree: parallel selection of weak learners in boosting, with application to ranking

Boosting algorithms have been found successful in many areas of machine learning and, in particular, in ranking. For typical classes of weak learners used in boosting (such as decision stumps or trees), a large feature space can slow down the training, while a long sequence of weak hypotheses combined by boosting can result in a computationally expensive model. In this paper we propose a strategy that builds several sequences of weak hypotheses in parallel, and extends the ones that are likely to yield a good model. The weak hypothesis sequences are arranged in a boosting tree, and new weak hypotheses are added to promising nodes (both leaves and inner nodes) of the tree using some randomized method. Theoretical results show that the proposed algorithm asymptotically achieves the performance of the base boosting algorithm applied. Experiments are provided in ranking web documents and move ordering in chess, and the results indicate that the new strategy yields better performance when the length of the sequence is limited, and converges to similar performance as the original boosting algorithms otherwise. © 2013 The Author(s)

Innovation and Access to Medicines for Neglected Populations: Could a Treaty Address a Broken Pharmaceutical R&D System?

As part of a cluster of articles leading up to the 2012 World Health Report and critically reflecting on the theme of “no health without research,” Suerie Moon and colleagues argue for a global health R&D treaty to improve innovation in new medicines and strengthening affordability, sustainable financing, efficiency in innovation, and equitable health-centered governance

Shaping a screening file for maximal lead discovery efficiency and effectiveness: elimination of molecular redundancy

High Throughput Screening (HTS) is a successful strategy for finding hits and leads that have the opportunity to be converted into drugs. In this paper we highlight novel computational methods used to select compounds to build a new screening file at Pfizer and the analytical methods we used to assess their quality. We also introduce the novel concept of molecular redundancy to help decide on the density of compounds required in any region of chemical space in order to be confident of running successful HTS campaigns

Common characteristics of open source software development and applicability for drug discovery: a systematic review

<p>Abstract</p> <p>Background</p> <p>Innovation through an open source model has proven to be successful for software development. This success has led many to speculate if open source can be applied to other industries with similar success. We attempt to provide an understanding of open source software development characteristics for researchers, business leaders and government officials who may be interested in utilizing open source innovation in other contexts and with an emphasis on drug discovery.</p> <p>Methods</p> <p>A systematic review was performed by searching relevant, multidisciplinary databases to extract empirical research regarding the common characteristics and barriers of initiating and maintaining an open source software development project.</p> <p>Results</p> <p>Common characteristics to open source software development pertinent to open source drug discovery were extracted. The characteristics were then grouped into the areas of participant attraction, management of volunteers, control mechanisms, legal framework and physical constraints. Lastly, their applicability to drug discovery was examined.</p> <p>Conclusions</p> <p>We believe that the open source model is viable for drug discovery, although it is unlikely that it will exactly follow the form used in software development. Hybrids will likely develop that suit the unique characteristics of drug discovery. We suggest potential motivations for organizations to join an open source drug discovery project. We also examine specific differences between software and medicines, specifically how the need for laboratories and physical goods will impact the model as well as the effect of patents.</p

Metaphors in Nanomedicine: The Case of Targeted Drug Delivery

International audienceThe promises of nanotechnology have been framed by a variety of metaphors, that not only channel the attention of the public, orient the questions asked by researchers, and convey epistemic choices closely linked to ethical preferences. In particular, the image of the 'therapeutic missile' commonly used to present targeted drug delivery devices emphasizes precision, control, surveillance and efficiency. Such values are highly praised in the current context of crisis of pharmaceutical innovation where military metaphors foster a general mobilization of resources from multiple fields of cutting-edge research. The missile metaphor, reminiscent of Paul Ehrlich's 'magic bullet', has framed the problem in simple terms: how to deliver the right dose in the right place at the right moment? Chemists, physicists and engineers who design multi-functional devices operating in vitro can think in such terms, as long as the devices are not actually operating through the messy environment of the body. A close look at what has been done and what remains to be done suggests that the metaphor of the "therapeutic missile" is neither sufficient, nor even necessary. Recent developments in nanomedicine suggest that therapeutic efficacy cannot be obtained without negotiating with the biological milieu and taking advantage of what it affords. An 'oïkological' approach seems more appropriate, more heuristic and more promising than the popular missile. It is based on the view of organism as an oikos that has to be carefully managed. The dispositions of nanocapsules have to be coupled with the affordances of the environment. As it requires dealing with nanoparticles as relational entities (defined by their potential for interactions) rather than as stable substances (defined by intrinsic properties) this metaphor eventually might well change research priorities in nanotechnology in general