Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

Cross-organisation data sharing is challenging because all the involved organisations must agree on ’how’ and ’why’ the data is processed. Due to a lack of transparency, the organisations need to trust that others comply with the agreements and regulations. We propose to exploit blockchain and smart contracts technologies to define an Attribute-Based Access Control System for cross-organisation medical records sharing, coined SmartAccess. SmartAccess offers joint agreement over access policies and dynamic access control besides blockchain transparency and auditability. We leverage the Attribute-Based Access Control model to implement smart contracts.We deploy and test them on a private and permissioned blockchain, transforming the access control process into a distributed smart contract execution. This paper proposes the SmartAccess system and its application in two healthcare use cases. We introduce the threat model and perform a security analysis of the system. To demonstrate the feasibility of our proposal, we implement a proof-of-concept of the smart contracts, written in Solidity language, with a size-efficient policy representation, and analyse the complexity and scalability of the contracts’ functions. Furthermore, we present performance results, measuring the latency and throughput of the transactions to execute the access control functions with different blockchain network consensus setups. We also compare the performance of the SmartAccess system against two open-source Solidity implementations of smart contract-based access control, Role-based Access Control and Access Control List. Finally, we discuss the strengths and drawbacks of our proposal. SmartAccess requires the overhead of a decentralised system, but the trade-off is transparency, regulation compliance and auditability for complex cross-organisation data sharing.

Virus discovery combining sequence unbiased amplification with next generation sequencing is now state-of-the-art. We have previously determined that the performance of the unbiased amplification technique which is operational at our institute, VIDISCA-454, is efficient when respiratory samples are used as input. The performance of the assay is, however, not known for other clinical materials like blood or stool samples. Here, we investigated the sensitivity of VIDISCA-454 with feces-suspensions and serum samples that are positive and that have been quantified for norovirus and human immunodeficiency virus type 1, respectively. The performance of VIDISCA-454 in serum samples was equal to its performance in respiratory material, with an estimated lower threshold of 1,000 viral genome copies. The estimated threshold in feces-suspension is around 200,000 viral genome copies. The decreased sensitivity in feces suspension is mainly due to sequences that share no recognizable identity with known sequences. Most likely these sequences originate from bacteria and phages which are not completely sequenced.

Cyberattacks against healthcare institutions threaten patient care. The risk of being targeted by a damaging attack is increased when medical devices are used which rely on unmaintained legacy software that cannot be replaced and may have publicly known vulnerabilities. This review aims to provide insight into solutions presented in the literature that mitigate risks caused by legacy software on medical devices. We performed a scoping review by categorising and analysing the contributions of a selection of articles, taken from a literature set discovered through bidirectional citation searching. We found 18 solutions, each fitting at least one of the categories of intrusion detection and prevention, communication tunnelling or hardware protections. Approaches taken include proxying Bluetooth communication through smartphones, behaviour-specification based anomaly detection and authenticating signals based on physical characteristics. These solutions are applicable to various use-cases, ranging from securing pacemakers to medical sensor networks. Most of the solutions are based on intrusion detection and on tunnelling insecure wireless communications. These technologies have distinct application areas, and the decision which one is most appropriate will depend on the type of medical device.

Summary: Science gateways provide UIs and high‐level services to access and manage applications and data collections on distributed resources. They facilitate users to perform data analysis on distributed computing infrastructures without getting involved into the technical details. The e‐BioInfra Gateway is a science gateway for biomedical data analysis on a national grid infrastructure, which has been successfully adopted for neuroscience research. This paper describes the motivation, requirements, and design of a new generation of e‐BioInfra Gateway, which is based on the grid and cloud user support environment (also known as WS‐PGRADE/gUSE framework) and supports heterogeneous infrastructures. The new gateway has been designed to have additional data and meta‐data management facilities to access and manage (biomedical) data servers, and to provide data‐centric user interaction. We have implemented and deployed the new gateway for the computational neuroscience research community of the Academic Medical Center of the University of Amsterdam. This paper presents the system architecture of the new gateway, highlights the improvements that have been achieved, discusses the choices that we have made, and reflects on those based on initial user feedback. Copyright © 2014 John Wiley & Sons, Ltd.