Decision-theoretic designs for phase II clinical trials allowing for competing studies

This article describes an approach to optimal design of phase II clinical trials using Bayesian decision theory. The method proposed extends that suggested by Stallard (1998, Biometrics 54, 279-294) in which designs were obtained to maximize a gain function including the cost of drug development and the benefit from a successful therapy. Here, the approach is extended by the consideration of other potential therapies, the development of which is competing for the same limited resources. The resulting optimal designs are shown to have frequentist properties much more similar to those traditionally used in phase II trials.     

Review of trap-and-haul for managing Pacific salmonids (Oncorhynchus spp.) in impounded river systems

High-head dams are migration barriers for Pacific salmon Oncorhynchus spp. in many river systems and recovery measures for impacted stocks are limited. Trap-and-haul has been widely used in attempts to facilitate recovery but information from existing programs has not been synthesized to inform improvements to aid recovery of salmonids in systems with high-head dams. We reviewed 17 trap-and-haul programs regarding Pacific salmon to: (1) summarize information about facility design, operation and biological effects; (2) identify critical knowledge gaps; and (3) evaluate trap-and-haul as a current and future management tool. Existing programs are operated to address a range of management goals including restoring access to historical habitats, temporarily reducing exposure to dangerous in-river conditions, and reintroducing ecological processes upstream from dams. Information gathered from decades of operation on facility design criteria and fish handling protocols, and robust literature on fish collection and passage are available. While many aspects of trap-and-haul have been evaluated, effects on population productivity and sustainability remain poorly understood. Long-term and systematic studies of trap-and-haul outcomes are rare, and assessments can be confounded by concurrent management actions and broad ecological and climatic effects. Existing data suggest that performance and effectiveness vary among programs and over various time scales within programs. Although critical information gaps exist, trap-and-haul is an important management and conservation tool for providing Pacific salmonids access to historical habitats. Successful application of trap-and-haul programs requires long-term commitment and an adaptive management approach by dam owners and stakeholders, and careful planning of new programs.

     

MRPack: Multi-Algorithm Execution Using Compute-Intensive Approach in MapReduce

Large quantities of data have been generated from multiple sources at exponential rates in the last few years. These data are generated at high velocity as real time and streaming data in variety of formats. These characteristics give rise to challenges in its modeling, computation, and processing. Hadoop MapReduce (MR) is a well known data-intensive distributed processing framework using the distributed file system (DFS) for Big Data. Current implementations of MR only support execution of a single algorithm in the entire Hadoop cluster. In this paper, we propose MapReducePack (MRPack), a variation of MR that supports execution of a set of related algorithms in a single MR job. We exploit the computational capability of a cluster by increasing the compute-intensiveness of MapReduce while maintaining its data-intensive approach. It uses the available computing resources by dynamically managing the task assignment and intermediate data. Intermediate data from multiple algorithms are managed using multi-key and skew mitigation strategies. The performance study of the proposed system shows that it is time, I/O, and memory efficient compared to the default MapReduce. The proposed approach reduces the execution time by 200% with an approximate 50% decrease in I/O cost. Complexity and qualitative results analysis shows significant performance improvement.     

Optimal sample size allocation and go/no‐go decision rules for phase II/III programs where several phase III trials are performed

The conduct of phase II and III programs is costly, time‐consuming and, due to high failure rates in late development stages, risky. There is a strong connection between phase II and III trials as the go/no‐go decision and the sample size chosen for phase III are based on the results observed in phase II. An integrated planning of phase II and III is therefore reasonable. The success of phase II/III programs crucially depends on the allocation of the resources to phase II and III in terms of sample size and the rule applied to decide whether to stop or to proceed with phase III. Recently, a utility‐based approach was proposed, where optimal planning of phase II/III programs is achieved by taking fixed and variable costs of the drug development program and potential gains after a successful launch into account. However, this method is restricted to programs with a single phase III trial, while regulatory authorities usually require statistical significance in two or more phase III trials. We present a generalization of this procedure to programs where two or more phase III trials are performed. Optimal phase II sample sizes and go/no‐go decision rules are provided for time‐to‐event outcomes and cases, where at least one, two, or three phase III trials need to be successful. Different drug development program strategies (e.g. one large vs. two phase III trials) are compared within these different cases. Application to practical examples typically met in oncology trials illustrates the proposed method.     

Use of Comparative Genomics to Develop EST-SSRs for Red Drum (Sciaenops ocellatus)

Microsatellites physically linked to expressed sequence tags (EST-SSRs) are an important resource for linkage mapping and comparative genomics, and data mining in publicly available EST databases is a common strategy for EST-SSR discovery. At present, many species lack species-specific EST sequence data needed for the efficient characterization of EST-SSRs. This paper describes the discovery and development of EST-SSRs for red drum (Sciaenops ocellatus), an estuarine-dependent sciaenid species of economic importance in the USA and elsewhere, using a phylogenetically informed, comparative genomics approach to primer design. The approach entailed comparing existing genomic resources from species closely allied phylogenetically to red drum, with resources from more distantly related outgroup species. By taking into account the degree to which flanking regions are conserved across taxa, the efficiency of PCR primer design was increased greatly. The amplification success rate for primers designed for red drum was 100?% when using EST libraries from confamilial species and 92?% when using an EST library from a species in the same suborder. The primers developed also amplified EST-SSRs in a wide range of perciform fishes, suggesting potential use in comparative genomics. This study demonstrates that EST-SSRs can be efficiently developed for an organism when limited species-specific data are available by exploiting genomic resources from well-studied species, even those at extended phylogenetic distances.     

Seed planning,sourcing, and procurement

Ensuring the availability of adequate seed supplies of species and sources appropriate for restoration projects and programs necessitates extensive science‐based planning. The selection of target species requires a review of disturbance conditions and reference areas, development of a reference model, and consideration of specific objectives, timeframes, available resources, and budgets as well as the performance of prospective species in past restoration efforts. Identification of seed sources adapted to site conditions is critical to provide for short‐term establishment and long‐term sustainability. Seed zones and plant movement guidelines provide tools for sourcing plant materials with reduced risk of maladaptation. A seed zone framework also facilitates seed use planning and contributes to stability and predictability of the commercial market, thereby reducing costs and improving the availability of adapted seed supplies. Calculating the amount of seed required for each species is based on seed quality (viability, purity), seed weight, expected seedling establishment, and desired composition of the seeding. If adequate collections from wildland stands are not feasible, then seed increase in seed fields or use of nursery stock may be warranted. Adherence to seed collection and seed production protocols for conserving genetic diversity is critical to protect genetic resources and buffer new seedings and plantings against environmental stressors. Maintenance of genetic diversity becomes even more critical considering current or expected climate change impacts. Collaboration and partnerships can benefit seed selection and procurement programs through sharing of information, coordination in project planning, and increasing the availability of native seed.     

Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds

ABSTRACT: BACKGROUND: The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster. In Bioinformatics, MapReduce has already been adopted to various case scenarios such as mapping next generation sequencing data to a reference genome, finding SNPs from short read data or matching strings in genotype files. Nevertheless, tasks like installing and maintaining MapReduce on a cluster system, importing data into its distributed file system or executing MapReduce programs require advanced knowledge in computer science and could thus prevent scientists from usage of currently available and useful software solutions. RESULTS: Here we present Cloudgene, a freely available platform to improve the usability of MapReduce programs in Bioinformatics by providing a graphical user interface for the execution, the import and export of data and the reproducibility of workflows on in-house (private clouds) and rented clusters (public clouds). The aim of Cloudgene is to build a standardized graphical execution environment for currently available and future MapReduce programs, which can all be integrated by using its plug-in interface. Since Cloudgene can be executed on private clusters, sensitive datasets can be kept in house at all time and data transfer times are therefore minimized. CONCLUSIONS: Our results show that MapReduce programs can be integrated into Cloudgene with little effort and without adding any computational overhead to existing programs. This platform gives developers the opportunity to focus on the actual implementation task and provides scientists a platform with the aim to hide the complexity of MapReduce. In addition to MapReduce programs, Cloudgene can also be used to launch predefined systems (e.g. Cloud BioLinux, RStudio) in public clouds. Currently, five different bioinformatic programs using MapReduce and two systems are integrated and have been successfully deployed. Cloudgene is freely available at http://cloudgene.uibk.ac.at.     

Women and the management of acute coronary syndrome

Coronary heart disease (CHD) is the leading cause of morbidity and mortality in both men and women in the developed countries. Despite this fact, females are still under-represented in the majority of clinical trials. At the present time, only limited evidence is available with respect to the female-specific aspects of pathogenesis, management, and outcomes in acute coronary syndrome (ACS). Women less frequently undergo coronary intervention, and a lower proportion of women receive evidence-based pharmacotherapy, compared with men. It has been shown that women benefit from an invasive approach and coronary intervention in ACS as much as men, despite their advanced age and higher rate of bleeding complications. Also, administration of beta-blockers, ACE-inhibitors, and intensive statin therapy is associated with a comparable reduction of cardiovascular event rates in women and men. On the other hand, women may profit less than men from fibrinolytic or glycoprotein IIb/IIIa inhibitor therapy. Both sexes benefit equally from aspirin therapy, whereas contradictory data are available on the efficacy of clopidogrel in women. There is an urgent need for intensive research in the development of female-specific therapeutic strategy in ACS, even though the detailed mechanisms of sex differences are still unknown.     

AutoClickChem: click chemistry in silico

Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.     

A new degree of freedom for memory allocation in clusters

Improvements in parallel computing hardware usually involve increments in the number of available resources for a given application such as the number of computing cores and the amount of memory. In the case of shared-memory computers, the increase in computing resources and available memory is usually constrained by the coherency protocol, whose overhead rises with system size, limiting the scalability of the final system. In this paper we propose an efficient and cost-effective way to increase the memory available for a given application by leveraging free memory in other computers in the cluster. Our proposal is based on the observation that many applications benefit from having more memory resources but do not require more computing cores, thus reducing the requirements for cache coherency and allowing a simpler implementation and better scalability. Simulation results show that, when additional mechanisms intended to hide remote memory latency are used, execution time of applications that use our proposal is similar to the time required to execute them in a computer populated with enough local memory, thus validating the feasibility of our proposal. We are currently building a prototype that implements our ideas. The first results from real executions in this prototype demonstrate not only that our proposal works but also that it can efficiently execute applications that make use of remote memory resources.     

CisML: an XML-based format for sequence motif detection software

SUMMARY: CisML is an XML-based format for sequence motif detection software. This proposed standard is applicable to many types of sequence motif detection programs. It is intended to facilitate the integration of data and the comparison of results from different software packages, and to simplify the development of downstream tools. XSL stylesheets are provided for easy generation of text, html and graphical reports from CisML-formatted data. AVAILABILITY: http://zlab.bu.edu/CisML/ SUPPLEMENTARY INFORMATION: Example CisML-formatted data and XSL stylesheets for report generation are available along with the sample output.     

Planning regional ecosystem sustainability under multiple uncertainties—An interval stochastic credibility-constrained programming approach

Inherent uncertainties in regional ecosystems can affect the modeling processes and the relevant results for managing and planning the real-world problems. In this study, an interval stochastic credibility-constrained programming (ISCP) method is developed for tacking multiple uncertainties expressed as intervals, fuzzy sets and probability distributions. The ISCP method is applied to planning regional ecosystem sustainability in the City of Dongying (China), in which ecosystem services valuation approach is directly incorporated within the optimization processes. Results associated with credibility levels of resources availability and the effects of sensitive ecological factors on the ecosystem services and ecological benefit are analyzed. Results show that a tighter limitation of ecological resources availability could cause lower economic development, particularly for oil field and oil refinery industries. Tradeoffs among social, economic and natural subsystems are also examined under different credibility levels, which are provided for generating optimal strategies in supporting of balancing the city’s economic and ecological sustainable development. Results of sensitivity analysis reveal that runoff coefficient is one of the most sensitive ecological factors in the process of calculating the ecological benefit. The findings can provide scientific bases for the integration of economic and ecological activities as well as the development of regional ecosystem-sustainability strategies.     

A vaccine against Asian schistosomiasis

There is continued transmission of schistosomiasis japonica in China and Philippines despite highly effective control programs that focus on the application of the highly effective drug praziquantel (PZQ). The massive Three Gorges Dam across the Yangtze River in Southern China, soon to be completed, is expected to significantly increase schistosomiasis transmission and introduce the disease into areas currently unaffected. After long-term experience it is generally accepted that PZQ chemotherapy, although the cornerstone of current control programs, does have significant limitations. Furthermore, efficient drug delivery requires a substantial infrastructure to regularly cover all parts of an endemic area. Although there is not yet clear-cut evidence for the existence of PZQ-resistant schistosome strains, decreased susceptibility to the drug has been observed in several countries. As a result, a protective vaccine represents an essential component for the long-term control of schistosomiasis. This article briefly reviews aspects of anti-schistosome protective immunity that are important in the context of vaccine development. The current status in the development of vaccines against Schistosoma japonicum will then be discussed as will new approaches that may improve on the efficacy of available vaccines, and aid in the identification of new targets for immune attack. With new and extensive data becoming available from the S. japonicum genome project, the prospects for developing an effective vaccine are encouraging. The challenges that remain are many but it is crucial that the momentum towards developing effective anti-schistosome vaccines is maintained.     

MapsiDB: an integrated web database for type I polyketide synthases

Polyketides have diverse biological activities, including pharmacological functions such as antibiotic, antitumor and agrochemical properties. They are biosynthesized from short carboxylic acid precursors by polyketide synthases (PKSs). As natural polyketide products include many clinically important drugs and the volume of data on polyketides is rapidly increasing, the development of a database system to manage polyketide data is essential. MapsiDB is an integrated web database formulated to contain data on type I polyketides and their PKSs, including domain and module composition and related genome information. Data on polyketides were collected from journals and online resources and processed with analysis programs. Web interfaces were utilized to construct and to access this database, allowing polyketide researchers to add their data to this database and to use it easily. MapsiDB is available at .