The Human Toxome Project is part of a long-term vision to modernize toxicity testing for the 21st century. In the initial phase of the project, a consortium of six academic, commercial, and government organizations has partnered to map pathways of toxicity, using endocrine disruption as a model hazard. Experimental data is generated at multiple sites, and analyzed using a range of computational tools. While effectively gathering, managing, and analyzing the data for high-content experiments is a challenge in its own right, doing so for a growing number of -omics technologies, with larger data sets, across multiple institutions complicates the process. Interestingly, one of the most difficult, ongoing challenges has been the computational collaboration between the geographically separate institutions. Existing solutions cannot handle the growing heterogeneous data, provide a computational environment for consistent analysis, accommodate different workflows, and adapt to the constantly evolving methods and goals of a research project. To meet the needs of the project, we have created and managed The Human Toxome Collaboratorium, a shared computational environment hosted on third-party cloud services. The Collaboratorium provides a familiar virtual desktop, with a mix of commercial, open-source, and custom-built applications. It shares some of the challenges of traditional information technology, but with unique and unexpected constraints that emerge from the cloud. Here we describe the problems we faced, the current architecture of the solution, an example of its use, the major lessons we learned, and the future potential of the concept. In particular, the Collaboratorium represents a novel distribution method that could increase the reproducibility and reusability of results from similar large, multi-omic studies.
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http://dx.doi.org/10.3389/fphar.2015.00322 | DOI Listing |
Appl In Vitro Toxicol
December 2018
Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Quantitative to extrapolation (QIVIVE) is broadly considered a prerequisite bridge from findings to a dose paradigm. Quality and relevance of cell systems are the first prerequisite for QIVIVE. Information-rich and mechanistic endpoints (biomarkers) improve extrapolations, but a sophisticated endpoint does not make a bad cell model a good one.
View Article and Find Full Text PDFNow in its sixth year, the Lush Prize supports animal-free testing by awarding money prizes of up to £350,000 to the most effective projects and individuals who have been working towards the goal of replacing animals in product or ingredient safety testing. Prizes are awarded for developments in five strategic areas: Science; Lobbying; Training; Public Awareness; and Young Researchers. In the event of a major breakthrough leading to the replacement of animal tests in the area of 21st Century Toxicology, a Black Box Prize (equivalent to the entire annual fund) is awarded.
View Article and Find Full Text PDFJ Antimicrob Chemother
January 2018
Division of Paediatric Infectious Diseases, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Objectives: Clonal complex (CC) 9 is a prevalent livestock-associated (LA) MRSA clone in Asia whose pathogenicity in humans remains unknown.
Methods: In 2012, we identified a patient with CC9-MRSA infection linked to livestock. After screening 3328 clinical MRSA isolates from a national database, eight isolates (0.
The Lush Prize supports animal-free testing by rewarding the most effective projects and individuals who have been working toward the goal of replacing animals in product or ingredient safety testing. Prizes are awarded for developments in five strategic areas: Science; Lobbying; Training; Public Awareness; and Young Researchers. Should there be a major breakthrough in 21st century toxicology, a Black Box Prize equivalent to the entire annual fund of £250,000 is awarded.
View Article and Find Full Text PDFArch Toxicol
April 2017
The Hamner Institutes for Health Sciences, Research Triangle Park, NC, USA.
The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts.
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