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http://www.humgen.rwth-aachen.de/

Catalog of all changes detected in PKHD1 (Polycystic Kidney and Hepatic Disease 1) in a locus specific database. Investigators are invited to submit their novel data to this database. These data should be meaningful for clinical practice as well as of relevance for the reader interested in molecular aspects of polycystic kidney disease (PKD). There are also some links and information for ARPKD patients and their parents. Autosomal recessive polycystic kidney disease (ARPKD/PKHD1) is an important cause of renal-related and liver-related morbidity and mortality in childhood. This study reports mutation screening in 90 ARPKD patients and identifies mutations in 110 alleles making up a detection rate of 61%. Thirty-four of the detected mutations have not been reported previously. Two underlying mutations in 40 patients and one mutation in 30 cases are disclosed, and no mutation was detected on the remaining chromosomes. Mutations were found to be scattered throughout the gene without evidence of clustering at specific sites. PKHD1 mutation analysis is a powerful tool to establish the molecular cause of ARPKD in a given family. Direct identification of mutations allows an unequivocal diagnosis and accurate genetic counseling even in families displaying diagnostic challenges.

Proper citation: Autosomal Recessive Polycystic Kidney Disease Mutation Database (RRID:SCR_002290) Copy   

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http://talkbank.org/

Databases of transcript and media data collected from conversations with adults and older children to foster fundamental research in the study of human and animal communication. Conversations with children are available from CHILDES. All of the data is transcribed in CHAT and CA/CHAT formats. Databases of the following types are included in the collection: Aphasia patient speech, Child speech, Study of Phonological Development, Conversation Analysis, and Bilingualism and Second Language Acquisition. TalkBank will use these databases to advance the development of standards and tools for creating, sharing, searching, and commenting upon primary materials via networked computers.

Proper citation: TalkBank (RRID:SCR_003242) Copy   

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http://www.i2b2cictr.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 08, 2013. A two year Clinical and Translational Science Award (CTSA) supplement that set up a SHRINE (Shared Health Research Informatics NEtwork) network to create an information exchange environment that successfully shared 4.2M deidentified patient records. The network successfully linked i2b2 sites at UW, UCSF, UC Davis and Harvard Catalyst. Recombinant Data Corporation was actively involved in this implementation. This is a collaborative information exchange pilot project to adapt and extend data discovery tools and processes to enhance research design and retrospective data study capabilities for clinical translational investigators. The novel approach of this project will be to incrementally build a common technical, semantic and appropriately secure and governed distributed system in close partnership with active researchers at three large and geographically distributed academic medical centers. This collaboration will extend the Informatics for Integrating Biology and the Bedside (i2b2) software architecture developed by the Harvard based National Center for Biomedical Computing (NCBC) to support multi-institution data query capabilities. The anticipated outcome of this two-year project is to make high-level anonymized descriptive characteristics of population-level data discoverable for research design, hypothesis generation and retrospective data studies.

Proper citation: i2b2 Cross-Institutional Clinical Translational Research project (RRID:SCR_003367) Copy   

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http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

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http://purl.bioontology.org/ontology/XCO

An ontology designed to represent the conditions under which physiological and morphological measurements are made both in the clinic and in studies involving humans or model organisms.

Proper citation: Experimental Conditions Ontology (RRID:SCR_003306) Copy   

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http://sagebase.org/

Non-profit biomedical research organization developing predictors of disease and accelerating health research through creation of open systems, incentives, and standards. Formed to coordinate and link academic and commercial biomedical researchers through Commons that represents new paradigm for genomics intellectual property, researcher cooperation, and contributor evolved resources.

Proper citation: Sage Bionetworks (RRID:SCR_003384) Copy   

•   Source: SciCrunch Registry

http://www.humanvariomeproject.org/

Project facilitating the establishment and maintenance of standards systems and infrastructure for the worldwide collection and sharing of all genetic variations effecting human disease. The Human Variome Project produces two categories of recommendations: HVP Standards and HVP Guidelines. HVP Standards are those systems, procedures and technologies that the Human Variome Project Consortium has determined should be used by the community. These carry more weight than the less prescriptive HVP Guidelines, which cover those systems, procedures and technologies that the Human Variome Project Consortium has determined would be beneficial for the community to adopt. HVP Standards and Guidelines are central to supporting the work of the Human Variome Project Consortium and cover a wide range of fields and disciplines, from ethics to nomenclature, data transfer protocols to collection protocols from clinics. They can be thought of as both technical manuals and scientific documents, and while the impact of HVP Standards and Guidelines differ, they are both generated in a similar fashion. A document has been generated both as a guide for those collecting and distributing data and for those developing policy. Items should include those generated by HGVS/HVP collaborators as well as those generated by groups of individual Societies and Standards bodies in all relevant fields worldwide.

Proper citation: Human Variome Project (RRID:SCR_003492) Copy   

•   Source: SciCrunch Registry

http://genomicsandhealth.org/

An international coalition formed to enable the sharing of genomic and clinical data to help unlock potential advancements in medicine and science. Bringing together more than 145 leading institutions working in healthcare, research, disease advocacy, life science, and information technology, the Global Alliance is working together to create and promulgate harmonized approaches to enable the responsible, voluntary, and secure sharing of genomic and clinical data.

Proper citation: Global Alliance for Genomics and Health (RRID:SCR_003555) Copy   

•   Source: SciCrunch Registry

http://www.eyemoviepedia.com/

Archive and access films from the field of Ophthalmology for free on highly secure servers for permanent access and citeability. A citeable identification number (specific addressing using DOI), allows for citation of individual films in journal publications. Films may be commented by the author either in speech, or in text. Key wording provided by the authors at the time of submission, make each film recognizable to internet search machines.

Proper citation: eyeMoviePedia (RRID:SCR_003541) Copy   

•   Source: SciCrunch Registry

http://clinicalinformatics.stanford.edu/projects/cdw.html

Research and development project at Stanford University to create a standards-based informatics platform supporting clinical and translational research. STRIDE consists of three integrated components: a clinical data warehouse, based on the HL7 Reference Information Model (RIM), containing clinical information on over 1.6 million pediatric and adult patients cared for at Stanford University Medical Center since 1995; an application development framework for building research data management applications on the STRIDE platform and a biospecimen data management system. STRIDE's semantic model uses standardized terminologies, such as SNOMED, RxNorm, ICD and CPT, to represent important biomedical concepts and their relationships. STRIDE receives clinical data for research use via HL7 feeds from both SUMC hospitals: Lucile Packard Children's Hospital and Stanford Hospital and Clinics. This clinical data is used to support a wide variety of translational research services including: * Anonymized Patient Research Cohort Discovery * Electronic Chart Review for Research * IRB-Approved Clinical Data Extraction * Biospecimen Data Management * Multimedia Research * Data Management and Research Registries STRIDE is a highly secure environment utilizing encryption, fine-grained access control, robust auditing and detailed data segregation. Additionally, STRIDE has a robust access control framework with well-defined access granting authorities and access control groups. Consequently STRIDE meets or exceeds the requirements of the HIPAA Privacy and Security regulations. Privacy protection is further enhanced by requiring IRB approval for all research projects using STRIDE clinical data. From a technology and standards perspective, STRIDE is hosted on the Oracle 11g database platform. STRIDE application software provides access to the web services of a three-tier infrastructures using SSL encryption with strong authentication. These programs are cross-platform, self-updating thick-client applications that provides a rich user interface for data entry, retrieval and review as well as image manipulation and annotation. STRIDE makes extensive use of XML technologies for representation of structured meta data, distributed systems technologies using JSON for secure remote communication between client and server, and Swing graphical interface components providing a rich widget-set as well as advanced imaging and graphing capabilities. Users of the STRIDE Research Desktop Client can perform rapid data entry into structured fields, compose complex queries, and interact securely with clinical, research and imaging data.

Proper citation: Stanford Translational Research Integrated Database Environment and Clinical Data Warehouse (RRID:SCR_003453) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/amp/alzheimers.htm

The Alzheimer's disease arm of the Accelerating Medicines Partnership (AMP) that will identify biomarkers that can predict clinical outcomes, conduct a large scale analysis of human AD patient brain tissue samples to validate biological targets, and to increase the understanding of molecular pathways involved in the disease to identify new potential therapeutic targets. The initiative will deposit all data in a repository that will be accessible for use by the biomedical community. The five year endeavor, beginning in 2014, will result in several sets of project outcomes. For the biomarkers project, tau imaging and EEG data will be released in year two, as baseline data becomes available. Completed data from the randomized, blinded trials will be added after the end of the five year studies. This will include both imaging data and data from blood and spinal fluid biomarker studies. For the network analysis project, each project will general several network models of late onset AD (LOAD) and identify key drivers of disease pathogensis by the end of year three. Years four and five will be dedicated to validating the novel targets and refining the network models of LOAD, including screening novel compounds or drugs already in use for other conditions that may have the ability to modulate the likely targets.

Proper citation: Accelerating Medicines Partnership - Alzheimers (RRID:SCR_003742) Copy   

•   Source: SciCrunch Registry

http://www.cimit.org/

A non-profit consortium of Boston academic medical centers and universities (and growing) to accelerate the healthcare innovation cycle by fostering interdisciplinary, inter-institutional collaboration among experts in translational research, medicine, science, engineering, healthcare implementation and entrepreneurship in concert with industry, foundations and government to rapidly improve patient care. It concentrates on early stage, high-risk ideas, projects and supports them through to a commercial exit from academia. It provides innovators with resources to explore, develop and implement novel technological solutions for today's most urgent healthcare problems. CIMIT is dedicated to helping develop medical technology that will help both military and civilian patients.

Proper citation: Center for Integration of Medicine and Innovative Technology (RRID:SCR_003710) Copy   

•   Source: SciCrunch Registry

http://c3nproject.org/

Project designing, prototyping, optimizing, and evaluating a learning health system to improve clinical practice, patient self-management, and disease outcomes of patients with chronic illness. This open, peer production system combines the collective input of patients, clinicians and researchers. It combines large clinical data registries with patient entered data and makes them accessible and interactive. A platform allows researchers to design, test and implement new knowledge and innovations in patient care. To test their platform approach, C3N is working on a model of treating children with Inflammatory Bowel Disease using the ImproveCareNow Network of pediatric clinics. Following this demonstration phase, the goal is to apply the social, scientific and technical platform to transform the care of a variety of chronic illnesses. The C3N effort has the following goals: # Deploy and optimize an integrated set of engagement tools to make it easier for patients and care providers to collect and use the right information during the clinical encounter and in between visits. # Prototype novel interventions to re-design care delivery by promoting the development of tools for real-time and dynamic population management, "just-in time" scheduling of visits, virtual clinic visits, and measuring the impact of these interventions on health, care, and cost. # Pilot and deploy patient-focused technology to improve the flow of data between patients, clinicians and scientists to enable faster learning and improvement.

Proper citation: Collaborative Chronic Care Network (RRID:SCR_003708) Copy   

•   Source: SciCrunch Registry

http://c-path.org/programs/pstc/

A public-private partnership to identify new and improved translational safety testing methods for use in nonclinical and clinical studies and submit them for formal regulatory qualification by the FDA (Food and Drug Administration), EMA (European Medicines Agency), and PMDA (Japanese Pharmaceutical and Medical Devices Agency). The current 19 corporate members of the consortium share internal experience with nonclinical and clinical safety biomarkers in six working groups: cardiac hypertrophy, nephrotoxicity, hepatotoxicity, skeletal myopathy, testicular toxicity, and vascular injury. The ultimate goal of the consortium is to improve the current approach to drug safety testing and offer assurance to the drug developers that these approaches will be accepted by the regulatory authorities in their drug development programs. Through PSTC, members are able to share their expertise, resources, data, and internally developed approaches in a neutral, precompetitive, confidential environment. There are more than 250 participating scientists and C-Path serves as the trusted third party, leading the collaborative process by collecting and summarizing the data, and leading the interactions with global health authorities.

Proper citation: Predictive Safety Testing Consortium (RRID:SCR_003727) Copy   

•   Source: SciCrunch Registry

http://ispy2.org/

A collaboration to test an adaptive clinical trial model that would assess the efficacy of a candidate therapeutic earlier than traditional clinical trials, potentially enabling drugs to be developed and approved using fewer patients, less time and fewer resources. This trial focuses on women with newly diagnosed locally advanced breast cancer to test whether adding investigational drugs to standard chemotherapy is better than standard chemotherapy alone. It uses genetic and biological markers from individual patients' tumors to screen several promising new treatments simultaneously and allows doctors to quickly measure the effectiveness of the treatment prior to removing the tumor. The experimental adaptive trial design uses patient outcomes to immediately inform treatment options for subsequent trial participants. The trial has 5 components that differentiate it from conventional clinical trial models. # I-SPY2 uses tissue and imaging biomarkers from individual cancer patients' tumors to determine eligibility, guide/screen promising new treatments and identify which treatments are most effective in specific tumor subtypes. # The trial's adaptive design allows the Team to learn as they go, enabling researchers to use data from patients early in the trial to guide decisions about which treatments might be more useful for patients who enter the trial earlier. I-SPY2 provides a scientific basis for researchers to eliminate ineffective treatments and graduate effective treatments more quickly. # The neoadjuvant treatment approach - in which chemotherapy is given to patients prior to surgery - allow the team to evaluate tumor response with MRI before removal. This approach is safe as treating after surgery, allowing tumors to shrink, and more importantly, it enables critical learning early on about how well treatments work. # The ability for the team to screen multiple drug candidates developed by multiple companies. New agents will be selected and added as those used initially and either graduate to Phase III, or are dropped, based on their efficacy in targeted patients. # The trials informatics system allows data to be collected, verified, and shared in real-time. This allows data to be assessed early and in an integrated fashion - with an aim to enhance and encourage collaboration

Proper citation: I-SPY 2 TRIAL (RRID:SCR_003713) Copy   

•   Source: SciCrunch Registry

http://www.transformproject.eu/portfolio-item/d6-3-data-integration-models/

A set of three models, which in conjunction with the semantic mediator enables the execution of queries formulated through the eligibility representation of the Clinical research information model (WT6.4). An ontology-driven mechanism was developed to enable linkage and integration of phenotypic and genotypic data from multiple distributed data sources. It makes use of the Clinical Data Integration Model (CDIM, WT6.5), the Data Source Model (DSM, WT6.6) and the CDIM-DSM mapping model (WT6.6). Queries formulated through the CDIM and vocabulary service (WT7.2) are translated to local queries by the mediator using the individual source instances of the DSM and CDIM-DSM models.

Proper citation: TRANSFoRm Data Integration Models (RRID:SCR_003892) Copy   

•   Source: SciCrunch Registry

http://www.clinit.net/

An independent owner-operated contract research organization providing clinical research services to the biopharmaceutical industry and life science organizations. If you are looking for data management, biostatistics and EDC solutions or plan to conduct a high quality phase I-IV or non-interventional study in and outside of Germany KOEHLER eClinical is your partner in study planning, conduct, evaluation and publication.

Proper citation: KOEHLER eClinical (RRID:SCR_003896) Copy   

•   Source: SciCrunch Registry

http://www.precisesads.eu/

A project that will study 2,500 people with various systemic autoimmune diseases (SADs), gathering data on the molecular causes of their disease as well as their clinical symptoms, enabling them to pave the way for a new classification of these diseases. The goal is to use OMICs and bioinformatics to identify new classifications for diseases known to share common pathophysiological mechanisms. Results will be shared to deliver a new molecular taxonomy of systemic autoimmune diseases. In order to achieve this, PRECISEADS is informing on a regular basis on the project implementation and results, and involving stakeholders from Europe in its activities in order to broaden the project impact and increase opportunities for cooperation.

Proper citation: PRECISESADS (RRID:SCR_003882) Copy   

•   Source: SciCrunch Registry

http://www.onestudy.org/

Consortium aiming to produce regulatory T cells that are compatible with a kidney transplant patient''''s immune system, as a measure to suppress the body''''s natural immune response against a transplanted organ. If successful, this approach will reduce a transplantation patient''''s life-long dependency on immune suppressing drugs, many of which are often associated with undesirable side effects and can limit the patient''''s daily routine. The consortium goals are to develop and conduct clinical trials of various immunoregulatory T-cell-based products in organ transplantation recipients, allowing a direct comparison of the safety, clinical practicality and therapeutic efficacy of each cell type. The central focus of the project is to: # Production and manufacture of distinct populations of hematopoietic immunoregulatory T cells # Comparatively study the tolerogenic characteristics of these regulatory cell types # Test these cell therapy products side by side in a clinical trial living donor renal transplant recipients The first workstream will work with different T regulatory cell, tolerogenic DC and suppressive macrophage cell products that are currently in development. In addition to these therapeutics, another goal of this workstream is to develop a cell tracking technology that assesses pharmacodynamics and pharmacokinetics of these cell-based therapies. The second workstream is focused on designing and conducting a cell therapy based clinical trial in renal transplantation, taking into consideration ethics, concurrent immunosuppressive drug use, state-of-the-art immune monitoring, innovative all-in-one data capturing systems, and pharmacovigilance. The goal is to have a comparative evaluation of hematopoietic cell therapy safety in renal transplantation. The third workstream aims to learn more about the specific comparative characteristics of suppressive cell types and to use this knowledge to improve later trial designs and foster novel ideas for new or improved suppressive / tolerogenic cell population.

Proper citation: ONE Study (RRID:SCR_003886) Copy   

•   Source: SciCrunch Registry

http://www.transformproject.eu/wp-content/uploads/documents/cdim.owl

A global mediation model expressed as an ontology for use in the primary care domain. It uses a realist approach employing Basic Formal Ontology (BFO v1.1) as an upper ontology. Other ontologies were imported or specialized to give deeper definition to the concepts in the domain. These included OGMS, IAO and VSO. The CDIM ontology includes concepts that are especially important to primary care (e.g. episode of care or reason for encounter), but also others to handle temporality in queries (e.g. the start and beginning of processes). The owl file provided for download is the merged file created directly in Prot��g�� through the Refactor/Merge ontologies tool in order to facilitate the load of CDIM in LexEVS for use in the unified interoperability framework.

Proper citation: TRANSFoRm Clinical Data Integration Model (RRID:SCR_003885) Copy   

•   Source: SciCrunch Registry