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http://academicdepartments.musc.edu/aging/

A center dedicated to research, service, and education concerning aging. MUSC primarily promotes the health, increased longevity, and improved quality of life of senior South Carolinians. This organization does such through the establishment of a national translational research program about aging, the development of a comprehensive/coordinated system of health care delivery for older individuals, and providing health education and outreach to students, faculty members, practicing health providers and the overall public. This center consists of several different research programs, including the Movement Disorder program, Stroke program, Alzheimer's program, Biology of Aging program, Outreach and Education program, and the Clinical Geriatric program.

Proper citation: Medical University of South Carolina Center on Aging (RRID:SCR_008825) Copy   

•   Source: SciCrunch Registry

http://www.mssm.edu/research/centers/alzheimers-disease-research-center/

A research facility and clinical program that is dedicated to the study and the treatment of both normal aging and Alzheimer's disease. This facility will accommodate requests for its resources (for example, data or tissue) from investigators that are not funded by the ADRC. Their team is composed of experts in geriatrics, geriatric psychiatry and psychology, neurology, pathology, and radiology. All team members work to provide services to those with memory disorders. This center sponsors educational programs for healthcare professionals and community groups. Data from the ADRC cores are available to all ADRC investigators after approval from the PI who collected the data. Data generated by the ADRC cores are communicated to the National Alzheimer's Coordinating Center (NACC) and can be available through them. Tissue can be distributed after approval of the Tissue Allocation Committee, and can be used for further research.

Proper citation: Mount Sinai Alzheimer's Disease Research Center (RRID:SCR_008780) Copy   

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http://depts.washington.edu/adrcweb/

Research center investigating the basic mechanisms underlying the development of Alzheimer's disease and related disorders, directing particular attention to biomarkers and experimental new treatments. They also continue to search for genetic risk factors underlying Alzheimer's disease (AD). Their main priorities are to find causes, effective treatments, and prevention strategies. Their investigators also are partnering with other Alzheimer's Centers across the country to evaluate promising new medications and other treatments for AD. The ultimate goal of their basic and clinical studies is to improve patient care and function, and improve the quality of life for both the patient and the caregiver. ADRC Cores: * Administration * Clinical Core * Satellite Core * Data Management & Biostatistics * Neuropathology Core * Education & Information Transfer * Genetics

Proper citation: University of Washington Alzheimers Disease Research Center (RRID:SCR_008814) Copy   

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http://www.cancerimagingarchive.net/

Archive of medical images of cancer accessible for public download. All images are stored in DICOM file format and organized as Collections, typically patients related by common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. Neuroimaging data sets include clinical outcomes, pathology, and genomics in addition to DICOM images. Submitting Data Proposals are welcomed.

Proper citation: Cancer Imaging Archive (TCIA) (RRID:SCR_008927) Copy   

•   Source: SciCrunch Registry

https://joslinresearch.org

Diabetes research center which provides patient care and performs diabetes research. Its primary aim is to provide a facilitating framework for conducting multi-disciplinary basic and clinical research and to encourage the scientific development of young investigators.

Proper citation: Joslin Diabetes Center (RRID:SCR_009019) Copy   

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http://hub.ucsf.edu/

Portal to resources, expertise, and best practices for investigators, study staff, participants and partners/affiliates to facilitate efficient, compliant and ethical study conduct and management. This collaborative effort across a number of organizations and administrative units was built to leverage existing resources and create new content where readily accessible resources currently don''''t exist. The goals of the HUB are to: * Promote excellence in the quality of clinical research management through education. * Facilitate effective and timely clinical research initiation by improving institutional processes and providing clinical research protocol, regulatory, budget, and financial tools. * Increase awareness of clinical trials in the community through education and community participant recruitment outreach activities. * Interface with institutional/industry partners to support enhanced clinical research practice.

Proper citation: Clinical Research Resource HUB (RRID:SCR_008979) Copy   

•   Source: SciCrunch Registry

https://wiki.nci.nih.gov/display/caGWAS/caGWAS

Too that allows researchers to integrate, query, report, and analyze significant associations between genetic variations and disease, drug response or other clinical outcomes. SNP array technologies make it possible to genotype hundreds of thousands of single nucleotide polymorphisms (SNPs) simultaneously, enabling whole genome association studies. Within the Clinical Genomic Object Model (CGOM), the caIntegrator team created a domain model for Whole Genome Association Study Analysis. CGOM-caGWAS is a A semantically annotated domain model that captures associations between Study, Study Participant, Disease, SNP Association Analysis, SNP Population Frequency and SNP annotations. caGWAS APIs and web portal provide: * a semantically annotated domain model, database schema with sample data, seasoned middleware, APIs, and web portal for GWAS data; * platform and disease agnostic CGOM-caGWAS model and associated APIs; * the opportunity for developers to customize the look and feel of their GWAS portal; * a foundation of open source technologies; * a well-tested and performance-enhanced platform, as the same software is being used to house the CGEMS data portal; * accelerated analysis of results from various biomedical studies; and * a single application through which researchers and bioinformaticians can access and analyze clinical and experimental data from a variety of data types, as caGWAS objects are part of the CGOM, which includes microarray, genomic, immunohistochemistry, imaging, and clinical data.

Proper citation: caGWAS (RRID:SCR_009617) Copy   

•   Source: SciCrunch Registry

http://www.magventure.com

A complete line of non-invasive magnetic stimulation systems designed for clinical examinations and for research in the areas of neurophysiology, neurology, cognitive neuroscience, rehabilitation and psychiatry.

Proper citation: MagVenture: MagPro Magnetic Stimulator (RRID:SCR_009601) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/neuropsychological-testing-ontology/

An ontology that represents neuropsychological assessments such as the Folstein Mini-Mental State Examination (MMSE), the Trail-Making Test, the Hopkins Verbal Learning Test, and the Wechsler Memory Scale. NPT is designed to allow for the integration of results from a variety of neuropsychological tests that assay similar measures of cognitive functioning and provides a set of classes for the annotation of neuropsychological testing data. Neuropsychological testing is an important component in developing the clinical pictures used in the diagnosis of patients with a range of neurological diseases such as Alzheimer''s disease, multiple sclerosis, and following stroke or traumatic brain injury. An initial goal of the NPT project is to test hypotheses about the diagnosis of Alzheimer''s disease based on the results of neuropsychological assessments. NPT is being built in accordance with the OBO Foundry principles. It is as an extension of the Ontology for Biomedical Investigations (OBI), which utilizes both the Information Artifact Ontology (IAO) and the Basic Formal Ontology (BFO). NPT is a corollary project of the Neurological Disease Ontology (ND) and is being developed in collaboration with the developers of the Mental Functioning Ontology (MF).

Proper citation: Neuropsychological testing ontology (RRID:SCR_010283) 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