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https://sites.google.com/site/p2tconsortium/

A three-member pharmaceutical industry consortium that aims to provide a new platform to improve access to information about clinical trials for patients and providers. The platform aims to enhance the existing clinicaltrials.gov by providing more detailed and patient-friendly information about available trials and embedding a machine-readable target health profile to improve the ability of healthcare software to match individual health profiles with applicable clinical trials. Using clinicaltrials.gov as its foundation and Eli Lilly''''s Application Programming Interface (API), the consortium is focused on creating an open platform to make this data more amenable to patients and providers, as well as creating an opportunity to integrate a patient''''s electronic health record into the clinical trial matching service. This feature will allow patients to search for trials using their own Blue Button data. The following features are planned add-ons to clinicaltrials.gov: * Target Profile is a machine readable query, that can be executed against an electronic file (or record) with patient health data such as an Electronic Health Record (EHR), an Electronic Medical Record (EMR) or Personally Controlled Health Record (PCHR) * Augmented Content is public, IRB approved information about the study that has not been published on clinicaltrials.gov, and that is shared with / targeted for patients with a matching Target Profile. The following are the incremental goals of the consortium: * Advancement of the Lilly API platform to support read/write interaction and additional data objects and information. * The initial 3 sponsor organizations - Lilly, Pfizer and Novartis - will upload Target Profiles for a select set of clinical trials. A Target Profile is a machine interpretable description of the characteristics of patients who may qualify for that trial i.e. a query that can be executed against a patient''''s electronic health record or personal health record. Additionally, sponsors of clinical research studies will also be able to upload Augmented Content to the Lilly Platform to supplement information on clinicaltrials.gov with additional, patient-focused information about the study, e.g., a study brochure and practical information on how to contact investigational sites. * A matching service, developed by Corengi, will compare Target Profiles to a de-dentified personally controlled health record (PCHR), represented by patient''''s Blue Button Plus CCDA XML document. * Integration into a patient community platform from Avado for providing the patient PCHR and presenting the results of the match service. The patient will be able to explore the respective matching studies for additional information and next steps such as contacting a nearby investigator clinic or hospital. The first demo of the prototype was made available on June 2014, built on a database of anonymized patient health records from different clinical research studies sponsored by Lilly, Novartis, and Pfizer. Other website: http://portal.lillycoi.com/

Proper citation: Patients to Trials Consortium (RRID:SCR_003877) Copy   

•   Source: SciCrunch Registry

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

Ontology of SNOMED (Systematized Nomenclature of Medicine) clinical terms.

Proper citation: Systematized Nomenclature of Medicine - Clinical Terms (RRID:SCR_003915) Copy   

•   Source: SciCrunch Registry

http://www.rcpsych.ac.uk/pressparliament/podcasts.aspx

Each month our podcast team will be broadcasting the very latest breakthroughs and discoveries in neurosciences, psychiatry and psychology.

Proper citation: Royal College of Psychiatrists Podcasts (RRID:SCR_003913) Copy   

•   Source: SciCrunch Registry

http://altbibl.io/dst4l/

An experimental course and blog offered by the Harvard-Smithsonian Center for Astrophysics John G. Wolbach Library and the Harvard Library to train librarians to respond to the growing data needs of their communities. Data science techniques are becoming increasingly important to all fields of scholarship. In the hands-on course, librarians learn the latest tools for extracting, wrangling, storing, analyzing, and visualizing data. By experiencing the research data lifecycle themselves, librarians develop the data savvy skills that can help transform the services they offer. Material will be made available via the DST4L website as it progresses.

Proper citation: Data Scientist Training for Librarians (RRID:SCR_004124) Copy   

•   Source: SciCrunch Registry

http://gigadb.org/

Repository to host data and tools associated with articles published by GigaScience & GigaByte journals. GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support an article or study. Through their association with DataCite, each dataset will be assigned a DOI that can be used as a standard citation for future use of these data in other articles by the authors and other researchers. Datasets in GigaDB all require a title that is specific to the dataset, an author list, and an abstract that provides information specific to the data included within the dataset. Detailed information about the dataset is curated by dedicated biocurators in collaboration with the article authors at the time of publication of the associated manuscript to ensure full transparency and reproducibility of all journal articles published in GigaScience and GigaByte journals.

Proper citation: GigaDB (RRID:SCR_004002) Copy   

•   Source: SciCrunch Registry

http://dash.harvard.edu/

Harvard University''s central service for sharing and preserving work. In addition to the scholarly journal articles targeted by Harvard''s several open access resolutions, DASH maybe used to self-archive manuscripts and materials. DASH supports a variety of file formats, and users are encouraged to deposit related materials with manuscripts (including data, images, audio and video files, etc.) When users deposit their work in DASH, it becomes visible to colleagues around the world by virtue of metadata harvesting, Google Scholar, and other indexing services. Higher visibility leads to higher rates of citation and impact. When users post early versions of their work, before publication, they establish intellectual priority sooner. Users act in their own best interests by taking part in the University''s mission to share and preserve the knowledge produced there. Because Harvard now has a prior, non-exclusive license to faculty journal articles in schools with open access policies, those faculty members are required to act accordingly when publishing journal articles, either by attaching an addendum to their publication agreement or obtaining a waiver. They then must deposit the publication in DASH.

Proper citation: Digital Access to Scholarship at Harvard (RRID:SCR_004122) Copy   

•   Source: SciCrunch Registry

https://rarediseases.org/organizations/nihoffice-of-rare-disease-research/

Organization which develops and maintains a centralized database on rare disease clinical research supported by the NIH. It also stimulates rare disease research by supporting scientific workshops and symposia, responds to requests for information on highly technical matters and matters of public policy, provides information to the Office of the Director on matters relating to rare diseases and orphan products, and coordinates and serves as a liaison with Federal and non-Federal national and international organizations.

Proper citation: Office of Rare Diseases Research (RRID:SCR_004121) Copy   

•   Source: SciCrunch Registry

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

A structured controlled vocabulary of mutant and transgenic mouse pathology phenotypes

Proper citation: Mouse Pathology Ontology (RRID:SCR_003950) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/NHSQI2009

Ontology to organise a 2009 set of over 200 NHS quality indicators from different sources. Relationships between indicators, a basic set of inclusion / exclusion criteria, clinical pathway, clinical code and purpose (per 1992 Institute of Medicine, originally intended to categorise clinical guidelines) are identifies and made searchable.

Proper citation: NHS Quality Indicators (RRID:SCR_004005) Copy   

•   Source: SciCrunch Registry

https://www.corengi.com/

A comprehensive, free, and interactive platform to help individuals discover more about clinical trials that may be appropriate for them for a variety of diseases. The platform allows stakeholders within the clinical trials community (investigators, site personnel, sponsors, and disease advocates) to engage with potential enrollees and educate them about specific clinical trials. They have identified some of the most commonly used criteria for the clinical trials in each disease. Using these criteria, they developed a questionnaire for a single disease. Then, looking at just those questions, they can start to get a sense of which clinical trials might be appropriate for a particular person which is a helpful to start to narrow down the list of potentially appropriate trials. All clinical trials that are posted on www.clinicaltrials.gov for the diseases that Corengi covers will be on the website.

Proper citation: Corengi (RRID:SCR_003942) Copy   

•   Source: SciCrunch Registry

http://www.forebrain.org

Portal on the evolution of the Human Forebrain with schematically depicted sequential age levels of cortical evolution: Staggered Dual Parameter Grid, Growth Rings of the Neocortex, Growth Shells of Thalamus, Major Nuclei of the Thalamus, Dual Parameter - Grid, Types of Neocortical Lamination, and Rolf Hasslers Hexa-Partition of Unit Thalamic Inputs. The cytoarchitectonic subdivisions of both the thalamus and the neocortex are topographically defined in terms of the variables of phylogenetic age and input specificity. The cortical and thalamic parcellations of Brodmann, von Economo and Hassler are each quantitatively correlated to a specific Cartesian coordinate value designating discrete levels for both age and input basic parameters. The variable of phylogenetic age is represented in the cortex by the five circumferential growth rings demonstrated by Sanides, plus an additional growth ring detected intermediate to the fifth and sixth age levels and designated as prekoniocortex. The paleocortex and the archaecortex are the two primordial neocortical precursors that form the mammalian neocortex. In contrast to the arrangement in the planar cortex, six phylogenetically distinct growth shells are detected in the three-dimensional thalamus and are designated after the corresponding schematic levels of Rolf Hassler''s paradigm of hexapartition of unit-thalamic inputs. The subthalamus and the epithalamus analogously represent the primordial diencephalic precursors of the mammalian dorsal thalamus, Both the neocortex and the dorsal thalamus evolved in response to the necessity for a more comprehensive blending of inputs from differing neuraxial levels. Unlike the age variable, the parameter of input specificity is most readily apparent in the dorsal thalamus; which is the site of termination for each major forebrain input. Accordingly, the fourteen individual units of the parameter of input specificity are designated after each of the specific input classifications projecting discretely to circumscribed thalamic sectors, An identical complement of input parameter levels also occurs in the cortex by way of thalamic relay across the internal capsule. Furthermore, each thalamic nucleus of specific parameter coordinates directs its main projection to cells of the cortex displaying identical coordinate values, establishing forebrain interconnectivity as an additional function of the dual parameter paradigm.

Proper citation: EVOLUTIONARY FOUNDATIONS FOR THE HUMAN FOREBRAIN (RRID:SCR_004199) Copy   

•   Source: SciCrunch Registry

https://www.bigtencrc.org/

A consortium that aims to transform cancer research through collaborative oncology trials that leverage the scientific and clinical expertise of the Big Ten universities. The goal is to align the conduct of cancer research through collaborative, hypothesis-driven, highly translational oncology trials that leverage the scientific and clinical expertise. The clinical trials that will be developed will be linked to molecular diagnostics, enabling researchers to understand what drives the cancers to grow and what might be done to stop them from growing. The consortium also leverages geographical locations and existing relationships among the cancer centers. One of the consortium's goals is to harmonize contracts and scientific review processes to expedite clinical trials. The consortium will only focus on phase 0 to II trials because larger trials - even a randomized phase II trial - are difficult to conduct at a single cancer center.

Proper citation: Big Ten Cancer Research Consortium (RRID:SCR_004025) Copy   

•   Source: SciCrunch Registry

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

A reference ontology of classical physics as applied to the dynamics of biological systems. It is designed to encompass the multiple structural scales (multiscale atoms to organisms) and multiple physical domains (multidomain fluid dynamics, chemical kinetics, particle diffusion, etc.) that are encountered in the study and analysis of biological organisms.

Proper citation: Ontology of Physics for Biology (RRID:SCR_004144) Copy   

•   Source: SciCrunch Registry

http://www.euadr-project.org/

Consortium that created the capability to detect Adverse Drug Response (ADR) signals by creating the infrastructure for large-scale monitoring of drug safety using electronic health records (EHR). The platform leverages EHR''''s comprising demographics, drug use and clinical data of over 30 million patients from several European countries. Special attention was given to patient groups that are not routinely involved in clinical trials, for ethical or practical reasons (e.g. pregnant women, elderly people, people using many drugs simultaneously, and children). This project also studies and compares a number of different techniques that all aim to detect unexpected or disproportional rates of events. The algorithms that they studied originate not only from the field of (pharmaco)epidemiology, but also from fields such as bio-terrorism, machine learning, and classical signal detection. EU-ADR specific objectives are: To detect events, To relate these events to drugs, To develop hypothesis that explain adverse events, To detect adverse events earlier, and To avoid false positives. The web-based platform is available at https://bioinformatics.ua.pt/euadr/ EU-ADR has contributed to the ability to conduct better drug safety studies based on the re-use of healthcare data. By facilitating the early detection of adverse drug reactions, but also providing key information on populations at risk, potential drug interactions, potential underlying mechanisms and intervening pathways in adverse events, etc., the project will allow for improved and more complete information to be available for drug and healthcare delivery, leading to increased patient safety and its associated cost savings. The EU-ADR system can be considered as a complementary tool to already existing pharamcovigilance systems. Should the system be widespread in the long term, it has the potential to contribute to the development of future electronic health record systems, insofar as the expected benefits of these IT tools are only fully attainable when EHRs develop themselves in consistency, richness and formats that allow them to be subject of such tools. In anticipation, EU-ADR has been designed to be modular and scalable, so that different EHR databases (other than those participating in the Consortium) can be progressively enlisted in the future, adopt the software for data extraction and therefore become susceptible of exploitation by the system, for maximum global effect.

Proper citation: EU-ADR (RRID:SCR_004028) Copy   

•   Source: SciCrunch Registry

http://www.compact-research.org/

Consortium to reduce delivery and targeting bottlenecks for developing novel innovative biopharmaceutical based medicines. The project aims to shed new light on the obstacles biopharmaceuticals (medicines based on biological molecules such as proteins, peptides or nucleic acids) need to overcome to get to where they are needed in the body. The team will then use this information to develop and validate biopharmaceutical formulations to deliver these novel drugs to their targets. By finding more effective ways of administering these biopharmaceutical drugs, and improving their ability to travel through the body to where they are needed, COMPACT will allow more patients to benefit from biopharmaceuticals. Furthermore, designing less invasive administration routes and reducing the dose (and therefore the side effects) and frequency of administration will help to improve patient compliance with treatments.

Proper citation: COMPACT (RRID:SCR_003850) Copy   

•   Source: SciCrunch Registry

http://danstem.ku.dk/

Center consisting of 9 research groups who all address basic questions in stem cell and developmental biology with the overall aim of developing new stem cell-based therapeutic approaches for diabetes and cancer. DanStem comprises two sections: * The Novo Nordisk Foundation Section for Basic Stem Cell Biology (BasicStem) * The Section for Strategic Translational Stem Cell Research and Therapy (TransStem) DanStem was established as a result of a series of international recruitments coupled with internationally recognized research groups focused on insulin producing beta cells and cancer research already located at the University of Copenhagen. They all have well-established, international collaborations and actively participate in several international scientific consortia. DanStem is also active in training undergraduates, PhD students and postdocs.

Proper citation: DanStem (RRID:SCR_004021) Copy   

•   Source: SciCrunch Registry

http://www.mcewencentre.com/

Center aiming to be a catalyst for regenerative medicine by facilitating collaboration, supporting research, and promoting awareness of the field. The center includes 15 scientists at five Toronto hospitals, as well as the University of Toronto, currently working to accelerate the development of more effective treatments for conditions such as heart disease, diabetes, respiratory disease and spinal cord injury. They collaborate with many other research institutions throughout North America, Europe and the Asia / Pacific region. The research is powered by a team of recent doctoral graduates recruited from around the world that are selected through a competitive process. They are a critical tool for supporting the work of McEwen Centre, allowing them to find medical breakthroughs faster.

Proper citation: McEwen Centre for Regenerative Medicine (RRID:SCR_004020) Copy   

•   Source: SciCrunch Registry

http://www.cihr.gc.ca/e/46475.html

Consortium that will be the premier research hub for all aspects of research involving neurodegenerative diseases that affect cognition in aging - including Alzheimer's disease. They will promote high impact, inter-institutional and interdisciplinary collaboration through a pan-Canadian approach, and will position Canadian researchers to lead and participate in a new wave of national and international initiatives with congruent goals. The consortium focuses research into the basic mechanisms of neurodegenerative diseases, accelerating the development of tools that can be used to assist in the diagnosis and treatment of the diseases. The intended outcome of these tools is to improve the quality of life and services patients with neurodegenerative diseases. As part of the Canadian contribution to the International Collaborative Research Strategy for Alzheimer's disease, the consortium brings together Canadian government agencies (federal and provincial), foundations, pharmaceutical companies, philanthropists and international stakeholders to identify if there are common causes and risk factors to neurodegenerative diseases. The consortium is focused on three themes: * Primary Prevention aimed at preventing the disease from developing * Secondary Prevention focused on delaying the clinical manifestations of the already developing disease * Quality of Life designed for helping individuals, caregivers and the health system in the context of a clinically developed disease.

Proper citation: Canadian Consortium on Neurodegeneration in Aging (RRID:SCR_003846) Copy   

•   Source: SciCrunch Registry

https://www.aakp.org/

Association of kidney patients focused on patient-centered education, advocacy and community. They share educational pieces covering every level of kidney disease, advocate for improved access to high-quality health care through regulatory and legislative reform at the federal level, and make an effort to bring kidney patients together to promote community, conversations and to seek out services that help maximize patients'' everyday lives.

Proper citation: American Association of Kidney Patients (RRID:SCR_003965) Copy   

•   Source: SciCrunch Registry

http://clinicaltrials.gov/show/NCT01211678

A consortium evaluating a new biomarker screening test that might help identify patients with rheumatoid arthritis (RA) who are unlikely to benefit from anti-tumor necrosis factor-alpha (TNFalpha) medications. BATTER-UP will enroll around 1,000 patients being treated by one of several marketed anti-TNF RA drugs: Enbrel, Remicade, Humira, Simponi, or Cimzia. Through data analyses and predictive response modeling, the consortium aims to better understand which patients with RA will derive the greatest benefit from TNF inhibitors. The investigators in this observational study will attempt to validate an 8-gene biomarker set based on work by Biogen Idec researchers as likely to predict anti-TNF responsiveness in patients with RA. In preliminary results, the 8-gene biomarker set predicted with 89% accuracy individuals who did not reach European League Against Rheumatism (EULAR) Disease Activity Score (DAS)-28 good response after 14 weeks of treatment. The 8 genes included in the screen are CLTB, MXRA7, CXorf52, COL4A3BP, YIPF6, FAM44A, SFRS2, and PGK1. Biological samples and clinical outcome information will be used to confirm and extend the utility of previously published biomarkers that can predict response to anti-TNF agents. These data may also generate new hypotheses for further testing. The BATTER-UP samples and data will be established as a reference set for investigation of personalized medicine in RA. The study will be a resource of DNA and other biological materials that can be investigated for biomarkers in the future as new technologies arise.

Proper citation: Biomarkers of Anti-TNF Treatment Efficacy in Rheumatoid Arthritis - Unresponsive Populations (RRID:SCR_004019) Copy   

•   Source: SciCrunch Registry