Tools   Select Another Resource Report Type

http://earip.eu/

Consortium that convenes asthma experts from across Europe to define research gaps to reduce the impact of asthma. The project activities range from basic cell science research, to assessing and improving European healthcare systems. Their activities include workshops, prioritization exercises, consensus strategies, and the development and publication of a set of recommendations about what's needed to reduce asthma deaths and hospitalizations. The eventual goal is to have a comprehensive R&D roadmap for asthma. EARIP will target a number of asthma research areas to ensure a comprehensive overview of all current research strategies from across Europe is included in the project road map. These include: * Research into biological targets, aiming to discover new targets and better define the role of existing biological targets * Identify new systems, models and tools for phenotypic stratification * Develop better and more efficient healthcare systems across Europe * Define and develop new diagnostic tools * Assess and improve patient self-management systems and provide suggestions for how these can be developed * Identify how to establish a European Innovation Partnership (EIP) for the management of asthma * Establish a European research network of clinical asthma research facilities

Proper citation: EARIP (RRID:SCR_003854) Copy   

•   Source: SciCrunch Registry

http://www.ted.com/

A nonprofit devoted to spreading ideas, usually in the form of short, powerful talks (18 minutes or less). TED began as a conference where Technology, Entertainment and Design converged, and today covers almost all topics - from science to business to global issues - in more than 100 languages. Meanwhile, independently run TEDx events help share ideas in communities around the world.

Proper citation: TED (RRID:SCR_003739) Copy   

•   Source: SciCrunch Registry

https://www.pharmatching.com/

A matchmaker portal for the pharmaceutical industry worldwide offering a directory and contact platform. This includes a database of ten thousands of profiles of companies offering pharma services as well as a selection of companies including niche providers delivering the service of interest. The platform is used to search for human medicinal products, veterinary medicinal products, cosmeceuticals, nutriceuticals, medical devices, and diagnostics. The company''s platform also enables users to post their service requests, service offers, and APIs/intermediates; and interact with other users. In addition, it offers advice and operational support services for outsourcing and inlicensing processes, such as strategic, scientific, and regulatory advice related to due diligence and decision making of research and development, sourcing, and M and A processes; conduct of third party GMP and pharmacovigilance audits; customized interim solutions; and qualified person functions for GMP and pharmacovigilance. The company also serves various sectors of the life science industry, such as contract manufacture, laboratory investigations and contractual testing, clinical research organizations and pre-clinical research organizations, consulting and legal counseling, logistics and distribution, education, marketing, IT, and investment and financing sectors; and small and medium enterprises/pharma, academic, public institutions, and freelancers. (Bloomberg Businessweek)

Proper citation: Pharmatching (RRID:SCR_003897) Copy   

•   Source: SciCrunch Registry

http://www.lhasalimited.org/

A not-for-profit membership organization and educational charity that facilitates collaborative data sharing projects in the pharmaceutical, cosmetics and chemistry-related industries specializing in the development of expert computer systems for toxicity and metabolism prediction. They provide a number of extensive and continually updated knowledge bases and the software needed to interrogate them. Its charitable aims include the sponsorship of activities that advance scientific knowledge and understanding and they regularly support computational chemistry events and initiatives that are of interest to Lhasa Limited members and the wider scientific community. All applications for sponsorship will be considered on their individual merits.

Proper citation: Lhasa Limited (RRID:SCR_003775) Copy   

•   Source: SciCrunch Registry

http://www.transformproject.eu/portfolio-item/d6-2-clinical-research-information-model/

A clinical research information model for the integration of clinical research covering randomized clinical trials (RCT), case-control studies and database searches into the TRANSFoRm application development. TRANSFoRm clinical research is based on primary care data, clinical data and genetic data stored in databases and electronic health records and employs the principle of reusing primary care data, adapting data collection by patient reported outcomes (PRO) and eSource based Case Report Forms. CRIM was developed using the TRANSFoRm clinical use cases of GORD and Diabetes. Their use case driven approach consisted of three levels of modelling drawing heavily on the clinical research workflow of the use cases. Different available information models were evaluated for their usefulness to represent TRANSFoRm clinical research, including for example CTOM of caBIG, Primary Care Research Object Model (PRCOM) of ePCRN and BRIDG of CDISC. The PCROM model turned out to be the most suitable and it was possible to extend and modify this model with only 12 new information objects, 3 episode of care related objects and 2 areas to satisfy all requirements of the TRANSFoRm research use cases. Now the information model covers Good Clinical Practice (GCP) compliant research, as well as case control studies and database search studies, including the interaction between patient and GP (family doctor) during patient consultation, appointment, screening, patient recruitment and adverse event reporting.

Proper citation: TRANSFoRm Clinical Research Information Model (RRID:SCR_003889) Copy   

•   Source: SciCrunch Registry

http://www.oncotrack.eu/

An international consortium to develop and assess novel approaches to identify and characterize biological markers for colon cancer that will deepen the understanding of the variable make-up of tumors and how this affects the way patients respond to treatment. They will use cutting edge laboratory-based genome sequencing techniques coupled to novel computer modelling approaches to study both the biological heterogeneity of colon cancers (i.e. patient to patient variability) as well as tumor variation within the patient for example, by comparing primary tumors with metastases. This five year project brings together top scientists from European academic institutions offering a wide range of expertise, and partners them with pharmaceutical companies. The project is based on the premise that this genetic and epigenetic information, combined with a description of the molecular pathology of the tumor, will allow OncoTrack to generate a more accurate in-silico model of the cancer cell. This will facilitate the identification of predictive markers that can be used to guide the optimal therapy strategy at the level of the individual patient - and will also provide on-going prognostic guidance for the clinician. This project will not only advance understanding of the fundamental biology of colon cancers but will provide the means and approach for the identification of previously undetected biomarkers not only in the cancer under study, but potentially also in other solid cancers and, in doing so, open the door for personalized management of the oncology patient.

Proper citation: OncoTrack (RRID:SCR_003767) Copy   

•   Source: SciCrunch Registry

http://co.mbine.org/standards/miase

A set of guidelines (community effort) suitable for use with any structured format for simulation experiments to identify the Minimal Information About a Simulation Experiment necessary to enable the reproducible simulation experiments. The Guidelines list the information that a modeller needs to provide to enable the execution and reproduction of a numerical simulation experiment, derived from a given set of quantitative models. MIASE is designed to help modelers and software tools to exchange their simulation settings and to foster collaboration. In 2011, he MIASE guidelines were accepted by researchers from 19 different institutes.

Proper citation: Minimum Information About a Simulation Experiment (RRID:SCR_003800) Copy   

•   Source: SciCrunch Registry

http://www.transformproject.eu/

Project to develop a ''rapid learning healthcare system'' driven by advanced computational infrastructure that can improve both patient safety and the conduct and volume of clinical research in Europe. Three carefully chosen clinical ''use cases'' will drive, evaluate and validate the approach to the ICT (information and communications technology) challenges. The project will build on existing work at international level in clinical trial information models (BRIDG and PCROM), service-based approaches to semantic interoperability and data standards (ISO11179 and controlled vocabulary), data discovery, machine learning and electronic health records based on open standards (openEHR). TRANSFoRm will extend this work to interact with individual eHR systems as well as operate within the consultation itself providing both diagnostic support and support for the identification and follow up of subjects for research. The approach to system design will be modular and standards-based, providing services via a distributed architecture, and will be tightly linked with the user community. Four years of development and testing will end with a fifth year that will be dedicated to summative validation of the project deliverables in the Primary Care setting. In order to support patient safety in both clinical and research settings, significant ICT challenges need to be overcome in the areas of interoperability, common standards for data integration, data presentation, recording, scalability, and security., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: TRANSFoRm (RRID:SCR_003888) Copy   

•   Source: SciCrunch Registry

http://neurotrends.org/

Service that extracts and analyzes methodological information from thousands of published studies across the functional neuroimaging literature. It currently offers searching articles by methodological choices, visualization of methods trends over time, and extraction of methods information from text. It currently includes 282,476 methodological details about 21,562 articles, published between 1992 and 2014. (2014) * Search for articles by title, authors, and methods. * Interactive visualizations of methodological parameters over time, by author, and more. * All data are programmatically accessible through a simple application programming interface. It''s simple to re-analyze the data or integrate with your own application.

Proper citation: NeuroTrends (RRID:SCR_003921) Copy   

•   Source: SciCrunch Registry

http://www.predict-tb.eu/

Consortium to accelerate the search for new, more effective combinations of treatments to tackle Tuberculosis and address pre-clinical research barriers to the discovery and development of new TB drug combinations. To overcome the challenges in Tuberculosis drug development they will create tools to accelerate PK-PD (Pharmacokinetic / Pharmacodynamic) analysis that are connected to clinical outcomes. By addressing the gaps in preclinical information, the consortium aims to provide a framework and tools to facilitate the transition of the best combinations of drugs to late phase development. They aim to develop an integrated set of laboratory-based models that will provide much-needed data to indicate the most appropriate doses and combinations of drugs for patients. In addition, the project will generate a comprehensive database of patient data from previous and on-going clinical trials for use as a reference for evaluating the performance of combination anti-TB drug regimens in these newly developed laboratory models. Ultimately, they aim to enable researchers to be able to use the information generated by the novel models to design better clinical trials involving TB patients. The aims of the consortium: * To systematically evaluate two successive panels of representative anti-tuberculosis drugs (licensed and novel) using a suite of standard, novel and enhanced preclinical model systems, with respect to performance in clinical trials * To refine the set of preclinical systems on the basis of these results in order to identify and define the currently optimal critical path in discovery and pre-clinical development for tuberculosis. * To develop an integrated PK-PD / Disease modelling and simulation framework for tuberculosis which will facilitate prediction of optimal combinations and design of clinical studies.

Proper citation: Predict-TB (RRID:SCR_003766) Copy   

•   Source: SciCrunch Registry

http://www.ucsd.tv/stein/

Videos and podcasts presenting the latest innovative research being conducted by the Stein Institute for Research on Aging medical faculty, with the aim of promoting healthy aging. Additionally, many of the public lectures from the Public Lecture Series are also available on UCSD-TV's website video on demand programming. The Lecture series allows affiliated faculty members of the Stein Institute for Research on Aging and other scientists from the UCSD School of Medicine, as well as individuals from surrounding academic and research institutions, to present the latest findings in their respective fields of expertise and share their present work with the general community. All of these lectures focus on topics related to healthy aging or age-related diseases.

Proper citation: Stein Institute for Research on Aging Video Archive (RRID:SCR_003761) Copy   

•   Source: SciCrunch Registry

http://www.etriks.org/

Research informatics and analytics platform for the IMI OncoTrack consortium.

Proper citation: eTRIKS (RRID:SCR_003765) Copy   

•   Source: SciCrunch Registry

http://www.psidev.info/index.php?q=node/257

Markup language for encoding raw spectrometer output. From 2005-2008 there has existed two separate XML formats for encoding raw spectrometer output: mzData developed by the PSI and mzXML developed at the Seattle Proteome Center at the Institute for Systems Biology. It was recognized that the existence of two separate formats for essentially the same thing generated confusion and required extra programming effort. Therefore the PSI, with full participation by ISB, has developed a new format by taking the best aspects of each of the precursor formats to form a single one. It is intended to replace the previous two formats. This new format was originally given a working name of dataXML. The final name is mzML.

Proper citation: mzML (RRID:SCR_003763) Copy   

•   Source: SciCrunch Registry

http://www.predect.eu/

Project that aims to create more appropriate in vitro platforms for target validation and drug discovery for breast, prostate and lung cancers. Laboratory platforms to validate whether target modulation would provide a clinical benefit are usually highly reductionist, often using long-established cell lines growing in 2 dimensions in vitro. These models do not reflect the complexity and heterogeneity of a tumor in situ, where biochemical pathways are wired with connections to the complex tumor environment provided by the stroma. PREDECT has the goal of comparing the pathological and molecular profiles of novel in vitro platforms with those of human tumors. Because obtention of clinical material presents both logistics and quality problems for ongoing and intense studies of target validation, PREDECT aims to use material from genetically engineered mouse models, and some advanced xenografts, whose pathology and molecular profiles closely match cohorts of human tumors. PREDECT hopes to provide more appropriate in vitro platforms both for target validation and subsequent preclinical studies which will replace a current cascade of tests which are poorly predictive of clinical activity. The project is expected to shift paradigms in cell biology as well as in preclinical target validation where it should permit greater predictivity of drug efficacy in patient cohorts.

Proper citation: PREDECT (RRID:SCR_003883) Copy   

•   Source: SciCrunch Registry

http://www.tipharma.com/

A not-for-profit organization that initiates and manages drug development consortia that involve the pharmaceutical industry, academia, and the Dutch Government. The aim of all their consortia is to conduct pre-competitive research while strengthening the Netherlands' international reputation for drug development. The consortia are focused on addressing therapeutic areas that are listed as priority areas by the World Health Organization including: autoimmune diseases, cardiovascular diseases, cancer, infectious diseases, and diseases of the brain. The consortia are also focused on enabling: therapeutic target discovery, validation, and animal models; lead selection and in-silico modeling; predictive drug disposition and toxicology; biomarkers and biosensors; drug formulation, delivery, and targeting; and, production technologies. TI Pharma consortia aim to improve the efficiency of the drug-development process, with a focus on advancing regulatory science. In addition to research, TI Pharma also has objectives to train and educate scientists in the Netherlands on the drug discovery and development processes, as well as on entrepreneurship. Participants include: all Dutch universities and academic medical centers, more than 30 industrial partners, small-to-medium sized companies, and representatives from the Dutch Medicines Evaluation Board (Netherlands regulatory body for drugs).

Proper citation: TI Pharma (RRID:SCR_003758) Copy   

•   Source: SciCrunch Registry

http://www.alzheimer-europe.org/Research/PharmaCog

Project aiming to tackle bottlenecks in Alzheimer''''s disease research and drug discovery by developing and validating new tools to test candidate drugs for the treatment of symptoms and disease in a faster and more sensitive way. They will provide the tools needed to define more precisely the potential of a drug candidate, reduce the development time of new medicines and thus accelerate the approvals of promising new medicines. By bringing together databases of previously conducted clinical trials and combining the results from blood tests, brain scans and behavioral tests, the scientists will develop a ''''signature'''' that gives more accurate information on the progression of the disease and the effect of candidate drugs than current methods do. The scientists will conduct parallel studies in laboratory models, healthy volunteers and patients in order to better predict good new drugs as early as possible. This will enable them, for instance, to find out how memory loss in Alzheimer''''s disease can be simulated in healthy volunteers, for example with sleep deprivation or drugs that temporarily affect the memory, in order to test the effect of candidate-medicines early in the drug development process.

Proper citation: PharmaCog (RRID:SCR_003878) Copy   

•   Source: SciCrunch Registry

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://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://www.antilope-project.eu/

Consortium focused on making electronic health data more interoperable, both within and outside of Europe, with the intention to create, validate, and disseminate standard methods to test and certify electronic health solutions and services. In particular it will: Drive the adoption of recognized sets of profiles and underlying standards for eHealth interoperability, and improve the impact of the EU and International eHealth standards development process; Define and validate testing guidelines and common approaches on Interoperability Labelling and Certification processes at European and at National / Regional level. Four work packages were created to provide guidelines, recommendations and frameworks based on a set of use cases, related profiles and standards, Interoperability Quality Management System, testing guidelines and Certification process. All the deliverables will be presented for validation and promotion by organizing workshops across Europe.

Proper citation: Antilope Project (RRID:SCR_003829) 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