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Initiative to advance oncology research by enabling collaborative sharing of historical oncology clinical trial data through a universal platform (database). The initiative aims to network all stakeholders in the cancer community researchers, industry, academia, advocacy, and other organizations to share insights and collaborate on issues that could not be solved individually. To do this, they have made efforts to address issues of data privacy, security, intellectual property, resources, and incentives as part of its effort to maximize participation. Data contributions include control arms of clinical trials, and the platform uses data-security precautions and analytics to pool multiple studies associated with the same diagnosis in a manner that seeks to protect the privacy of patients and the security of the data contributed.
Ontology of Medical Diagnostic Categories-Diagnosis Related Groups
Initiative to improve the safety of drugs on the market that utilized information drawn from patient medical record databases and health insurance claims to develop and test methods to detect and evaluate drug safety issues over time. The OMOP pilot project focused on the following objectives: * Defining and evaluating analytical methods that can be used to identify associations between drugs and health-related conditions. * Developing tools for organizing access to and evaluating the usefulness of multiple observational datasets. * Study how information from analyses of observational data can be used to inform ongoing pharmacovigilence efforts. The software tools - packaged as the OMOP Web RL Platform was developed and made available to the public, https://github.com/OMOP . In addition to these data tools, this collaborative research effort discovered methods for using data to reliably identify correlations between individual medical interventions and specific health outcomes. These insights are being used to help inform the FDA Sentinel Initiative as part of the Innovation in Medical Evidence Development and Surveillance (IMEDS) program. The achievements of the program include: * Establishment of a common data model and creation of data characterization tools, and vocabulary mappings * Implementation of Health Outcome of Interest definitions, including a program to implement these definitions as part of the Regularized Identification of Cohorts (RICO) * Release of 14 analysis methods to evaluate the performance of methods and data in identifying drug safety issues
A non-profit foundation that funds basic research and is focused on accelerating the development of myelin repair therapeutics for multiple sclerosis. They have defined a 15-year research plan to develop a drug or drugs and believes its Accelerated Research Collaborative (ARC) model can subsequently be used to accelerate the treatment for all diseases. The ARC framework coordinates and manages the entire therapeutic development continuum from discovery biology to FDA approval. The model works by coordinating multi-disciplinary basic research from academic and government laboratories, systematically validating and derisking potential compounds/targets, and collaborating with pharma partners to increase the probability of successful programs.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Database providing access and limited analysis to the MMGP portal data sets. These include the MMRC funded reference array comparative genomic hybridization (aCGH) and gene expression data and additional public multiple myeloma datasets. The MMGP will be updated with new features such as additional data and analysis tools as they become available.
A personalized medicine initiative to discover biomarkers that can better define the biological basis of multiple myeloma to help stratify patients. This effort hopes to obtain samples from approximately 1,000 multiple myeloma patients and follow them over time to identify how a patient's genetic profile is related to clinical progression and treatment response. As a partnership between 17 academic centers, 5 pharmaceuticals and the Department of Veterans Affairs, the goal of this eight year study is to create a database that can accelerate future clinical trials and personalized treatment strategies. MMRF's CoMMpass Study has the following goals: * Create a guide to which treatments work best for specific patient subgroups. * Share data with researchers to accelerate drug development for specific subtypes of multiple myeloma patients. In order to facilitate discoveries and development related to targeted therapies, the comprehensive data from CoMMpass is placed in an open-access research portal. The data will be part of the Multiple Myeloma Research Foundation's (MMRF) Personalized Medicine Platform combines CoMMpass data with those collected from MMRF's Genomics Initiative. It is hoped that the longitudinal data, combined with the annotated bio-specimens will help provide insights that can accelerate personalized therapies.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. A clinical spinal cord injury network that provides a database of clinical assessment data from spinal cord injured patients. The EMSCI assessment scheme currently consists of the so called core sets: neurological (ISNCSCI), functional (10MWT, 6MWT, TUG, WISCI2) measurements and independence measures (SCIM3). Additional assessments are: neurophysiology (MEP, SSEP, NCV), pain, hand function and an urodynamics.
A structured controlled vocabulary of the anatomy and development of the Japanese medaka fish, Oryzias latipes.
An electronically administered patient-reported outcome (PRO) measure that is a qualified measure of symptoms of acute bacterial exacerbation of chronic bronchitis in patients with chronic obstructive pulmonary disease (ABECB-COPD), for use in phase 2 trials. Refer to the proposed context of use, http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/UCM399682.pdf. Its intent to quantify frequency, severity, and duration of acute exacerbations in clinical trials of COPD including those with chronic bronchitis. It is designed as an electronic diary made up of fourteen items to be completed by the patient each evening just prior to bedtime. (An item-reduction statistical analysis narrowed the questions from 23 to 14.) For more information see, http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/UCM386248.pdf
Serum / plasma biomarkers, Cardiac troponins T (cTnT) and I (cTnI), in safety assessment studies for rats, dogs, and monkeys are qualified biomarkers for the following contexts of use: # When there is previous indication of cardiac structural damage with a particular drug, cardiac troponin testing can help estimate a lowest toxic dose or a highest non-toxic dose to help choose doses for human testing. In this case, cardiac troponins may serve as a clinical chemistry correlate to the histology. For example, in a safety assessment study, lower doses without increases in cardiac troponins may be used to support a no observed effect level (NOEL) identified by histology. # When there is known cardiac structural damage with a particular pharmacologic class of a drug and histopathologic analyses do not reveal structural damage, circulating cardiac troponins may be used to support or refute the inference of low cardiotoxic potential. # When unexpected cardiac structural toxicity is found in a nonclinical study, the retroactive (reflex) examination of serum or plasma from that study for cardiac troponins can be used to help determine a no observed adverse effect level (NOAEL) or lowest observed adverse effect level (LOAEL). The results of this testing may support inclusion of cardiac troponin testing in subsequent safety assessment studies.
Urinary kidney biomarkers, Clusterin and Renal Papillary Antigen-1 (RPA-1), that sponsors may use to determine more conservative NOAELs for estimating starting doses in the initial human clinical trial of a drug that displays nonclinical nephrotoxicity as determined by histopathology. When tested with a limited number of nephrotoxic compounds, the Receiver Operating Characteristic (ROC) analyses showed that urinary clusterin and renal papillary antigen-1 (RPA-1) have better sensitivity and specificity than BUN and creatinine for the detection of specific kidney pathologies in male rats. Clusterin and RPA-1 provide additional and complementary information to BUN, serum creatinine (sCr), and histopathology for the detection of acute drug-induced nephrotoxicity in safety assessment studies.
The Hungarian Society of Clinical Neurgenetics established a nationwide collaboration for prospective collection of human biological materials and databases from patient with neurological and psychiatric diseases. The basic triangle of the NEPSYBANK is the sample, the information and the study management. The present participants of the NEPSYBANK are the Department of Neurology and Psychiatry of the four Medical Universities (in Budapest, Debrecen, Pecs, Szeged) and the National Institute of Psychiatry and Neurology in Budapest. The NEPSYBANK is a disease based biobank collecting both phenotypical and environmental data and biological materials such as DNA/RNA, whole blood, plasma, cerebral spinal fluid, muscle / nerve / skin biopsy, brain, and fibroblast. The target of the diseases is presently (Phase I): stroke syndromes, dementias, movement disorders, motoneuron diseases, epilepsy, multiple sclerosis, schizophrenia, alcohol addiction. In the near future (Phase II.) it is planned to enlarge the scale with headaches, disorders of the peripheral nerves, disorders of neuromuscular transmission, disorders of skeletal muscle, depression, anxiety. DNA/RNA is usually extracted from whole blood, but occasionally different tissues such as muscle, brain etc. can be used as well. The extracting procedures differ among the institutes, but in all cases the concentration and the quality of the DNA/RNA must be registered in the database. Participating institutional biobanks have committed themselves to follow common quality standards, which provide access to samples after prioritization on scientific grounds only. In every case the following data are registered. 1. General data: main bank categories, age, sex, ethnicity, body height, body weight, economic stats, education, type of place of living, marital status, birth complications, alcohol, drugs, smoking. 2. Sample properties (sample ID, type of sample, date of extraction, concentration, and level of purity). General patient data as blood pressure, heart rate, internal medical status, ECG, additional diseases. Disease specific question e.g. in schizophrenia the diagnosis after DSMIV and ICD 10, detailed diagnostic questions after both classification, detailed psychiatric and neurological status, laboratory findings, rating scales, data of neuroimaging, genetic tests, applied medication (with generic name, dose, duration), adverse drug effects and other treatments. The Biobank Information Management System (BIMS) is responsible for linkage of databases containing information on the individual sample donors. If you want to have samples from the NEPSYBANK an application must be submitted containing the following information: short research plan including aims and study design, ethic application with a positive decision, specific demands regarding the right of disposition, agreements with grant organizations which regulate immaterial property, information about financing (academic grants, support from industry). All participants have the right to withdraw their samples through a simple order.
To support Drug Development Tools development efforts, FDA established qualification programs for animal models for use under Animal Rule, biomarkers, and clinical outcome assessments. DDTs are methods, materials, or measures that have potential to facilitate drug development. Examples of DDTs may include, but are not limited to biomarker2 used for clinical trial enrichment, clinical outcome assessment used to evaluate clinical benefit, and animal model used for efficacy testing of medical countermeasures under regulations commonly referred to as Animal Rule3.
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
Project to develop a drug safety database from the pharmaceutical industry legacy toxicology reports and public toxicology data; innovative in silico strategies and novel software tools to better predict the toxicological profiles of small molecules in early stages of the drug development pipeline. The project is creating this pharmaco-toxicological database with an aim to: * Reduce the number of animal tests * Decrease the attrition rates of new drug candidates * Increase the success rate of new molecular entities becoming drugs * Improve the safety of drugs on the market The project consists of three different systems, * eTOX VITIC Database a unified database containing all confidential and non-confidential data collected in eTOX (historical data from the pharmaceutical industry) * ChOX Database a unified database containing public data (literature and public database) * eTOXsys Query and Prediction System an interface providing a uniform access to the two databases (VITIC and ChOX) and to all developed prediction models and systems
Consortium to identify, fund and support breakthrough technologies that will significantly enhance biopharmaceutical R&D productivity and accelerate the development of new safe and efficacious drugs. CQDM is a neutral ground that brings patient groups, academia, governments, biotech and the pharma industry together to work collaboratively on complex medical challenges. Projects supported by the consortium are highly relevant to the pharmaceutical sector and typically address: * Opportunity for new therapeutic approaches and research * Safe and effective new drug development * Enhancing the efficacy of already existing drugs * Reducing costs, time and risks associated with the discovery and development of new drugs Funded projects typically involve multidisciplinary collaborations between research teams that represent both the academic and the private sector, who are mentored by industry scientists provided by the consortium sponsors.
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.
Urinary kidney biomarkers (KIM-1, albumin, total protein, 2-microglobulin, cystatin C, clusterin and trefoil factor-3) that are considered acceptable biomarkers for the detection of acute drug-induced nephrotoxicity in rats and can be included along with traditional clinical chemistry markers and histopathology in toxicology studies. These biomarkers may be used voluntarily as additional evidence of nephrotoxicity in nonclinical safety assessment studies to complement the standard data (BUN and sCr). In ROC analyses, some of these biomarkers showed better sensitivity and specificity than BUN and sCr relative to histopathological alterations considered to be the gold standard when tested with a limited number of nephrotoxicant and control compounds.
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.
Data set of standardized terms used to describe human morphology including definitions of terms for the craniofacies in general, the major components of the face, and the hands and feet. This provides a uniform and internationally accepted terms to describe the human phenotype.