Cytel converted data from Unilever’s cosmetics trials to CDISC SDTM standards with the long-term goal of combining the data from all human trials into a single database using an industry standard format.
One of the largest components of clinical trial data is laboratory data. Developing a standard lab data format is critical to achieving CDISC’s mission of creating standard data models that support the end-to-end data flow of clinical trials, from the data sources into an operational database and through to analysis and submission.
The TRANSFoRm eHealth solution for clinical trial management collects Patient Reported Outcome Measurement (PROM) data from web and mobile (mHealth) platforms, CRF data extracted from electronic health records (EHRs), and data entered into CRFs by researchers. The PROM software permits remote trial data collection from patients suffering from chronic diseases, and uses algorithms to trigger alarms if the patients need medical attention. The ability to provide this service remotely reduces healthcare costs, while improving quality of life by minimizing disruption to patients’ lives. The system relies on the ODM standard to generate its questionnaire-based, data-collection instruments, including mHealth forms running on Apple’s iOS-based iPhones or Android phones.
CDISC served as a key stakeholder, providing input to the development of Common Protocol Template (CPT). CPT aligns with NIH/FDA-developed Template connecting the parallel universes of clinical care and research as stated by the FDA Commissioner during the CDISC/FDA strategy session in August 2016.
The Immunology Database and Analysis Portal (ImmPort) has been developed under the Bioinformatics Integration Support Contract (BISC) Phase II by the Northrop Grumman Information Technology Health Solutions team for the National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID), Division of Allergy, Immunology, and Transplantation (DAIT). Immport is based on SDTM and is the largest database of data flow.
The Coalition Against Major Diseases (CAMD) used CDISC standards to develop a database that enables pooling of data from different sources to create an Online Data Repository for Alzheimer’s with the aim of supporting accelerated drug development.
Alzheimer’s Disease trial simulation tool was built using CDISC standardized data allows researchers to optimize the design of new trials.
CDISC Standards facilitated the interoperability of datasets in a data sharing platform to foster the development of a disease progression model for Duchenne Muscular Dystrophy. The Duchenne Parent Project wrote a corresponding blog about the need for CDISC standards in their research
A team from the Worldwide Antimalarial Resistance Network (WWARN), University of Oxford, and Infectious Diseases Data Observatory (IDDO) led by Dr. Laura Merson applied CDISC standards in field research data collection and aggregation leading to new treatment recommendations on how low-weight children suffering from malaria in sub-Saharan Africa are treated. These updated guidelines included increasing dosing for this pediatric weight class resulting in a reduction of mortality in these vulnerable patients.
The Multiple Sclerosis Outcomes Assessments Consortium (the Critical Path Institute and the National MS Society) use CDISC standards to standardize and analyze MS data to qualify a new measure of disability as a primary or secondary endpoint for future trials of MS therapies
Application of CDISC Standards has supported the discovery of clinical research biomarkers for Parkinson’s Disease — the evidence for which had been hidden in non-standardized datasets for years prior to their standardization, aggregation, and analysis. These biomarkers now enable researchers to identify diseases early, when intervention may be possible.
Application of CDISC Standards has supported the discovery of clinical research biomarkers for polycystic kidney disease —the evidence for which had been hidden in non-standardized datasets for years prior to their standardization, aggregation, and analysis. These biomarkers now enable researchers to identify diseases early, when intervention may be possible.
CDISC developed a standard for Traumatic Brain Injury under the Coalition for Accelerating Standards and Therapies (CFAST) initiative, a collaboration with C-Path, with expert contribution from members of the TBI Endpoints Development (TED) Initiative and Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) investigator communities, and generous support from One Mind for Research.
The CDISC TBI standards will help catalyze awareness of the types of clinical information that may be relevant to capture, in terms of clinical measures and biomarkers in TBI studies
The Critical Path Institute used CDISC standards to create an aggregated TB Clinical Trial Data-Sharing Platform to enable more efficient and effective drug development