Clinical trial data management involves gathering, refining and managing the data of an individual, according to regulatory requirements. It supports the production of high-quality and reliable data from clinical trials and significantly reduces the time taken for the development and commercialisation while maintaining the quality standards.
Leading clinical data management companies
Clinical Trials Arena has listed some of the leading clinical data management consultants based on its experience in the sector.
The information provided is drafted for pharmaceutical executives, clinical data co-ordinators and data managers, analysts, support engineers, clinical research associates, pharmacovigilance associates, as well as any other individual involved in the clinical data management services.
The document contains detailed information on relevant suppliers and their product lines, alongside contact details to aid your purchasing decision.
The list comprises a range of service providers including, but not limited to:
- Data management
- Contract research
- e-clinical systems for clinical trials
Clinical data management tools
Several clinical research data management software tools are available for clinical data management, of which RAVE, ORACLE CLINICAL, eClinical Suite and CLINTRIAL are the most used. Some of the widely utilised open-source software tools are openCDMS, OpenClinica and TrialDB. The e-clinical software for e-clinical trials and data management services are also the integrated, user-friendly software used in the pharmaceutical, life sciences and healthcare industries.
The software tools, which utilise modern information technology (IT) infrastructure, help to maintain audit trail records to prevent any data management discrepancies in regulatory submission studies. Pharmaceutical companies mostly use commercial software tools while some pharmaceutical firms use customised tools for their requirements.
Clinical data management training
Training in clinical data management is essential to understand and implement the concepts and methods of data collection, storage and distribution in clinical research.
It helps in selecting an optimal clinical trial design with reduced trial duration and expenses, better understanding the risk factors for informed decision making, minimising the uncertainties in clinical operations, and helping statisticians gain insights for better product development.