Clinical Data Management: Challenges & Opportunities "A"

One of Albert Einstein’s many great quotes during his life included the following: ““The distinction between past,present and future is only a stubbornly persistent illusion”.This quote is a perfect micr
ocosm for data standards in theclinical research industry.Over the last decade the clinical research industry hasattempted to work toward a common data standard with thegoal of accelerating drug development by improving the data collection, transformation, analysis, and submissionprocess. The adoption of industry widestandards has been lethargic and led toa plethora of challenges. This paper
will provide a history of clinical data standards, the role of SAS® in these standards, and a forward view on how standards might evolve over the next decade. 

To maintain a competitive position, the biopharmaceutical industry has been facing the challenge of increasing productivity both internally and externally. As the product of the clinical development process, clinical data are recognized to be the key corporate asset and provide critical evidence of a medicine’s efficacy and safety and of its potential economic value to the market. It is also well recognized that using effective technology-enabled methods to manage clinical data can enhance the speed with which the drug is developed and commercialized, hence enhancing the competitive advantage. The effective use of data-capture tools may ensure that high-quality data are available for  early review and rapid decision-making. A well-designed, protocol-driven, standardized, site workflow-oriented and documented database, populated via efficient data feed mechanisms, will ensure regulatory and commercial questions receive rapid responses. When information from a sponsor’s clinical database or data warehouse develops into corporate knowledge, the value of the medicine can be realized. Moreover, regulators, payer groups, patients, activist groups, patient advocacy groups, and employers are becoming more educated consumers of medicine, requiring monetary value and quality, and seeking out up-todate medical information supplied by biopharmaceutical companies. All these developments in the current biopharmaceutical arena demand that clinical data management (CDM) is at the forefront, leading change, influencing direction, and providing objective evidence. Sustaining an integrated database or data repository for initial product registration and subsequent postmarketing uses is a long-term process to maximize return on investment for organizations. CDM should be the owner of driving clinical data-cleaning process in consultation with other stakeholders, such as clinical operations, safety, quality assurance, and sites, and responsible for building a knowledge base to add potential value in assisting further study designs or clinical programs. CDM needs to draw on a broad range of skills such as technical, scientific, project management, information technology (IT), systems engineering, and interpersonal skills to tackle, drive, and provide valued service in managing data within the anticipated e-clinical age. Commitment to regulatory compliance is required in this regulated industry; however, a can-do attitude with strong willingness to change and to seek ways to improve CDM functions and processes proactively are essential to continued success and to ensure quality data-driven productivity.