October 15, 2014

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The Contributions and Challenges of Clinical Data Management (CDM)

A prospective industry view suggests that the role of CDM personnel is in a state of flux. This role is not only about accomplishing routine activities like designing case report forms (paper CRF/eCRF), annotating CRFs, designing databases, entering, validating and  coding data, locking databases, and creating CDISC/analysis datasets, but also about stepping forward to meet all the expectations of the pharma fraternity. Here’s a quick list of some of these expectations:

  • Augment the process of  subject recruitment and retention in clinical trials
  • Establish a vision for subject care, by maintaining subject profile and population health outcomes based on classifications such as - geography, gender, race, and more
  • Extrapolate trial information for future use, with respect to medicine safety and efficacy, subject  profile/disease information/drug price
  • Evolve as a main subsidiary for risk based monitoring, centralized monitoring, and study site support
  • Coalesce clinical trial data with Big Data, to help forecast trial success or to establish brand positioning, etc.
  • Optimize the cost of clinical research with predictive analysis techniques
  • Effectively manage links, alliances, associations and CRO data, based on historic performance and user friendly classifications, in order to help retrieve information by other teams of clinical research
  • Enhance study digitalization for an overall boost in the processes

In most of the organizations, CDM managers have already established the procedural activities. They are, however, still struggling to find the right, most adaptable Clinical Data Management Solutions, which is made up of the right IT infrastructure that can support regulatory mandates.

The available software packages cannot sustain all activities at one time and are not adaptable enough to address constantly evolving regulatory requirements.  Hence, these are not the preferred choice. But if chosen, the cost of licensing, validating, implementing and supporting them are high. When implemented, it takes considerable time to complete the training, and production time also increases because of complicated programming.

Stakeholders believe that primarily two work models can be adopted, to achieve desirable results:

  • Work model 1: Develop a new, customized, low-cost  software with all the capabilities built into it
  • Work model 2: Integrate all individual (existing in-house) software into one common functional platform

The good news is that HCL can deliver tailored and regulatory-compliant support for both models.  HCL can handle every contingency, help enhance data quality and enable timely regulatory submissions, cost-effectively. HCL helps organizations achieve their study/project/program objectives through the use of adaptable technology and the seamless integration of all their processes. And by taking on some of the tasks of the data managers, we free them up to focus on more crucial and strategic missions.