Clinical data management is the actual development, execution, and supervision of plans, programs, policies, and practices which control, deliver, and protect the value of information and data assets in clinical research courses or study. CDM has diverse connectivity with several cross-functional features, which has come a long way over the last few decades. It is a recognized profession that has a growing demand in today’s research world. It is gaining importance even outside the pharmaceutical and medical world.

Despite CDM being a dynamic and complex profession, it continues to grow into a firmly established discipline in its right. It focuses on managing clinical research trial data as a valuable and reliable resource.

 

Challenges in clinical data management

Despite EDC technologies and e-clinical systems have been launched to enhance the different aspects of the data management process, the launch has not caused a rapid rise in the management process’s improvement. The medical device industry, biotechnology, pharmaceutical industry, academia, and government have now understood EDC’s efficiency and benefits. Although the main aim of CDM shall not change, there is no room for doubt that the management process shall transform with the use of EDC and other e-clinical systems. The major challenges include:

  • Clinical form design and balancing needs: There are interdisciplinary several CRF design challenges that involve technology, protocol-driven science, validation, work-flow, and standardization usability for EDC studies. The final report, which is the product of complex computer programs and statistical analysis, is dependent on the data collected in the CRF. The entire data collection process, including checking, analyzing, and presenting it, is done using sophisticated technology and employing highly skilled professionals. The growing need for post-marketing data acquisition in large-populations for safety studies presents multiple challenges, including collecting, integrating, and analyzing lists of growing data sources. 
  • Sensitive clinical operation with process re-engineering: This is another challenge faced during clinical process re-engineering to make sure that EDC studies are planned and implemented in the context of addressing clinical support and safety process improvements. The organization needs to optimize daily clinical operations. The trend of outsourcing this aspect continues to grow, as many organizations increase the percentage of trials performed by CROs. While outsourcing, one must realize that there are several issues present, including data safety. The knowledge and integration give the long-term value while placing the right people for the job.
  • Continuous technology improvement: The challenge also lies in the improvement of technology and its flexible configurations. Several interconnected clinical systems can participate and support a clinical research trial operation, showing the need to use contextual systems processes while investigating and resolving any probable issues. Today’s technology-enabled environment, clinical data management, and willingness to improve among several groups are the key to engendering clinical efficiencies and cost benefits.
  • Evolving standardization and integrationStandard-based systems integration will present some challenges. The EDC technology needs to establish interoperable channels with several other systems. Standardization of these clinical protocols, common medical domains, adverse events, and medication coding is the key to ensure quality data on study efficacy and safety assessment. Standardization is also critical to ensure the success of pooled data analysis among various subjects in the clinical databases used. Standardization is extremely challenging as one does not have a standard framework to allow full system integration. 

Opportunities in clinical data management

Clinical data managers and CRF designers should be involved with the earliest development of the strategies, protocols, and data acquisition tools. Data managers need to understand the varied data sources and the form in which the data will be retrieved. It is increasingly recognized that the CRF design is a critical quality step in making sure the data required by the protocol and regulatory compliance study attributes and cross-checking of data items within a form or across various forms are addressed. CRF design is an engineering process that requires not only technical skills in utilizing the information technology tools and expertise in scientific reasoning in therapeutic areas. These systems need engineering work which requires cross-functional team collaborations. The CRFs and guidelines must be properly tested and reviewed and should be used at least among clinical data management and verification staff. 

 

The acceptance of EDC has led to new demands for improvement and intelligent features. Shortening the clinical trial lifecycle by acquiring quality data quickly and quickening the availability of data is the solution to a major path bottleneck the industry has been working on for many years. It has allowed the establishment of a new industry of clinical software vendors. Clinical research professionals that are gone through the best of clinical research training have to anticipate and embrace attentively to prepare for the further challenges from both systems and business engineering perspectives.