Clinical Data Management Delivery of the Quality Data for Drug Development


Clinical trial is a critical stage of drug development, which involves a long run process and thus produces huge amount of scientific data. This data will eventually make a new product useful and marketable in disease therapy. The clinical data management process relates to a sequence of activities which include development of a data management plan followed by study set up (CRF designing, database setup, etc.) and training.

CDM is an on-going process and begins with the protocol development and ends at the completion of the statistical analysis. It involves the collection, recording, processing, analysis and reporting of the data; monitoring data quality and data safety; maintaining audit trial; database closure; data storage while ensuring the security and confidentiality through the process.

The principal objective of data management is to deliver high quality data with minimizing the possibilities of errors or omission of data. To fulfill this purpose, best possible practices are adopted to make sure that the data processed or which is about to be processed is complete, reliable and correctly analyzed. Thus, developing a data management plan (DMP) is the first step to be taken during the early setup of the study. DMP must define all the components of the data management process. Each component must specify the work to be performed and the responsible staff for work. It should ensure that the guidelines / SOPs will be followed as per regulatory framework. DMP remains live through the life cycle of a clinical study, to address any updates / changes made during conduct of the study.

Shortly after, or along with the development of the clinical protocol, Case Report Forms (CRFs) are developed to cover all the appropriate data for analysis specified by the protocol. The CRF is handled by CDM team as the first step in rendering the protocol activities into data being generated. The quality of data rests on the CRFs. The CRF should be clear and concise as well as self-explanatory. The data fields should be clearly defined. Extraneous or redundant data should be strictly avoided as it adversely affects the data quality. Separate sets in the CRF should be developed for each visit, eg Screening, Randomization, Adverse Drug Monitoring, Follow up visits, etc. CRF completion guidelines (the filling instructions) should be provided along with CRF to avoid errors during data acquisition.

An efficient clinical data management during the trials demands skilled CDM team members, who are associated with different roles and responsibilities. Every member must have competent qualifications (must be a graduate or post graduate in life sciences, pharmacy or relevant fields) with sound knowledge of computer applications. The key members of the CDM team are: Data Manager / Product Manager, Database Programmer / Developer, Database Administrator, Clinical Data Associate and Medical Coder, who perform their fundamental roles that are essential for the team.

The biopharmaceutical industry under the competitive pressure is experiencing the challenge of increased productivity and thus is forced to seek better ways of reducing drug development times. The innovative technologies have now enabled tools for CDM to boost up the speed of drug development and commercialization. The use of better data-capture tools such as Electronic Data Capture (EDC) and eCRF for the collection of clinical trial data in electronic forms ensure the good quality of data. The use of such tools has increased gradually in the recent years and has greatly supported the contract research organizations (CROs) in their clinical research activities.

CDM continues to evolve in response to the special cross-functional needs and according to the particular strengths of e-clinical research advances due to much enhanced clinical harmonization, global standardization, and expected clinical systems interoperability initiatives.

Neha Rawal