Clinical Data Management Success Key: DMP

One must not be afraid of the word management, especially when it is linked to data. Systematic approach of planning, collecting, proofing of information and processing it further for analysis is the basic approach of data management. In the world of medicine, data management plays the most important role during clinical trials on various investigational products. Nuremberg code and declaration of Helsinki gave ethical framework of clinically sound data analysis of the newly developed medications by introducing ICH-GCP guideline-based clinical trials. ICH-GCP principle #10 says:

All clinical trial information should be recorded, handled, and stored in a way that allows its accurate reporting interpretation and verification.

Which means,

The trial data collected during subject visit based on scientifically sound protocol needs to be managed in accordance with the ICH-GCP principles and Good Clinical Data Management Practices guidelines.

Taking into consideration principles of ethics, safety, efficacy and data privacy, Clinical Data Management is well strategized to the granular level in GCDMP. Focusing on the guidelines mentioned in GCDMP, Clinical data has become much easier to manage, vast though.

CDM – An Integral Part of Clinical Trial:

Success of any clinical trial is based on bio-statistical approach toward the primary and secondary endpoints, but to help achieve these points main carrier of this trial is nothing but clinical data management. As per GCDMP, end result of CDM is to provide a study database that is accurate, secure, reliable and ready for analysis. So key functions of the CDM are:

  1. To make sure that the data collection modules (CRF-case report forms) are in accordance with the study protocol: They are capturing exact data points required for analysis. The data points are accurately mentioned based on study design. CRFs should acts as pillars on protocol plinth to develop a system generating integral data.
  2. To capture source data in desired format facilitating quick analysis: This can be done with single/double data entry for Paper CRF study or for EDC. Collecting data should be easy from multiple locations if required and for multiple times even for a single subject.
  3. To clean the data: Data validation checks working at data entry level or manual quality check of the entered data is required to clean the data. This is the most important function of CDM to make sure that the data forwarded for analysis is integral.

List does not stop here. It also includes steps like database designing, validation UATs and more. All these processes are interlinked and interdependent. How to make sure that all these crucial steps are well taken care of during the lifecycle of study. Data management plan is the answer to this question. It promotes consistent, efficient and effective data management practices.

Data Management Plan:

Study protocol is a bible for any study though, data management plan created based on protocol key points provides road map for all the activities to be carried out during clinical trial. It includes expected scenarios and its solutions and should include plan to deal with unexpected. It is an auditable document having details of procedures of the data management activities. It also mentions the responsibility matrix and step by step information about every activity. It should support compliance with regulatory boards. Systematically crafted activities from study initiation until database closeout including archiving should be covered under guidelines. This approved data management plan should be followed from study initiation to closeout. If there are any changes in the protocol or study pattern/design, this document should be updated accordingly. It also must be updated if there are any finding during course of trial.

Having a well-crafted data management plan implemented and followed for the trial is a success formula of any clinical trial.

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