All clinical trials are performed to answer certain questions about the efficacy and safety of a drug or device. The answers solely depend upon the quality of data, which are collected during the trial and submitted after the trial. The study data is an immense asset for the pharma and biotech companies. Probability of getting a drug or device being approved for marketing increases if the study data is in good shape. Hence data management plays a crucial role in ensuring the success of a trial. Adopting proper methods to manage the trial data helps in increasing the quality of data. Learning, practicing and improving upon these methods has lead to the creation of clinical data management as a subject.
This topic describes: History of clinical data management, Overview of clinical data management, Data management plan, Data capture and collection, CRF design, Clinical database, Data entry, Data review and validation, Quality assurance and quality control (qa/qc), Data storage and archival, Recent advances in CDM and Data standards.