Program Overview

Clinical data management (CDM) is the effective and efficient generation and management of data for clinical research. It is an important phase of clinical research and trial. In order to collect accurate and reliable data, clinical data management is being done.

Admission Requirements

This program is designed for life sciences and healthcare graduates / clinicians who are ready to pursue a career in clinical research at any level.
BSc.Life Science, B.Pharm, BDS, Ph.D, MBBS, B.Sc.Nursing or equivalent are eligible to apply.

Graduation Requirements

To successfully meet the program outcomes the student must:

•   Achieve a minimum mark of 80% in all of the module assignments and exams
•   Achieve a satisfactory rating in the internship evaluation

Career Opportunities

Drug safety monitoring will be significantly impacted by artificial intelligence (AI). AI is improving the quality of data from drug trials, resulting in better drug safety decisions. This is possible thanks to developments in natural language understanding and image recognition. Big data analytics and cloud-based Data Management platforms will continue to advance, allowing for more complex analysis of massive datasets. Artificial intelligence can expedite the risk assessment process and lessen human error. In order to help people make better decisions more quickly, AI can analyze vast amounts of data to find patterns and trends. Numerous opportunities exist to use AI and machine learning in Data Management as a result of their rapid uptake. The market is looking for integrated solutions that, by revealing hidden data and utilizing automation to boost efficiency, can manage Data Management from beginning to end.