|Details of person submitting|
|Details of abstract|
|Title of abstract||Data Management technology innovations throughout the evolution of the Clinical Data Manager role|
The role of Data Management (DM) continues to face increasing challenges in today’s high-pressured, fast-paced clinical development environment. Highly complex protocols, collaborative studies, multiple data types coordination (electronic health records, eSource data, among others) and the nonstop need for continuous automatization of data management systems are just a few variables in this multifaceted environment. Patients around the world demand safer products be delivered faster, the industry needs a more efficient and effective DM strategy while exceeding the expectations of our clinical research sites, especially in the areas of simplification and satisfaction.
The foundational goal of the Clinical Data Manager (CDM) remains the same, ensure the quality of appropriately collected clinical trial data, which directly aims to achieve dependable results that can be presented to regulatory authorities. We are living in the age of technology, CDMs have been exposed to a broader set of capabilities not considered possible few years ago, risk-based monitoring and review, machine learning and even artificial intelligence will aim directly to an increased understanding of clinical trial data quality and more efficient processes.
So, how can we, as CDMs, evolve our role to better contribute to new technology implementations and process simplifications without compromising data integrity and quality? This session will be dedicated to discussing how CDMs can predict the unexpected from new technology implementations, and how to optimize transparency of benefits and risk assessments during this process. With real case studies, experiences in process and technology innovations, the session will explain how the CDM role can adapt and maximize results in the pharma industry, in parallel, the risks associated with the inherent application of changes can be mitigated. We would like to share what we have learned in this journey and discuss the vision of the future CDM role under the auspices of researching and adoption of new technologies.
|First learning objective||Understand the main challenges faced by Clinical Data Management during the implementation of new technologies.|
|Second learning objective||Learn how implementation of new technologies can be importantly advanced by ensuring full CDM involvement.|
|Third learning objective||Understand how to increase efficiency and effectiveness of the CDM of the future.|
|Job title||Ass Dir, Principal Clinical Data Manager|
|Job title||Ass Dir, Data Management Trial Execution – Sub Process Owner|