Data Management has forever been changed by the introduction of Oncology Clinical Trials. We must be agile and innovative and continuously learning, seeking out improvements and molding site and stakeholder relationships. Getting to a point where the critical data supporting the efficacy and safety of the drugs is cleaner faster and with optimal quality, must be a top priority for all.
The number of indications, high volume of new patient populations, constant Interim Analyses (IA), and increasingly complex protocol designs, pose a new and constant challenge for the Data Managers. Special consideration must be made by the clinical data managers in the; design of data collection and data validation tools; appropriate set up/management of External Data; and appropriate balance between robustness vs. usability data entry guidelines. We can no longer get by with defaulting to the process and guidelines of the past.
During this presentation we will examine the current landscape of data management in Oncology Clinical Trials as well as the detailed challenges faced by the clinical data manager including design, validation/cleaning, timing, flexibility and collaboration across stakeholders and customers. We will also take time to look at how some of these challenges are being approached. For example; external data handling; building solid expertise in end-to-end clinical trial study development with advanced knowledge of oncologic diseases, patients and trials through fully supportive and continuous mentoring and training programs; development of robust but flexible validation tools to enable team collaboration in design, consistency with the protocol, and quality from start to finish to support; and Engaging with sites to improve the sites’ experiences and collaboration with the data management team.