Provides DM functional leadership to deliver quality and timely data in a manner that enhances the integrity, speed, and outcomes of the trial.
Interfaces with the project team and sponsors across the lifecycle of the project to proactively ensure data integrity and quality.
Mentors more junior DMs and other project team members on areas related to data management.
Effectively presents information and responds to questions from sponsors, senior managers, project team members, and clinical trial sites.
Makes strategic decisions and recommendations related to the data that benefit the project as a whole.
Ensures compliance with standard operating procedures.
Manages database design, development, testing and system validation for new studies. Has the expertise to do tasks independently and/or to oversee and mentor others in task completion.
Leads design of eCRF and reviews with study team to ensure design is robust and minimizes risk. Works particularly closely with the lead statistician to translate study outcomes, protocol guidelines and prior build experience into eCRF design.
Creates and implements data management plans (DMPs), data entry guidelines, data completion guidelines and other study documents. Ensures that the project team is trained and has a shared understanding of how data will be cleaned and each person’s role in the process.
Leads electronic data capture (EDC) system design and validation, including oversight of all database specifications (eCRF, SDTM where applicable, edit check, external transfer, randomization, etc.).
Defines clinical database variables (type, format, univariate validation checks) from an annotated CRF using either DMS or EDC data dictionaries.
Reviews and approves creation of all edit checks, including validation of simple univariate and multivariate edit checks, programming of complex multivariate validation checks, and UAT of system edit checks. Ability to write simple edit checks using SAS or similar languages is required.
Reviews recommended data management tools and selects the best tools for the study, leveraging study metadata and automation to minimize manual error and facilitate deeper understanding of study data.
Uses data cleaning tools to identify data trends and potential issues early in the study, and implements intervention plans with project team to address issues.
Holds periodic multidisciplinary data reviews with the project team to review data trends and anomalies, and to proactively address risks.
Follows-up with the project team to answer questions, to ensure data timeliness and cleanliness, and to process and follow queries to closure.
Conducts or oversees completion of all activities for database lock, ensuring data integrity and adherence to applicable regulations.
Ensures all study materials are finalized in an eTMF and archived for delivery.