Data Science/Management
Evolution of Clinical Data Management to Clinical Data Science
Due to the use of Artificial Intelligence (AI) and Machine Learning (ML) in the use and conduct of clinical trials, the role has evolved, and our data manager has also evolved. Complex protocol designs and Trials are now executed in a patient centric, data driven and risk-based approach ensuring subject protection as well as the reliability and credibility of trial results.
In contrast, Clinical Data Management is responsible for the life cycle of clinical data from collection to their delivery for statistical analysis in support of regulatory activities. Clinical Data Management is primarily focusing on dataflows and data integrity (i.e., data is managed the right way). Clinical Data Science broadens this focus by adding the data risk, data meaning and value dimensions for achieving data quality (i.e., data is credible and reliable). Clinical Data Science also expands the scope of Clinical Data Management beyond the study construct by requiring the ability to generate knowledge and insights from clinical data to support other clinical research activities which require different expertise, approaches, and technologies.
We are your one-stop shop for Clinical Data Management services from study startup including EDC System choice, setup, CRF design and standards to study conduct, data review to database lock!
Solutions and Services:
- Registry Studies
- Data Entry backlog solutions
- CDM Staffing (contracts/consultants) – consulting services regardless of phase of your study
- EDC Build and Administration
- CRO Oversight
- Vendor Oversight