Data Management and Analysis

Clinical Data Management is one of the main elements of our services portfolio. As part of our data management services we offer traditional paper-based CRFs, EDC systems as well as data integration with other data systems such as central laboratories, central readers, IVRS, etc. Using thoughtful review process we recommend the most efficient, cost-effective data capture technologies to ensure high-quality, accurate, reliable, and statistically sound data from clinical studies.

In providing Data Management services we employ the best in the industry EDC systems to provide data management services for Phase I through Phase III clinical studies. As part of our data management services we offer traditional paper-based CRFs, EDC systems as well as data integration with other data systems such as central laboratories, central readers, IVRS, etc.

Clinartis’ robust Standard Operating Procedures and comprehensive training programs are designed to provide seamless execution of the data management plan and ensure continuous compliance with compliance with 21 CFR Part 11 requirements and with Good Clinical Data Management Practice (GCDMP).

From database build to database lock, our experienced data management experts work seamlessly with other study team members to ensure the we meet or exceed our clients expectations in regards to both timelines and quality.

 

Our Data Management Services include:

Data Management Data management plan development eCRF and paper-based CRF design Database design and programming Edit check programming, validation, and testing User acceptance testing CRF completion guidelines EDC training (on-site and remote) Data entry and processing Data cleaning and query resolution Medical coding of adverse events, medical history, and concomitant medications (MedDRA, WHODrug dictionaries) Data quality control audits Integration of external data SAE reconciliations

Statistics Study design and protocol input Sample size estimation and power analyses Statistical analysis plan development Randomization schedule Statistical interpretation and analysis Data conversion and validation Generation of tables, figures, listing Interim analysis and final statistical reports Statistical regulatory support SAS programming to CDISC standards for regulatory submissions