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Clinical research for medicinal products continues to mature in terms of scope and complexity. Protocols now have stringent eligibility criteria, more endpoints, complicated procedures, and enhanced amendments. This is convoluted further by the involvement of outsourcing, increased number of study sites, and globalization.
As a result of dealing with disparate systems over the years, many pharmaceutical organizations are unable to efficiently manage end-to-end (E-2-E) data (flow or even retrieve details about one particular trial beyond generating some standard reports.
Some key challenges faced in end-to-end clinical data flow are as mentioned below:
- Data received from clinical research organizations is not clean, complete, or compliant to sponsor specific CDISC SDTM standards
- ETL programs run issues while comparing against sponsor-specific data standards
- Final data is not available to bio-statisticians for timely analysis and reporting
- Reconciliation challenges between clinical and safety for AE mismatch, coding inconsistencies, and so on
- Access, transfer, and other problems with underlying systems (SAS data sets, eTMF, DMS, and so on) for timely analysis, reporting, and CSR creation
The successful and timely execution of complex business processes is an important step in achieving faster go-to-market business objectives. It is, thus, imperative for a vendor supporting clinical applications to have a view of not just the clinical applications in scope but also of the associated business processes.