Drugs

Data Volume, Diversity Slow Drug Development: Study

A Tufts Center for the Study of Drug Development study with Veeva Systems finds that the volume and diversity of clinical data are presenting integration, compatibility, loading, and interoperability challenges that the drug industry must address to optimize drug development performance. The study (purchase or subscription required), reported in an Impact Report, included nearly 260 drug sponsors and contract research organizations (CROs) and yielded a baseline assessment of data management practices and experience.

Sponsors and CROs reported they use electronic data capture (EDC) applications in clinical trials. About 75% of respondents reported using applications to manage randomization and trial supply management, safety and pharmacovigilance, and electronic trial master file data. However, 26% of sponsors and 52% of CROs said they still use paper report forms to support their clinical studies.

All sponsors and CROs reported managing electronic case report form (eCRF) data in their primary EDC application, with eCRF data representing 78% of the information managed by the application. Only 20% of sponsors and CROs reported managing electronic clinical outcomes assessment and medical imaging data in their primary EDC. Some 9.7% reported collecting mobile health and genomic data, but virtually none of that data are captured in the primary EDC.

Tufts reports that current data management cycle times are longer than those observed 10 years ago. Time from last patient, last visit to database lock was an average of 36.1 days in 2017, up from 33.4 days in 2007, due in large part, Tufts says, to the rapid growth in eClinical data volume and diversity of data captured. CROs reported, on average, building and locking study databases 20 days and 11 days faster, respectively, than sponsors.

Protocol changes accounted for 45.1% of database build delays reported by sponsors and CROs, Tufts says. They also found that more frequent study database releases after starting patient enrollment are associated with longer downstream data management cycle times, including time to enter data after patient visits and time from last patient, last visit to database lock.

Many companies reported technical challenges in loading the data into, and problems stemming from the limitations of, the primary EDC system, the report says. Some 32% of issues are related to EDC system limitations, and 29% are related to technical demands on support staff. The remaining 34% of data loading issues are related to challenges associated with integrating disparate data sets into an EDC system.

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