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Pharma Tech Outlook | Tuesday, March 14, 2023
Clinical efficiency has risen due to record-breaking vaccine development timelines. Managing external data and preparing it for downstream use requires agility.
FREMONT, CA: Clinical trial sponsors and CROs have witnessed the effects of disruptive innovation firsthand. They have continued clinical research despite COVID-19 constraints and streamlined processes, incorporated new technology, and enhanced efficiency, teamwork, and patient-centeredness. The industry cannot return to "old methods" of managing trials and data.
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But, clinical personnel are now confronted with the conundrum of increased expectations. Over the previous three years, numerous enhancements have made development accustomed to faster cycle times. Month-long delays in study build and extensive interruptions for manual data cleaning and reconciliation are no longer acceptable, mainly when mid-trial modifications are necessary.
The necessity to manage rising volumes of patient data, which cannot be managed directly in the EDC, has contributed to the difficulty. This data must be reported and analyzed by the biostatistics team and utilized in other crucial trial procedures, highlighting the necessity for a broader perspective on the requirements of cross-functional stakeholders. As the clinical environment evolves, transitioning from merely managing clinical data to comprehending it in a broader, scientific context promises to transform the data manager's work and bolster its significance.
Sponsors and CROs of clinical trials are already addressing top concerns in three critical areas, including reducing handoffs between clinical data and operations, which Boehringer-Ingelheim is pursuing with its OneMedicine program. They are enhancing access to clean patient data by implementing clinical workbench technologies and automation through artificial intelligence (AI), and they are improving their efforts to strengthen trial agility. They are partnering more effectively to improve patients' flexibility and experience. Already, steady and continuous progress is being made.
Enhancing agility and minimizing handoffs
Accelerating study initiation is a primary focus. Many organizations are decreasing trial durations by relocating the data management focal point away from the EDC, which cannot retain distant data from decentralized trials. Conventional EDC study designs have an average cycle time of 69 days from protocol clearance to database go-live; however, agile techniques employing a clinical data management system (CDMS) can significantly minimize start-up times. According to Trevor Griffiths, director of clinical data management at Syneos Health, implementing an agile CDMS reduced start-up periods to a few weeks.
Further pushing the change from EDC to CDMS as the data-management center is the fact that more studies are moving from the clinic to the patients' homes, resulting in an increasing volume of patient data from wearables and other external sources that cannot be directly stored and controlled in the EDC. In the past, the only method to include this data was to take it offline and manually cleanse it, which was an expensive, time-consuming, and laborious operation. Specific CDMS software now provides clinical data workbench-type solutions, such as Veeva Vault CDB, which enable the cleaning and storage of external data within the CDMS.
Flexibility for data management teams is maximized by combining the workbench with external connectors, such as data aggregation tools, analytics solutions, and pre-built integrations. Externally, a connected approach tackles the issue of diverse data sources, but internally, dealing with various functions requires a robust workbench. Integrating the two systems enables teams to manage diverse information and paths in one location.
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