Lessons Learned In Implementing AI In Clinical Development

Point Solutions Are Only Band-Aid Fixes to Clinical Process Problems

Implementing an AI-powered data analytics system has been a game-changer for Taiho Oncology. In this article for Clinical Leader, Taiho executives Christopher Zergebel (Vice President, R&D Services) and Ed Chapman (CIO) explain the value of a comprehensive solution when it comes to gaining actionable insights from disparate and complex clinical data sources.

The authors share how adopting technology from Saama has made it possible to align key clinical trial stakeholders, internally and externally, to a single source of truth, resulting in improved risk management and study performance.

Data from multiple CROs and multiple sources, including CTMS, EDC, Labs, and IRT, were part of the initial implementation and plans are in the works to onboard additional sources, such as biomarker and pharmacovigilance data. Taiho also intends to layer in Saama’s Smart Applications for automatic query resolution, medical coding, and data mapping.

The authors share how Saama’s Life Science Analytics Cloud (LSAC) has given them greater insights into their data.

“We can now access and run various analytical reports for key internal stakeholders, including medical monitors, data management, and other functions spanning the clinical trial process…The result is greater ownership of our own data, available to us 24×7, as opposed to traditional approaches relying on our CRO for insights into our studies.”

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