更简单、更快、更稳健：统一跨功能数据生态系统的出现

Harnessing innovation to better inform decisions andprotect sponsor’s endpoints SABRINA STEFFEN,Vice President and Head of Data Sciences Innovation & Data Strategy Part 3 of a 4-part series highlighting key innovations in clinical research Table of contents Protecting sponsor’s endpoints in the new era of clinical research3The basics: successfully unifying end-to-end data flow3Aligning roles, processes and emerging technologies4Creating a best-in-class business process workflow system4Creating the central ‘brain’: the IQVIA Workflow Navigator4The powerful impact of cross-functional transparency4The benefits of removing ‘white space’5Rapid data sync: how faster decisions enable better decisions5Ensuring sponsors retain control6Standardizing processes6Creating a standards repository6Digitized protocols are reshaping the future of data flow7Integrating agentic AI ‘invisibly’ into tools and applications8Case study: embedding agentic AI into setup and planning8Further optimizing Risk-Based Quality Management (RBQM)8About the author9 The basics: successfullyunifying end-to-end data flow Protecting sponsor’sendpoints in the new era ofclinical research To successfully integrate and capitalize on the cutting-edge breakthroughs in automation, artificial intelligenceand other technologies, a strategic shift must occurwithin data management, underpinned by the followingfoundational principles — each of which is essential forachieving success: The landscape of clinical trials is undergoing a profoundand accelerating transformation, abound with stunningadvances and newfound complexities throughout thedesign, planning and conduct of clinical research. Keyinnovations such as groundbreaking artificial intelligence,cutting-edge prescriptive analytics and rapidly evolvingfunctional roles and workflows are reshaping conventionalthought as to how to approach clinical studies — posingnew opportunities and challenges for sponsors and theirCRO partners to make timely, well-informed decisions. Andnowhere is this transformation more evident — or critical— than in clinical data management. •Removing the traditional functional silosandunifyingend-to-end data flow processes across datacollection, acquisition, review, analysis and submission. •Eliminating the need for reviewers to seekdifferent portalsor destinations for their specifictasks or functions. •Designing a meticulously curated and organizeddata lake repositorythat optimizes metadatamanagement, scalability and performance, validationframeworks, and interoperability — while providinga seamless user experience for each functional role(including sponsors). Data, of course, is the lifeblood of medical research; it isthe primary output of a clinical trial, vital for sustainingand advancing medical knowledge. But the challengesof successfully managing data in today’s clinical trialecosystem can be formidable. Recent years have seenmassive increases in both the volume of data generated(a single clinical trial today may produce one billion datapoints or more) as well as a staggering breadth of newdata sources. At the same time, unprecedented demandfor enhancing speed and efficiencies while maintainingoptimal quality adds a daunting array of potentialcomplexities to a data review process that is already all-too-often disjointed. •Embedding artificial intelligence within the dataflow tools and algorithms, acting as an ‘invisible’virtual assistant to team members as they completetheir activities. •Seamlessly integrating end-to-end standardsinto allprocesses, managed in a standards repository. •Leveraging enhanced oversight and predictivemodelsto aid in decision-making. But an exciting development is at hand — the emergenceof a unified, cross-functional data ecosystem enabled bynew technologies and a modernized approach to functionalroles and processes. Adhering to these 6 key pillars provides a soundfoundation for ensuring robust implementation andsynergy between people, process and technology —across the entire, continuous data ecosystem. This paper will review several of the key innovations andcore principles driving this new opportunity to build asimpler, more transparent and unified data managementsystem. In the end, this model empowers sponsors tomake better-informed decisions while achieving maximumrigor, simplicity and efficiency. Let’s now explore some of the key opportunities at hand. Creating the central ‘brain’: the IQVIAWorkflow Navigator Aligning roles, processes and emergingtechnologies Moving forward, processes and skill sets must evolveto seamlessly integrate with the rapidly emergingtechnologies and ensure successful implementationof a unified data ecosystem. Automation and artificialintelligence — including GenAI and agentic AI — willassume many of the time-consuming administrativetasks, while providing highly robust predictions andrecommendations. This will generate greater needfor prudent decision-making skills, inquisitive criticalthinking abili