1、 2025 Syneos Health.All rights reserved.Unlocking the Potential of AI in Medical Data Review2IntroductionThe field of clinical trials is rapidly evolving,with artificial intelligence(AI)playing an increasingly pivotal role.AI encompasses techniques,predictions,and analytic tools that enhance the ide

2、ntification of target populations for clinical trials,optimize site and investigator selection,and facilitate robust clinical trial designs.These analytical tools must ensure that data remains secure,operational and interpretable into actionable results.AI algorithms,when combined with an effective

3、digital infrastructure,enable the continuous streamlining of clinical trial datacleaning,aggregating,coding,storing,and managing data with greater efficiency and accuracy1.Furthermore,AI-based tools are now being employed in precision medicine,site selection,safety monitoring,and improved electronic

4、 data capture(EDC)to minimize human error and integrate seamlessly with other databases.AI thus enhances and refines the entire process of clinical drug development1.The need for AI in medical data review is more pressing than ever.The pharmaceutical industry faces unprecedented challenges due to th

5、e rapid increase in data volume and complexity associated with diverse data sources,decentralized trials and innovative trial designs.Traditional methods of data review are becoming insufficient to handle these diverse data sources.AI-driven solutions are essential to streamline data management proc

6、esses,improve data quality,and enhance decision-making.Patient/SubjectCRF DataNon-CRF DataBatch LoaderClinical DatabaseEDCSafety Labs ECG data PK/PD dataMedical Data ReviewerData ExtractSAS ReportsOutputSafety listeningsExcel ListingsData BrowsingAd-hoc analysis of PK/PD Data3Breaking Down the Medic