Making clinical trial data management faster, smarter, and easier
i2e's clinical data services help life sciences organizations enhance trial project management by optimizing resourcing, and budget tracking. Our expertise ensures efficient allocation of resources and cost control, improving overall study execution. We also conduct technology fit assessments for clinical data management software. i2e can also seamlessly integrate and validate Veeva and Clue Points with existing systems, ensuring streamlined operations and compliance.
i2e’s implementation and integration services help life sciences organizations optimize trials by seamlessly integrating Clinical Data Coordinators (CDCs) and clinical systems into their workflows. We ensure smooth data flow, enhance system interoperability, and streamline data integration processes across EDC, CTMS, EHRs and other clinical platforms. Our custom data connectors and APIs improve data accuracy, and real-time decision-making, resulting in more efficient and compliant clinical trials.
Our clinical data engineering services enable life sciences organizations to streamline trial project management by integrating real-time data streaming from CAT-patient data sources to clinical data capture systems. We ensure seamless data flow across EDC, CTMS, and analytics platforms, enhancing data accuracy, traceability, and compliance. Our clinical data management support services enable advanced clinical insights, optimizing study execution and regulatory reporting.
By utilizing predictive analytics, organizations can forecast trends based on historical data, while prescriptive analytics offers actionable recommendations for optimizing processes. Our data visualization and reporting capabilities transform complex data into intuitive visual formats while custom reporting meets specific business needs. We also provide ML and AI-Powered solutions, this includes deploying AI/ML models within Veeva applications for real-time predictions and recommendations. i2e also excels in building AI/ ML algorithms which can predict clinical trial protocol risks, drug dosages at the clinical trial sites, and chatbots to handle team queries.