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Archives: Agenda
Reducing delays, damage & blind spots: how Tive support pharma companies to actionable visibility to ensure shipments arrive on-time and in full
- IOT and Technology Evolution
- From Reactivity to Proactively saving shipments.
- AI in predictability – The Next frontier
Automating and Enhancing Efficiency through R-Based Solutions
- Design and implementation of an automated Data Management pipeline that standardizes key processes and reduces manual workload across studies
- Lessons learned from developing and deploying the Data Management pipeline across multiple clinical studies
- How automation and reproducible pipelines are shaping the future of Data Management and Clinical Data Science
CASE STUDY: Applying Agentic AI for streamlined data management processes
Chair’s closing remarks
END OF DAY 1 AND NETWORKING DRINKS
VIRTUAL SESSION: RadioPharmaceuticals: Understanding the unique specificities of RadioPharm Trials, and the unique challenges for data management
- Unique Nature of Radiopharmaceuticals in Clinical Trials
- Strategies for Effective Data Management
- Operational Challenges in Trial Design & Execution
- Complexity of Multimodal Data Integration
- Unique Challenges in Data Management
Alliances and partnering solutions for delivery of Data Management in current business landscape
- Key considerations for delivery of a large portfolio
- Challenges and opportunities in the implementation of a new delivery model/framework
- A case study: Internal Vs External Resourcing
Navigating vendor relationships: Keys to clinical data management success
- Vendor Relationships in a Changing Environment
- Best Practices for Successful Vendor Collaboration
- From Vendor to Partner
- Keys to Establish Effective Oversight
My AI Got 100% Accuracy, So I Threw It Away: Surprising failures & successes of AI in Clinical Data Management
- Understanding challenges faced when integrating AI into clinical data management processes
- Evaluating AI readiness and identifying red flags during development, implementation and deployment
- Taking away actionable insight how to use and incorporate AI, by learning from setbacks and successes