- Integrating the right biomarker to narrow relevant patient groups and optimise and personalise disease management
- Engaging with the oncology community and advocacy groups to grow involvement of well-informed patients
- Leveraging investigator expertise for pragmatic trial designs and patient identification
- Building the evidence, from natural history to endpoint development, to support informed decisions by health authorities
- Challenges in securing initial funding/additional financing
- Expense associated with drug development
- Loss of new pharmaceutical technologies and cutting-edge compounds
- Impact on patients in need of options
- 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
- Effectively generating real world evidence in an efficient and timely manner
- Incorporating strategies that allow for high-quality real-world evidence collection
- Overviewing regulation to improve understanding of real-world evidence submissions
- 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
