- Demystifying the language of AI to assess whether it’s really the right solution for your study
- Concrete use cases for its successful and unsuccessful implementation
- Addressing concerns of inherent bias in data and increased data security and privacy fears
- What systems and vendors are on the market, and assessing their offerings for your specific data needs
- A roadmap to future proofing clinical data management: Implementing agile approaches to optimize stale workflows
- What will the growth of new clinical software vendors look like, and what will their offerings be?
- Scaling EDC and other systems to lead to the development of an integrated e-clinical environment and contribute to operational successes
- Ways in which today’s competitive pressures can push the industry to seek improved drug development strategies and shorten timelines
- Moving away from fragmented data and towards simplified pathways and what are the tools needed to facilitate data alignment?
- A look at Johnson&Johnson’s newly built platform to handle different data formats
- Ways to work together as an industry to hep standardize current processes
- Adapting to increased data sources and understanding the roadblocks to consolidating disparate data
- How can biotechs reliably minimize data risk and maximize data quality when combining different data sources?
- Running the trial: innovative approaches and overcoming challenges
- Treating with oncolytic virus intra-tumoral therapy
- Reaching clinical success: findings and future plans
- Comparing outcomes of a DCT model versus non DCT model
- Sharing benefits and lessons learned from experiences within rare disease DCTs
- Understanding regulatory pathways and incentives
- Identifying clinical development challenges and solutions
- Considering pricing, reimbursement and patient advocacy engagement
