Archives: Agenda

• How much data is good enough to make the decisions that we need?
• Defining the role of real-world data in clinical research to assess the effectiveness of treatments
• Prioritizing the timeliness of data to identify safety signals early and increase trial credibility: how are companies balancing their needs vs the requirements of the patients?
• Ongoing debate for in-house vs external data managers: when is it best to outsource?

Everyone talks about AI, but few are showing production use cases in Quality Management. In this session, Roche shares a practical look at their strategy for integrating GenAI into the Quality workflow. We will discuss the methodology behind using AI to enhance Risk-Based Quality Management (RBQM) and how we are leveraging unstructured data—like historical scribe notes—to modernize inspection readiness.

• AI in RBQM: How AI supports the shift from reactive issue management to proactive risk identification, allowing teams to spot signals earlier in the trial lifecycle.
• The “Mock Auditor” (Inspection Defense): A case study on analyzing unstructured data (such as scribe notes and deviation text) to predict auditor behavior and prepare teams for questioning.
• The Trust Factor: Best practices for governance, validation, and maintaining a “Human-in-the-loop” when deploying GenAI in a GxP environment.

• Outlining key differences in company budgets and pipelines
• How to align financial incentives between CROs and pharma so that both sides win
• Uniting in common challenges amongst all sponsors
• Lessons learned from partnerships that improved performance
• Balancing trust and transparency across the ecosystem
• Patient safety, innovation and adaptability as shared goals

• AI is poised to streamline the design, deployment, and monitoring of clinical trials.
• Clinical ink has developed AI solutions for every trial stage, all within a robust governance framework for safety and compliance.

• Challenges of data silos and interoperability across research and clinical
• Strategies for creating a cohesive data ecosystem that supports translational research
• Case examples of successful data integration improving patient outcomes or accelerating drug development
• Predictive and prognostic biomarker discovery through advanced analytics.
• Regulatory and validation considerations for clinical implementation

• Future-facing models: What will define a ‘remarkable’ trial in the next decade?
• Leveraging adaptive and decentralized trial designs to improve flexibility and speed
• Empowering sites and CROs as partners to improve patient outcomes
• Strengthening communication to avoid misaligned expectations in the face of global disruptions
• Reducing costs and environmental impact while maintaining scientific integrity

• Japan’s pharmaceutical market transformation: addressing drug lag and drug loss
• Regulatory and ecosystem reforms accelerating drug development in Japan
• Key trends and organizations supporting pharmaceutical innovation
• Strategic insights into Japan’s pharmaceutical business landscape
• Japan as a gateway to expansion across the Asian pharmaceutical market

• Shared operational foundations across rare oncology and other rare diseases
• Rare oncology–specific differences you must plan for in conducting and outsourcing clinical research