Archives: Agenda

Clinical development in the digital age

  • Regulatory landscape of drug and device approvals
  • Chronology of technological advances
  • Role of AI/ML in drug development
  • Artificial intelligence and ethics
  • Application of new technology/AI in various drug development – challenges and opportunities
  • Innovative methods and clinical trial considerations

PATIENT ADVOCATE PERSPECTIVE: Improving support given to caregivers to reduce burden on patients’ families

  • Implementing support services for caregivers so they can provide information and early warnings of declining patient health
  • Educating caregivers so they are able to provide more compassionate care and more prepared to financially support
  • Maximizing efficiency and patient safety in cancer trials through caregiver engagement
  • Prioritizing caregiver involvement and embracing new ways to ensure they are fully supported

PANEL DISCUSSION: How far can AI take us?

  • How AI, ML and predictive analytics are reshaping operations and redefining what CROs can deliver
  • A vision of what AI-powered research may look like in 2030
  • How to keep up with the fast-paced AI is developing whilst maintaining trial integrity
  • Ensuring AI use aligns with regulatory frameworks and safeguards patient trust
  • Promoting smarter trial designs using AI to optimize protocols and identify feasibility risks
  • AI, data and the changing role of the technology service provider

Leveraging Machine Learning and Security Orchestration, Automation, and Response (SOAR) to combat cyber threats in clinical data operations

  • A look at how the digital transformation of clinical trials has created unprecedented cybersecurity challenges in protecting sensitive patient data and maintaining trial integrity
  • Examining how artificial intelligence and SOAR technologies are revolutionizing clinical data protection against sophisticated cyber threats, particularly Business Email Compromise (BEC) attacks
  • Demonstrating how AI-driven security solutions, integrated with SOAR platforms, can detect and respond to threats in real-time while maintaining GxP compliance
  • A practical framework for implementing AI-enhanced security measures in clinical data environments, including zero-trust architectures and automated response protocols for protecting electronic data capture
  • Gaining actionable insights into building robust cybersecurity frameworks that leverage AI capabilities to protect sensitive clinical data while ensuring regulatory compliance

New approach to Site ID: Adding a semantic knowledge platform to a solid process foundation

  • Explores a “site ID in one click” roadmap that combines deep industry expertise with a first-of-its-kind semantic knowledge platform.
  • Demonstrates how 30 years of operational data, paired with external insights from 500k+ institutions and 3M sites, strengthens feasibility decision-making.
  • Shows how expertise-driven processes and advanced data integration reduce the industry’s 50% non-enrollment rate.
  • Highlights how this methodology enables sponsors to accelerate timelines, reduce costs, and improve overall trial efficiency.

KEYNOTE: Making data-driven decisions: Effectively managing overwhelming amounts of data collected to ensure an ROI

  • 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?

Deploying AI for generation and deployment within Roche’s Quality Programs

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.

PANEL DISCUSSION: Sponsor, CRO, site collaboration: Aligning priorities across stakeholders

  • 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