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Track 3: Data, Technology and AI

This track explores end-to-end strategies for designing and executing high-quality, efficient, and globally scalable clinical trials. It brings together global voices such as regulators, industry, academia, and patients, offering cross-disciplinary perspectives and emphasizing global harmonization of effort to address the most urgent operational and delivery challenges in modern clinical trials. Sessions highlight operational excellence, project management frameworks, technology-enabled solutions, and inclusive approaches that improve trial delivery from start-up through close-out. Attendees will gain insights into best practices for optimizing trial execution, managing vendors and partners, and ensuring operational readiness for increasingly complex trial designs.

  • Practical Applications of AI in Drug Development: Leveraging AI/ML for data generation, trial design optimization, predictive modeling, and regulatory submissions
  • Real-World Evidence (RWE) for Development and Post-Market Use: Generating, curating, and integrating RWE to inform clinical development, regulatory decision-making, and health technology assessments (HTAs)
  • Digital Health Technologies and Decentralized Trials: Lessons learned from DHT adoption, wearables, mobile apps, and approaches to scaling decentralized and hybrid trial solutions
  • Data Standards and Interoperability: Driving multi-stakeholder collaboration through standardized data frameworks, ensuring quality, integrity, and cross-border data sharing
  • Policy-Driven Innovation, Ethics, and Digital Equity: Understanding evolving policy frameworks for data use, ensuring information access and equity, and addressing cybersecurity, privacy, and responsible AI adoption
  • Transformation of Translational Science through Data Integration: Leveraging big data and advanced analytics to accelerate translational research and connect preclinical and clinical insights
  • Democratizing Patient Experience Data (PED) through AI and Digital Innovations: Exploring how advanced analytics, AI, and digital platforms can capture, democratize, and operationalize patient experience data to inform trial design, regulatory submissions, post-market decision-making, and equitable access to therapies
  • Clinical Data Management and Enablement: Best practices and innovations in trial data capture, curation, cleaning, standardization, and integration to ensure high-quality datasets for regulatory submissions, RWE generation, and decision-making
  1. How can AI and advanced analytics be practically applied to optimize clinical trial design, streamline development processes, and support regulatory decision-making?
  2. What best practices and lessons learned from digital health technologies (DHTs) and decentralized trial solutions can be scaled to improve patient access, engagement, and data quality?
  3. How can real-world evidence (RWE) and integrated data sources be effectively generated, curated, and applied in both development and post-market settings to inform regulatory submissions, safety monitoring, and healthcare decision-making?
  4. What data standards, interoperability frameworks, and policy-driven innovations are needed to ensure equitable information access, secure data sharing, and seamless collaboration across stakeholders globally?

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