Date: Thursday, September 24th, 2026
Time: 8am PT / 11am ET

Respiratory clinical trials are becoming increasingly challenging. Targeted therapies and growing biologic adoption are narrowing eligible patient populations, while competition for patients and high-performing sites continues to intensify. At the same time, complex protocols, demanding endpoints and operational barriers can increase patient and site burden, contributing to slower recruitment, delayed study start-up and greater execution risk. The scale of respiratory research is significant, with industry data reflecting 3,100+ global investigators, 175+ Phase I–IV studies, 30,000+ patients across 8,000+ sites in 70+ countries, and contributions to the development of 20+ marketed respiratory products.

This webinar will explore how AI and digital solutions can help address these interconnected challenges across the clinical trial lifecycle. From optimizing study design and identifying the right patients and sites, to predicting enrollment, reducing participant burden and detecting emerging site and quality risks earlier, we will examine how technology can enable a shift from reactive problem-solving toward earlier prediction and targeted intervention.

Drawing on practical applications and emerging approaches, the discussion will consider how these capabilities can support more patient-centric, data-driven and efficient respiratory trials—while maintaining the quality and oversight required for successful study delivery.

By attending this webinar, participants will:

• Understand the evolving challenges in respiratory clinical trials, including shrinking eligible patient populations, increasing protocol complexity, competition for high-performing sites and growing operational and quality pressures
• Explore where AI, advanced analytics and digital technologies can have the greatest impact, from study design, patient identification and site feasibility through enrollment prediction, decentralized data collection, site-performance analytics and quality-risk detection
• Learn how AI and digital enablement can support earlier, more targeted intervention, helping sponsors and study teams reduce patient and site burden, anticipate recruitment and operational risks, and improve the efficiency and quality of respiratory trial delivery