Harnessing Big Data, AI, and Real-World Evidence to Transform Regulatory and Health Technology Assessment in APAC

ISSUE: Real-World Evidence (RWE), derived from sources outside traditional clinical trials, is transforming healthcare decision-making in the Asia-Pacific region. RWE accelerates regulatory approvals and optimizes reimbursement decisions, drawing from electronic health records, claims data, and patient-generated information. Despite growing recognition, significant barriers hinder the full utilization of big data and artificial intelligence in developing robust evidence across APAC countries. Fragmented healthcare systems with inconsistent data standards impede cross-border RWE utilization. Regulatory frameworks vary substantially, with South Korea implementing parallel review processes while China pilots early-access programs, complicating multi-country evidence strategies. Stakeholders often remain skeptical of RWE compared to randomized controlled trials, despite increasing cost-effectiveness demands. The integration of artificial intelligence with RWE offers opportunities to overcome these barriers through advanced analytics and automated data validation. This convergence aligns with ISPOR's consideration of establishing a global health economics institution to support international organizations.

OVERVIEW: This panel will explore how APAC countries are leveraging RWE or AI-enhanced RWE for regulatory and reimbursement decisions. We will 1) Share case studies of successful RWE implementations, 2) Identify remaining challenges in RWE adoption, 3) Propose frameworks aligning with ISPOR's vision of a globally integrated health economics community. By examining RWE implementation in Health Technology Assessment (HTA), we aim to contribute to developing standardized methodologies that reflect Asia's unique healthcare contexts. This will advance evidence-based decision-making in the region and support ISPOR's initiatives in global health economics.