Discover how NMA enhances comparative effectiveness research, informs healthcare policies, and drives optimized patient outcomes in an evolving treatment landscape.
In an increasingly complex healthcare landscape, network meta-analysis (NMA) has become a powerful tool for comparing multiple treatments, even when direct head-to-head trials are lacking. By synthesizing direct and indirect evidence, NMA provides a robust framework for assessing treatment effectiveness, safety, and cost-effectiveness, making it an essential component of evidence-based decision-making.
Payers, health technology assessment (HTA) agencies, and pharmaceutical companies rely on NMA to rank interventions, support reimbursement decisions, and strengthen regulatory submissions.
This session provides an in-depth exploration of NMA methodologies, practical applications, and real-world impact. Attendees engage with case studies and gain hands-on experience using R packages such as netmeta and multinma, equipping them with practical skills to conduct and interpret NMAs effectively.
Presenters
Daniel Gallardo
Daniel Gallardo joined ICON’s Health Economics & Epidemiology team in 2024 as a Senior Consultant. He brings deep expertise in Health Technology Assessment (HTA) and meta-analytic methods, with a strong specialization in Bayesian statistical modelling. His current work focuses on advanced evidence synthesis—including network meta-analysis (NMA), dose-response, and multilevel models—supporting decision-making in healthcare. Proficient in both Bayesian and frequentist approaches, Daniel designs and implements rigorous statistical analysis plans, primarily using R. He has extensive experience with packages such as multinma, MBNMAdose, MBNMAtime, and BUGSnet, ensuring robust and interpretable results for complex HTA submissions.
Nathan Green
Nathan Green has a number of years experience working on a wide range of projects across government and academia in defense and health, and currently works in the Department of Statistical Science at UCL.
Ankit Pahwa
Ankit Pahwa has 14 years of experience in statistical modelling, analytics, and programming. At ICON, he is involved in chart review studies, cross-sectional survey studies, and indirect treatment comparison using external control arm.
Sponsor
