About
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 will provide an in-depth exploration of NMA methodologies, practical applications, and real-world impact. Attendees will 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.

Join us to discover how NMA enhances comparative effectiveness research, informs healthcare policies, and drives optimized patient outcomes in an evolving treatment landscape.
Presenters
1747941177-db3bac9a226e46c9
Ankit Pahwa, MS
Lead Epidemiologist, Health Economics & Epidemiology, ICON
Ankit Pahwa has 16 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.
1747941341-3691c57b5cc19906
Daniel Gallardo, PhD
Senior Consultant, Health Economics & Epidemiology, ICON
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.
1747941249-5c984948deae59ea
Nathan Green, PhD
Senior Research Fellow, Department of Statistical Science, University College London
Nathan Green is a Senior Research Fellow in the Department of Statistical Science, UCL. He has several years of experience working on a wide range of projects across government and academia in defense and health. His research interests include health economics, survival analysis, evidence synthesis and epidemiology.
Register To Watch Recording
First Name*
Last Name*
Email Address*
Country / Region*
Job Title*
Job Level*
Organization / Company*
Organization Type*
What is your greatest challenge as it relates to network meta-analysis?*
On a scale of 1-5, what is your familiarity/expertise with network meta-analysis?*
What do you hope to learn during this webinar?
Registration Terms
This event is hosted by HealthEconomics.com (a Scientist.com company). By registering and participating, you acknowledge that your personal data will be processed by HealthEconomics.com. You also agree to receive email communication from HealthEconomics.com about this webinar and other programs of similar nature. The sponsor of this webinar is ICON; by registering and participating, you acknowledge that your data will be processed in accordance with ICON’s Privacy Policy. You will receive email communication from ICON about this webinar and programs of similar interest. You can withdraw your consent at any time from these communications.
Yes, I consent to the registration terms.*
Yes, I consent to the registration terms.*
We use BigMarker as our webinar platform. By clicking Register, you acknowledge that the information you provide will be transferred to BigMarker processing in accordance with their Terms of Service and Privacy Policy.