The Case of An Integrated Biobanking Initiative in South Asia
May 15, 2026·
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Maxwell Salvatore
Yiran Wang
Preeti Syal
Brian Wahl
Harsh Parikh
Vishal Deo
Naveen Kumar Bhatraju
Kaushalya Jayaweera
Nisha Rana
Redoy Ranjan
Fyezah Jehan
Abdullah Yusuf
Karthik Adapa
Mona Duggal
Anurag Agrawal
Bhramar Mukherjee
Abstract
Large national, integrated biobanks have revolutionized how genetics-linked healthcare data can be scaled, providing access to massive databases to researchers globally. Recognizing the importance of integrated biobanks for public health and national scientific advancement, countries around the world have launched similar initiatives. Despite comprising a quarter of the world’s population, South Asia accounts for only 1·8% of EHR-indexed publications and 0·2% of GWAS participants. We argue for a South Asia Biobank Consortium: (1) a regional governing body overseeing interoperability across (2) national-level integrated biobanks that adapts the UK Biobank model to regional contexts (3) supported by federated analytics infrastructure with global access. If enacted, the consortium represents a scientific imperative and a pathway to digital health equity for nearly two billion people living in South Asia. We present a framework based on hallmarks of successful integrated biobanks and critical success factors. We propose a timeline for its establishment. Without decisive action, current disparities will worsen, leaving South Asia’s population marginalized as the transformative revolution continues. With a federated, equitable strategy, South Asia can transform from a peripheral participant into a central driver of biomedical discovery – strengthening health systems, advancing equity, and realizing the global promise of precision medicine.
Type
Publication
The Lancet Regional Health - Southeast Asia

Authors
Yiran Wang
(he/him)
Postdoctoral Fellow
Yiran Wang is a Postdoctoral Fellow at Institute of Health Policy, Management and Evaluation, University of Toronto. His research interests lie in developing methods that bridge theory and practice for a broad range of statistical problems, including Bayesian inference, population size estimation, mediation analysis, data integration, and latent variable models.