Reproducibility in biomedical research.

TitleReproducibility in biomedical research.
Publication TypeJournal Article
Year of Publication2026
AuthorsZhong J, D'Angelo D, Lyu C, Xu I, Enns PK, Wang F, Kaushal R
JournalNat Med
Volume32
Issue10
Pagination3564-3577
Date Published2026 Oct
ISSN1546-170X
KeywordsBiomedical Research, Humans, Reproducibility of Results
Abstract

Reproducibility has long been considered a foundation of trustworthy science, yet practices that enable reproducible research remain inconsistently implemented, despite widespread awareness and establishment of policies and guidelines. Biomedical research that cannot be reproduced can lead to resource waste and adversely impact patient safety, public health outcomes, scientific progress and public trust. Rapid advances in technology, scientific dissemination and clinical translation have prompted renewed emphasis on validating research methods and findings to ensure transparency, rigor and credibility. Here we provide an overview of the current landscape of reproducible research in the biomedical sciences, summarize current efforts to harmonize terminology and implementation, and highlight the persistent barriers to adoption of best practices. We outline a practical framework to promote more uniform implementation and explore future directions for advancing reproducibility across stakeholders in the research process, including researchers, institutions, journals and funders.

DOI10.1038/s41591-026-04667-1
Alternate JournalNat Med
PubMed ID42811190
PubMed Central IDPMC13715817
Grant ListR01 AG054467 / AG / NIA NIH HHS / United States
RF1 AG084178 / AG / NIA NIH HHS / United States
R01 AG080624 / AG / NIA NIH HHS / United States
R01 AG072449 / AG / NIA NIH HHS / United States
OT2 OD040511 / OD / NIH HHS / United States
R01 AG076234 / AG / NIA NIH HHS / United States
R01 LM013344 / LM / NLM NIH HHS / United States
R01 AG076448 / AG / NIA NIH HHS / United States
R01 AG080991 / AG / NIA NIH HHS / United States
U01 HD112564 / HD / NICHD NIH HHS / United States
R01 AG065330 / AG / NIA NIH HHS / United States
Division: 
Institute of Artificial Intelligence for Digital Health
Category: 
Faculty Publication