The National Institutes of Health has awarded $25 million to a research team at NYU Langone Health and Sage Bionetworks to build the data hub and coordinating center for its Complement-Animal Research in Experimentation program, known as Complement-ARIE. The grant runs at $5 million a year for five years and will establish the NYU-Sage NAMs Data Hub and Coordination Center.
Complement-ARIE exists to accelerate what researchers call new approach methodologies, or NAMs - testing methods built in the lab or on a computer rather than in animals. The technologies in scope include three-dimensional human cell systems such as organoids and organ-on-a-chip platforms, computational and machine learning models, and cell-free biochemical assays used for toxicology screening. The premise is that these approaches can model human biology more accurately than animal models in many contexts, either alongside them or in place of them.
The practical bottleneck for this kind of work is data. Results from a molecular assay, a 3D culture, and a simulated population outcome are generated in wildly different formats, which makes it hard to compare findings across labs or reuse them. The NYU-Sage center is meant to solve that, serving as the consortium's backbone for data, metadata, code, and computational models on a cloud architecture, with AI-assisted curation, a harmonization framework, and analytical tools researchers can apply to shared datasets.
Beyond the infrastructure, the center is tasked with keeping the consortium talking to itself through workshops, benchmarking competitions open to a wider research community, and outreach to groups invested in NAMs. Whether these methods eventually displace animal testing in areas such as neurodegenerative disease research will depend on how well the resulting data holds up under that kind of scrutiny - which is precisely what a shared, standardized repository is designed to make possible.