In a significant move that could reshape how early-stage biomedical research is done, the U.S. National Institutes of Health (NIH) has announced it will no longer fund studies that rely exclusively on animal models. Instead, researchers seeking NIH grants must now integrate non-animal methodologies such as organoids, “organ-on-chip” systems, advanced computer simulations, or other innovative platforms into their experimental design.

This policy change, effective immediately for newly submitted grant proposals, comes amid growing concern over reproducibility, translational failures, and ethical questions around animal research. NIH officials noted that while animal models have long been foundational, their limitations in faithfully predicting human outcomes have become increasingly evident.

What Researchers Will Need to Do Differently

Under the new guidelines, grant proposals that depend solely on traditional animal experiments will be deemed incomplete. Applicants are expected to include one or more of the following as part of their research plan:

• Use of human cell-based systems such as organoids, which can mimic human organ function in miniature.
• Incorporation of microfluidic devices (“organ-on-chip”) that recreate tissue-level physiology under controlled conditions.
• Utilisation of computational modelling, machine learning, or simulations to predict biological responses and help refine hypotheses before or alongside in vivo work.
• Hybrid study designs that cross-validate animal findings with results from non-animal systems.

NIH will also provide new funding streams or emphasis to support development and validation of non-animal models, recognising that for many areas these methods are still under development. Researchers told that clear justification will be needed when animal studies are proposed, including rationale for why alternative models cannot address the same question.

Potential Impacts Across Biomedical Research

The new policy is expected to ripple across preclinical research, drug discovery, toxicology, and disease modelling. Some of the implications include:

• Faster Translation: Using more human-relevant or predictive systems might reduce the high failure rate seen when therapies move from animal studies into human trials.
• Cost and Resource Allocation: Initial investment in non-animal technologies can be expensive, but over time could reduce the costs associated with large animal colonies, regulatory burden, and slower experimental cycles.
• Regulatory and Ethical Pressure: Other funding agencies globally may follow NIH’s lead, tightening standards on animal use. Ethics boards and institutional review committees may shift expectations accordingly.
• Challenges for Some Fields: Certain research topics, for example, whole-body pharmacokinetics, systemic immune response, or behaviour in complex organisms may still depend heavily on animal models. Researchers in those fields will need to carefully craft proposals with hybrid models or argue strong justification for animal use.

Overall, this policy change signals a milestone in how biomedical research may evolve over the next decade. For early-career scientists, labs developing non-animal platforms, and funding bodies, it opens both opportunities and new challenges. The full effects will depend on how broadly the non-animal technologies can be validated, adopted, and integrated into existing workflows.