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Major leaps in science are often driven by the invention of new technologies and approaches. For example, while genome editing technologies have been around for decades, the novel approach used by the CRISPR-CAS system transformed researchers’ capabilities to solve previously intractable problems. By harnessing this new technological approach, we now have our first .

We also are seeing dramatic leaps in technologies that allow researchers to use complementary, non-animal-based approaches to study biological functions and human disease. These so called “novel alternative methods” or NAMs, which include computational modeling and predictive technologies, cell-free methods and assays and cell-based culture models, hold tremendous promise when applied to the appropriate scientific inquiry.

With the explosion of work being done in developing and using NAMs, NIH charged a of the Advisory Committee to the Director (ACD) to assess the challenges and opportunities for NAMs, as well as provide recommendations to the ACD for priority investments to catalyze their use and development in biomedical research. The working group consulted with experts in the field and reviewed input from the community to deliver its to the ACD during the Dec. 14, 2023, meeting. This report, which the ACD enthusiastically endorsed and conveyed to the agency, recommended that NIH work with the community to:

• Prioritize the development and use of combinatorial NAMs
• Establish resources, infrastructure, and collaborations to promote the use of interoperable, reliable, and well curated/high quality datasets produced from research using NAMs
• Promote effective dissemination and interconnection of NAM technologies
• Invest in comprehensive training to bolster continuous advances in development and use of NAMs
• Facilitate multidisciplinary teams with expertise across technologies and the lifecycle of NAM development and use
• Promote social responsibility in both the creation and deployment of NAMs across the research lifecycle
• Support and maintain coordinated infrastructure to catalyze effective and responsible NAM development and use

I want to thank the members of the ACD and the working group for their diligent work and thoughtful insights. After careful review and consideration of the report, NIH accepts these recommendations and is committed to continuing its investment in building a robust suite of tools for researchers to study human biology and disease. These recommendations build on an existing foundation of NIH investment in NAMs projects. This foundation includes complex lab-based systems like cells and tissues grown on chips and 3D cultures of cells that can replicate some features of organs. There��are computer and machine learning/AI models for neurodegenerative disease, wound healing, learning and behavior, SARS-CoV-2 propagation��and many other conditions. Current NAMs also include biochemical screening and other assays such as those for skin irritation and eye toxicity. NIH continues to advance the validation and regulatory implementation of NAMs in partnership with other federal agencies via the Interagency Coordinating Committee on the Validation of Alternative Methods ().

I am also pleased to see new efforts underway such as a newly proposed Common Fund research program aimed to drive these integrative approaches forward. The new concept, Complement Animal Research in Experimentation (), received concept approval at a recent meeting of NIH’s Council of Councils. The program aims to further the ACD recommendations by accelerating the development, standardization, validation and use of new methods and approaches that will more accurately model human biology and can complement, or in some cases, replace traditional models. Through the work of Complement-ARIE and other efforts across the agency, NIH hopes to provide new tools that will transform the way that we do basic, translational and clinical research and accelerate progress toward all people living longer, healthier and happier lives.

Monica M. Bertagnolli, M.D.
Director, ľ��ֱ��

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