How Labs Can Prepare For and Align with the Future of Research
Last week, the NIH announced the creation of the Office of Research Innovation, Validation, and Application (ORIVA), an initiative designed to accelerate the development and implementation of human-based research methods while reducing use of animal models. The office will coordinate NIH efforts to advance technologies that aim to better capture human biology, such as organoids, tissue chips, and computational models. Additionally, the NIH will report on annual spending to track progress towards shifting funding away from animal studies and towards human-based approaches.
The impact of ORIVA will vary across fields, but the broader implication is clear: ORIVA is likely to shape how biomedical research is designed, evaluated, and funded. As grant opportunities and review criteria evolve, a growing emphasis will be placed on how researchers select and manage their model systems. What does a model system tell us about human biology, and what resources does it require to yield those insights?
As scientists navigate this changing landscape, it’s important to acknowledge that policy can shift faster than the research systems it influences. In many areas of biomedical science, animal studies have long been embedded in both research methodologies and publication practices; journal reviewers often expect in vivo animal data when claims involve organ-level biology. As a result, there is a need to maintain scientific rigor while making animal studies more efficient and laying the groundwork for an expansion into more human-focused models. During this period, services offered by Transnetyx can help researchers maximize information gained from experiments while minimizing animal use.
ORIVA builds on other recent efforts to accelerate actionable insights into human health while reducing reliance on animals. New Approach Methodologies (NAMs), sometimes referred to as Novel Alternative Methods, have been championed by the NIH and FDA as a way to improve translational relevance of biomedical research. A 2023 NAMs working group envisioned a future where researchers can choose from a diverse range of models to best capture the biology they seek to understand. The report emphasized improving human relevance, increasing reproducibility, integrating multiple experimental approaches, and reducing reliance on animals where alternative methods can provide equal or greater insight.
Although NAMs represent a new generation of research tools, they build on ideas that have shaped animal research for decades—ideas that are fundamental to how Transnetyx serves the industry. The field has long been guided by a framework known as the 3Rs: Replacement, Reduction, and Refinement. When possible, researchers should replace animal models with alternative approaches that can answer the same scientific question. When animal models remain necessary, studies should reduce the number of animals to the minimum number needed for reliable results. Finally, throughout the research process, practices should be refined to alleviate suffering and improve animal welfare. The 3Rs aspire to align scientific rigor with responsible stewardship, encouraging researchers to iteratively improve on laboratory techniques.
Each of the 3Rs reflects a different aspect of animal research, but all are shaped by a common factor: how efficiently biological systems can be translated into usable experimental data.
Before an animal model can be replaced, it is necessary to understand why it is being used in the first place: what biological question is being asked of it, and what measurable readouts can provide answers. This understanding equips researchers to assess whether alternative model systems could address the same question without loss of critical biological context. Such assessments, however, depend on accurate characterization of the existing model. Transnetyx improves the quality of information available at this stage by clarifying which genotypes are present in a colony, revealing biological constraints early in experimental planning, and centralizing records and documentation, making it easier to determine whether animal models are truly required for a given research question. In the long term, better characterization of existing animal models can help guide development of reliable non-animal alternatives.
Reduction comes into play once a model system has been chosen, and is determined by how efficiently data can be extracted from the model. Even well-designed studies can drift toward excess animal use when variability is underestimated, genotypes are confirmed late, or more animals are bred than experiments require. Transnetyx enables reduction through a range of tools. Automated Genotyping provides clarity in near real time, reducing repeat experiments caused by misclassification or uncertainty. Microbiome analysis addresses a hidden source of variability that can obscure trends and increase required sample sizes. Genetic Monitoring helps maintain strain integrity through early detection of contamination and unintended background variation, making it possible to course correct before these factors necessitate use of additional animals. Predictive colony management helps align breeding plans with experimental demand, preventing the birth of unnecessary animals.
Refinement is carried out in the day-to-day conduct of animal research, but is often determined by the quality and timing of information flowing through the entire experimental pipeline. When colony data is fragmented or outdated, animals may be handled more frequently than necessary, overcrowding occurs, and staff must take on additional administrative burdens to reconcile inconsistent records. By replacing manual tracking with unified, automated records, Transnetyx enables timely interventions for animal welfare while reducing strain on technicians. Additionally, integrated records of lineages and protocols reduce the need for manual reconstruction—which can be slow and error-prone—during audits or compliance reporting.
Taken together, these day-to-day improvements reflect a broader change in how biomedical science is being organized and funded. As priorities evolve through ORIVA and other initiatives, researchers will likely face increasing scrutiny not only on scientific significance, but on model selection and resource usage. Navigating that shift will require more than just new model systems; it will also depend on how existing animal studies are characterized, managed, and assessed. By improving analysis of animal models, preventing production of unnecessary animals, and tightening the link between breeding plans and experimental design, Transnetyx helps laboratories stay ahead of emerging expectations. That same shift toward more streamlined and well-characterized experimental systems will support more reproducible and responsible science, benefiting researchers, institutions, and the ultimate goal of improving human health.
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