Beyond good intentions: How life sciences can prove its readiness for NAMs

The life sciences industry is entering a pivotal era where the goal of moving beyond animal testing is moving forward with the help of all three key players: science, policy, and public engagement. For years, non-animal testing has been championed by advocacy groups and public interest organisations, but what’s different now is the alignment of these voices with regulatory support from agencies like the FDA, EMA, MHRA, MFDS, along with rising industry investment.

While support for reducing animal use has never been stronger, the path to broad adoption is steep and complex. Technologies are advancing rapidly, but qualification and validation standards, regulatory pathways, and shared frameworks are still evolving. While everyone agrees on the ethical imperative to reduce animal use, the challenge of widespread readiness will depend on partnership, proof, and continued development activities.

Misconceptions: What NAMs are and aren’t

Public perception often paints NAMs (New Approach Methodologies) as fully developed tools ready to replace animal testing across the board. The reality is far more nuanced. NAMs are not single technologies or assays; they are methodologies encompassing a range of in chemico, in vitro, ex vivo, in silico, and even animal tools designed to improve human translation. These can include 3D tissues, organoid models, microphysiological systems (organ-on-a-chip), AI-based simulations, refined animal formats, and more.

But the promise of NAMs is not about flipping a switch and eliminating animal models overnight. It’s about providing the resources to support new technological advances and building the scientific and regulatory confidence needed for these methods to stand on their own.

The challenge: From fragmentation to framework

While numerous stakeholders, including pharma, biotech, CROs, regulators, and advocacy groups, have all contributed to the advancement of NAMs, broad coordinated collaboration across the ecosystem has only begun to take shape in recent years. As a result, progress to date reflects a diversity of parallel efforts, rather than fully aligned frameworks. To realise the full potential of NAMs, the field now requires greater transparency, data sharing, and collective infrastructure to support model development, validation, regulatory qualification, and adoption. The key challenge is not resistance to NAMs, but rather the establishment of the collaborative frameworks needed to scale them effectively.

The FDA’s current roadmap highlights a specific drug class, monoclonal antibodies, where NAMs could add near-term value. However, there’s no universally accepted, comprehensive NAMs “toolbox” yet that companies can confidently apply across preclinical development even for less complex drug modalities.

How NAMs can succeed

Through the power of coordinated efforts across scientific and regulatory partners, widespread investment, and shared accountability, the industry can successfully create the framework for the development and adoption of NAMs.

1. Shared input across stakeholders: Companies should form or join multi-stakeholder consortia that bring together biopharma, CROs, regulators, and academic researchers in developing and validating NAMs collaboratively. With increased cooperation, there will be more shared experiences, which has the ability to reduce redundancy and ultimately speed up the path to standardised qualification and validation.

    

2. Invest in high-quality starting materials: Ensuring reproducibility starts with verified biological integrity. The use of traceable, well-characterised, and ethically sourced biological materials from qualified providers is foundational to study reliability. Partnering with suppliers, which provide documented provenance, donor metadata, and standardised quality testing, enables laboratories to build internal QC systems that support consistent, defensible, and reproducible research.

    

3. Integrate AI and data science for predictive power: AI is integral to complex NAM workflows. Expanding access to curated, high-quality datasets through secure, de-identified data sharing can dramatically improve model training and benchmarking. AI-driven in silico modelling can then elevate findings from NAMs studies to population-level predictions, enhancing both efficiency and confidence in programme advancement and regulatory decision-making.

    

4. Engage regulators early and often: Early regulatory dialogue is essential to ensure that workflow design, test systems, and data strategies align with emerging expectations for model qualification and weight-of-evidence approaches. Engagement with the EMA’s Innovation Task Force, where developers can receive early, informal scientific feedback on novel methodologies, can help shape study design and clarify technical considerations before formal regulatory interactions. Likewise, programmes such as FDA’s ISTAND initiative, which not only supports qualification of novel methods, but also provides publicly available examples of qualified assays, can help developers understand evidentiary needs, refine validation strategies, and build workflows suitable for future regulatory consideration.

    

5. Commit to shared validation and transparency: Both successes and failures must be published to accelerate learning and build trust. Establishing industry-wide validation standards and reproducibility benchmarks can prevent redundant efforts, improve consistency, and streamline acceptance.

The future

The truth is that the industry is not ready for full animal model replacement because the tools, validation criteria, and regulatory frameworks are still being built. Non-animal systems continue to face limitations in capturing long-term or multi-organ toxicities, and first-in-human trials remain the ultimate safety test for many complex therapies.

The path forward lies in creating a validated ecosystem of human-relevant alternatives that gradually reduce and refine animal use while improving predictive accuracy for human outcomes.

The shift toward NAMs is inevitable, but the extent of adoption and how rapidly it occurs depends on the industry’s ability to systematically develop, validate, scale, and standardise emerging methodologies. Achieving this will demand transparent collaboration, proactive regulatory alignment, and consistent scientific discipline. The next step for the field is to demonstrate readiness through coordinated action, shared evidence, and proven performance.

About the author

Kent Grindstaff is consulting director at BioIVT. He brings deep scientific and operational expertise across drug development, CRO management, and biotech commercialization to the role. Based in Boise, Idaho, Grindstaff has built a career spanning preclinical research, IND-enabling studies, and business leadership within pharma, biotech, and contract research organisations, and has held senior leadership roles at XenoPort, Optivia Biotechnology, Solvo Biotechnology, and CohBar, where he led discovery research, preclinical development, and supported clinical activities. Recognised for his practical, science-driven perspective, Grindstaff has also served as a consultant across multiple therapeutic modalities, advising on discovery and preclinical strategy for emerging biotechs. At BioIVT, Grindstaff supports ADME consulting, industry partnerships, business development, and technical thought leadership, while also helping drive internal awareness of market trends and emerging technologies.