Working in a CRO gives a rare perspective. Every week, we’re exposed to an amazing breadth of innovation coming from biotech companies around the world. Working alongside drug developers at the cutting edge as they tackle novel targets, rare diseases, and complex pathologies is a privilege, but it’s also a constant reminder of how much is at stake, and how crucial having the right tools is for success.
Too often, we see brilliant science stumble at the same hurdle: translation. Promising candidates that shine in animal models, rapidly fail in human trials. As an industry we’ve become accustomed to this pattern, but given the enormous amounts of time and money that is wasted as a result – not to mention delays in getting therapies to the patients that need them – the industry should not be accepting it as normal. It indicates that we’re using the wrong models to answer the wrong questions. It’s an uncomfortable truth, but for decades the industry has been building its translational pipeline on a shaky foundation: animal models that simply don’t reflect human biology.
That’s why I believe the FDA Modernization Act 3.0 represents not just a regulatory update, but a lifeline that will get the industry innovating for improved translational success. The 2025 Act ushers in regulatory support for non-animal models, removing the requirement for animal testing in monoclonal antibodies and other drugs. This momentum is also gaining ground beyond the United States: in November 2025, the UK government announced a £75 million strategy to accelerate the phase-out of animal testing, unveiling a roadmap to prioritize cutting-edge alternatives such as organ-on-a-chip technologies, AI-driven simulations, and human tissue models. This transatlantic alignment signals a broader regulatory change that promotes human-relevant science and unlocks a future of safer, faster, and more ethical innovation. It’s a chance to finally shift our focus from animal proxies to human biology.
The adoption of New Approach Methodologies (NAMs) represents a fundamental shift in how we understand and model disease. NAMs are tools that allow us to build mechanistic, human-relevant data right from early discovery, and include 3D human cell cultures, organoids, organ-on-a-chip systems, and computational models that integrate real biological complexity. These aren’t theoretical technologies of the future. They’re here. They work. And they’re already transforming how we approach drug development.
By integrating appropriate translational model systems early in the drug discovery process, researchers can identify promising therapeutic strategies sooner and deprioritize ineffective ones. This front-loaded approach enhances confidence in downstream decisions, reduces reliance on poorly predictive models, and improves the overall efficiency and success rate of clinical development.
NAMs offer something animal models never could: the ability to generate mechanistic, human-specific insight. With the right approach, we can understand why a drug works, how it interacts with human systems, and where it might fail. That’s the kind of knowledge that de-risks development. This also has the potential to take us beyond generic human-relevant data, and brings us closer to truly personalized medicine. The possibility of incorporating patient-specific mutations in testing, and having more predictive biomarkers available as a result of more robust testing up front, opens up the option for tailoring an individual’s treatment at the clinical stage.
These aren’t just technical obligations, they’re also moral ones. Every time we use a human-relevant model, we’re not just improving science; we’re reducing waste, avoiding harm, and getting closer to treatments that actually work. FDA 3.0 gives us the framework to do that. It pushes regulators to recognize and qualify these models. It demands transparency. And it sends a clear message: human relevance is no longer a nice-to-have, it’s a must-have.
I believe we’re at a turning point. We can keep pouring time and money into models that don’t translate. Or we can embrace the tools that biotech innovators are already using to build better, faster, more human-centric science.
About the author
Dr. Hayley Gooding is a dedicated and enthusiastic biologist driven by the art of problem-solving and building efficient solutions. Having earned her Ph.D. in Neuroscience from University of Edinburgh, Hayley's research during doctoral studies provided an insight into building model systems for drug discovery and development, which laid the groundwork for the early stages in her career at a University CRO Spin out, Aquila BioMedical.
Hayley leads a team of scientists, spanning diverse disciplines, to deliver cutting-edge projects for the pharmaceutical and biotechnology industries in the pursuit of novel therapies for diseases such as Cancer and Alzheimer’s, with the potential to impact the lives of millions worldwide.
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