Written by:
Senior Director, Head of Advanced Cell Models, R&D, AstraZeneca
Executive Director, Head of Safety Innovation, R&D, AstraZeneca
Advancing New Approach Methodologies through collaboration
At AstraZeneca, we are using New Approach Methodologies (NAMs) including advanced cell models, multiomics and AI, to strengthen how we predict the safety and efficacy of drug candidates, and to help accelerate the discovery of novel medicines. As these methods progress, collaboration across industry, academia, technology developers and regulators is critical to advance broader NAMs adoption across drug discovery and development.
Figure 1.NAMs are a connected set of innovative technologies that replicate aspects of human biology and help predict drug safety and efficacy.
Why are NAMs important for drug discovery and development?
NAMs help model how a drug candidate interacts with human biology before it reaches patients.
NAMs complement traditional approaches by offering more accurate and human-relevant tools to assess drug safety and efficacy profiles.
Approaches such as specialised human cell types, organoids, organ-on-chip and AI have demonstrated strong predictive value and can be applied early in drug discovery to help select the most promising candidates for further development, faster than before.
As these methods continue to mature and gain broader regulatory acceptance, they have the potential to help reduce long-term reliance on animal studies in specific contexts of use.
How can New Approach Methodologies (NAMs) gain wider adoption?
Across the US, EU, UK and to an extent Asia, policymakers and regulators are increasing support for the development, validation and wider use of NAMs. However, broader regulatory adoption depends on three fundamentals: a clear context of use, industrial readiness and regulatory engagement. In practice, that means showing a method is fit for purpose, reproducible at scale, and supported by the evidence needed for wider, global acceptance.
For example, a model designed to predict how a drug candidate affects liver cells may not be the right tool to assess effects in the lung, kidney or immune system. Defining where each method is most useful helps support more consistent application across research and regulation. At AstraZeneca, we are contributing to that progress by building evidence for how NAMs can inform decisions across R&D.
Why is collaboration essential to NAMs adoption?
No single organisation can build the evidence base, regulatory confidence and technical standards needed for wider NAMs adoption alone. Collaboration enables shared learnings, validated results and documented decision impact, supporting more harmonised application across regions and therapeutic areas.
How is AstraZeneca helping advance NAMs adoption?
AstraZeneca is advancing NAMs by integrating advanced cell models, multiomics and AI across R&D. These approaches complement traditional methods and support portfolio decisions by helping us build a more human-relevant understanding of drug safety and efficacy profiles earlier in drug discovery.
NAMs enhance the evidence base for everyday scientific decisions and support definition of the regulatory frameworks required for broader NAMs adoption across the industry, with the aim of identifying the best drug candidates through more informed, science-based decisions, and doing so faster.
Shaping the future of NAMs through collaboration
By working together across academia, industry, technology developers, service providers and regulators, we can improve reproducibility and support wider acceptance of NAMs across research and regulation.
Each part of this ecosystem plays a distinct role. Collaboration helps build, qualify and scale more human-relevant predictive science with the pace and rigour needed, aiming to accelerate bringing more targeted medicines for patients.
