The Resurgence of New Approach Methodologies (NAMs) in Drug Discovery and Safety Assessment

 In recent years, New Approach Methodologies (NAMs) have re-emerged as a transformative force in preclinical research, driven by advances in human-relevant biology, computational modelling, and regulatory momentum toward non-animal testing strategies.¹ Once considered supplementary tools, NAMs are now central to improving translational success, reducing attrition rates, and addressing ethical and economic challenges associated with traditional animal models.  

Defining NAMs: A Multidisciplinary Framework

NAMs encompass a broad suite of technologies that replace, reduce, or refine animal use in biomedical research.² These include:

• In vitro human-based systems (e.g., primary cell cultures, induced pluripotent stem cells, organoids)
• Ex vivo tissue models, particularly those derived from human biopsies
• In silico approaches, including machine learning and physiologically based pharmacokinetic (PBPK) modelling
• Microphysiological systems (MPS), such as organ-on-a-chip platforms

Collectively, these methodologies aim to better recapitulate human physiology and disease pathology compared to conventional in vivo models.

Scientific Drivers Behind the Resurgence

1. Translational Limitations of Animal Models

It is well established that animal models frequently fail to predict human responses due to interspecies differences in genetics, metabolism, and immune function. For example, discrepancies in cytochrome P450 enzyme activity and receptor pharmacology can lead to inaccurate predictions of drug toxicity or efficacy.³

NAMs, particularly those leveraging human-derived tissues, offer a more physiologically relevant context. Ex vivo systems preserve native tissue architecture, cell-cell interactions, and disease-specific phenotypes, features often lost in traditional cell lines or animal studies.⁴

2. Advances in Human-Relevant Biology

The development of 3D cell culture systems and organoids has enabled researchers to model complex tissue structures and disease states with increasing fidelity. When combined with CRISPR-based gene editing, these systems allow for precise interrogation of molecular mechanisms underlying disease and drug response.⁵

Moreover, access to fresh human tissue, including diseased biopsies, has enabled data-rich, patient-relevant studies. These models are particularly valuable in fields such as immunology, oncology, and gastroenterology, where disease heterogeneity plays a critical role in therapeutic outcomes.

3. Integration of Computational Modelling

In silico NAMs have matured significantly, with machine learning algorithms capable of predicting toxicity, pharmacokinetics, and off-target effects using large-scale datasets. PBPK models, for instance, integrate physiological parameters with compound-specific data to simulate drug distribution across organ systems.⁶

These approaches not only reduce reliance on animal studies but also enable early-stage decision-making, prioritising compounds with higher probabilities of clinical success.

Regulatory Momentum and Global Adoption

Regulatory agencies are increasingly recognising the value of NAMs. The U.S. Food and Drug Administration, European Medicines Agency, and Organisation for Economic Co-operation and Development have all initiated frameworks to validate and integrate NAMs into safety assessment pipelines.⁷

A significant recent development comes from the MHRA, which has introduced new measures explicitly designed to support the adoption of NAMs and reduce reliance on animal testing. These include offering early regulatory review of non-animal data and clarifying how such data will be evaluated in marketing applications, thereby reducing uncertainty for developers.

Importantly, the MHRA has committed to allowing companies to submit non-clinical (Module 4) data packages derived from NAMs for early review by the end of 2026, even before full marketing authorisation. This represents a substantial shift toward integrating NAM-derived evidence into regulatory decision-making earlier in the development pipeline.

The agency has also outlined key regulatory principles, including that certain products, such as generics or those lacking pharmacological activity in animals, should not require animal testing, while others may proceed to clinical trials without prior in vivo studies if sufficient human-relevant data exist.

Crucially, this initiative aligns with the UK Government’s broader strategy to phase out animal testing where feasible, while maintaining rigorous safety standards and recognising that some animal studies may still be required in specific contexts.⁸

Notably, recent legislative and policy shifts have removed mandatory animal testing requirements for certain drug classes, signalling a paradigm shift toward human-relevant data. The OECD’s development of Adverse Outcome Pathways (AOPs) further supports the mechanistic integration of NAMs into regulatory toxicology.

Applications Across the Drug Development Pipeline

Early Discovery and Target Validation

NAMs enable mechanistic insights into disease biology using human-relevant systems, improving target identification and validation. Organoids and tissue explants allow researchers to study disease progression and therapeutic intervention in a controlled yet physiologically meaningful context.

Safety Pharmacology and Toxicology

Human-based NAMs are increasingly used to assess organ-specific toxicity, including hepatotoxicity, cardiotoxicity, and gastrointestinal effects. Microphysiological systems can simulate multi-organ interactions, offering a systems-level understanding of compound safety.⁹

Precision Medicine and Patient Stratification

By leveraging patient-derived tissues and cells, NAMs support the development of personalised therapies. These approaches can identify responder and non-responder populations, enabling more targeted clinical trial design.

Challenges and Future Directions

Despite their promise, NAMs face several challenges:¹⁰

• Standardisation and reproducibility across laboratories
• Limited scalability for certain complex models
• Data integration across diverse platforms (in vitro, in silico, ex vivo)
• Regulatory validation for widespread acceptance

However, ongoing collaboration between academia, industry, and regulatory bodies is addressing these barriers. Initiatives focused on data sharing, protocol harmonisation, and cross-platform validation are accelerating the adoption of NAMs.

Conclusion

The resurgence of NAMs reflects a broader shift toward human-centric, data-rich, and mechanistically informed drug development. By overcoming the limitations of traditional models, NAMs have the potential to enhance predictive accuracy, reduce development costs, and ultimately bring safer, more effective therapies to patients faster.

As the field continues to evolve, the integration of NAMs into standard practice will not only redefine preclinical research but also set a new benchmark for scientific rigor and ethical responsibility in the life sciences.

References:

1. Incorporating New Approach Methodologies in the Development of New Medicines, hesiglobal.org/wp-content/uploads/2025/10/NC3Rs-2025_Incorporating-NAMs-in-new-medicines.pdf. Accessed 9 Apr. 2026.
2. Sewell F, Alexander-White C, Brescia S, Currie RA, Roberts R, Roper C, Vickers C, Westmoreland C, Kimber I. New approach methodologies (NAMs): identifying and overcoming hurdles to accelerated adoption. Toxicol Res (Camb). 2024 Mar 25;13(2):tfae044. doi: 10.1093/toxres/tfae044. PMID: 38533179; PMCID: PMC10964841. 
3. “How Many Animal Tests Fail to Predict Human Outcomes?” Biology Insights, 22 Aug. 2025, biologyinsights.com/how-many-animal-tests-fail-to-predict-human-outcomes/.
4. "Ex Vivo Culture: Key Applications and Advantages.” Biology Insights, 26 July 2025, biologyinsights.com/ex-vivo-culture-key-applications-and-advantages/.
5. Wang, D., Villenave, R., Stokar-Regenscheit, N. et al. Human organoids as 3D in vitro platforms for drug discovery: opportunities and challenges. Nat Rev Drug Discov 25, 204–226 (2026). https://doi.org/10.1038/s41573-025-01317-y 
6. “In Silico Nams and AI: How Digital Models Are Replacing Animal Testing in Drug Discovery.” Helixa Communications, Helixa Communications, 16 Dec. 2025, www.helixacommunications.com/blog/in-silico-nams-ai-drug-discovery.
7. Godbeer, Lucy. “Nams: Scientific Foundations and Evolving Regulatory Excellence.” DLRC, 22 Aug. 2025, www.dlrcgroup.com/nams-scientific-foundations-and-evolving-regulatory-excellence/.
8. Medicines and Healthcare products Regulatory Agency. “MHRA Action Boosts Drive to Phase out Animal Testing.” GOV.UK, GOV.UK, 24 Mar. 2026, www.gov.uk/government/news/mhra-action-boosts-drive-to-phase-out-animal-testing?utm_medium=email&utm_campaign=govuk-notifications-topic&utm_source=a1bd07c4-e236-486f-a087-462e3fc29220&utm_content=immediately.
9. Jochum K, Miccoli A, Sommersdorf C, Poetz O, Braeuning A, Tralau T, Marx-Stoelting P. Comparative case study on NAMs: towards enhancing specific target organ toxicity analysis. Arch Toxicol. 2024 Nov;98(11):3641-3658. doi: 10.1007/s00204-024-03839-7. Epub 2024 Aug 29. PMID: 39207506; PMCID: PMC11489238. 
10. “Standardizing Nams: Why the Field Needs a Unified Voice before Regulation Can Catch Up.” Proteomics & Metabolomics from Technology Networks, www.technologynetworks.com/proteomics/articles/standardizing-nams-why-the-field-needs-a-unified-voice-before-regulation-can-catch-up-410001. Accessed 9 Apr. 2026.