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NAMs and MIDD integration aims to advance human-relevant, simulation-informed drug developmentNew Methods Aim to Improve Safety in Drug Development

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Key Takeaway
Recognize NAMs and MIDD as complementary, not replacements for animal studies.

This guideline examines the integration of New Approach Methodologies (NAMs) and Model-Informed Drug Development (MIDD) as complementary approaches in drug development. NAMs are described as generating human-relevant experimental and computational evidence, while MIDD provides a quantitative framework to integrate and evaluate that evidence. The authors argue that together these approaches can move NAMs toward more central regulatory evidence and support a more simulation-informed, human-relevant, and risk-based paradigm.

The document does not report a study population, sample size, comparator, or follow-up, and no primary outcome or effect sizes are provided. The main synthesized point is conceptual: NAMs and MIDD are complementary rather than competing, with MIDD serving as the quantitative bridge for NAM-generated data.

Limitations are not reported in the source. The authors explicitly caution that the text does not imply an immediate replacement of animal studies, which is an important framing for clinicians and researchers interpreting the guideline.

Practice relevance centers on regulatory and development strategy rather than direct patient care. The approach aims to shift NAMs toward more central regulatory evidence and to support a more simulation-informed, human-relevant, and risk-based drug development paradigm. No safety data, adverse events, or tolerability information are reported.

Researchers are looking at new ways to develop medications more safely. These methods, known as New Approach Methodologies (NAMs) and Model-Informed Drug Development (MIDD), aim to provide a better way to test drugs before they reach people. Instead of relying only on traditional methods, these tools use human-relevant data and computer models to predict results.

These two methods work well together. NAMs provide the experimental and computer data that relate specifically to human biology. MIDD then provides a mathematical framework to organize and evaluate that information. This combination helps scientists understand the risks and benefits of a drug more clearly.

It is important to note that these new methods are not intended to replace animal testing immediately. Instead, they are meant to support a more risk-based approach to drug development. This could eventually help regulators make better decisions about which medicines are safe enough for the public.

What this means for you:
Newer modeling and testing methods aim to provide more human-relevant data during the drug development process.

Common questions

What are NAMs and MIDD?

NAMs stands for New Approach Methodologies, which provide human-relevant experimental and computational evidence. MIDD stands for Model-Informed Drug Development, which provides a quantitative framework to integrate and evaluate that evidence. Together, they help scientists better understand how a drug might behave in the human body.

Will these new methods replace animal testing?

The guidelines do not suggest an immediate replacement of animal studies. Instead, these new methods are intended to support a more risk-based and human-relevant approach to drug development, helping to provide more evidence for regulatory decisions.

Study Details

Study typeGuideline
EvidenceLevel 5
PublishedJul 2026
View Original Abstract ↓
The transition from animal-based experimentation toward New Approach Methodologies (NAMs) requires not only technological innovation but also regulatory frameworks that enable evidence-based decision-making. We discuss how the European Medicines Agency’s evolving strategy for regulatory acceptance of NAMs, combined with the ICH M15 guideline on Model-Informed Drug Development (MIDD), can support the integration of mechanistic pharmacokinetic/pharmacodynamic modeling, physiologically based pharmacokinetic models, quantitative systems pharmacology, and artificial intelligence-driven approaches into medicines development. We argue that NAMs and MIDD are complementary: NAMs generate human-relevant experimental and computational evidence, whereas MIDD provides a quantitative framework to integrate and evaluate this evidence for defined regulatory questions and contexts of use. We further propose that routine MIDD planning, context-of-use-based case studies, regulatory-grade models and data infrastructures, and shared regulatory expertise are needed to move NAMs toward more central regulatory evidence. Rather than implying an immediate replacement of animal studies, this approach could progressively support a more simulation-informed, human-relevant, and risk-based drug development paradigm.
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