Using New Approach Methodologies (NAMs) in Drug Development
Welcome back! For those in the drug or combination drug product industry, the Food and Drug Administration (FDA) released their latest draft guidance in March, “General Considerations for the Use of New Approach Methodologies (NAMs) in Drug Development Guidance for Industry”, currently open for comments. Under the FDA’s regulations, drug sponsors must submit nonclinical pharmacology and toxicology data before investigational drugs can proceed to clinical trials. While many studies have traditionally been conducted in animals, the Center for Drug Evaluation and Research’s (CDER) routinely reviews data from NAMs when the methodology demonstrates reliability and scientific validity. Why is this important? How does this impact your company? Let’s break it down!
The recommendations in this draft guidance are intended to highlight scientific principles of study design and reporting that can be applied broadly and flexibly in the validation of NAMs used in drug development. This draft guidance is not intended to address specific NAMs and does not address the use of NAMs in drug discovery; rather, it encourages the use of NAMs in regulatory submissions, especially when they improve the predictivity of nonclinical studies for increased safety in clinical trials [1] .
The FDA provides a framework for validating and integrating New Approach Methodologies (NAMs) to enhance predictive toxicology, reduce animal testing, and support regulatory decisions in drug development. NAMs are newer ways that manufacturers and scientists can test, develop, and evaluate drugs. Instead of relying only on traditional methods such as animal testing, NAMs include other areas like computer modeling, cell-based systems, and other innovative technologies. The goal is to make drug development faster, safer, and more efficient.
The guidance aims to facilitate the validation and use of NAMs to improve human predictive toxicology and support drug applications while moving away from animal testing.
It provides a validation framework for NAMs in drug development.
Encourages use of complex in vitro, 2D in vitro, in chemico, and in silico methods.
Supports regulatory submissions with nonclinical NAM data.
Highlights that validation is not always required for NAMs to be considered.
Emphasizes early engagement with FDA review divisions for suitability.
Validation enhances the interpretability and reliability of NAMs, focusing on context of use (COU), human relevance, technical characterization, and fitness for purpose.
COU specifies the intended application and regulatory purpose of the NAM, addressing specific drug development questions, where it must support a regulatory decision. Examples include supporting patient monitoring, dosage selection, mechanistic understanding, or risk prediction. COU should address data gaps and fulfill development objectives.
Companies can ensure human biological relevance by:
Describing relevant cell types, species origin, and anatomical features.
Demonstrating how NAM findings relate to clinical outcomes.
Using models that replicate key mechanisms of toxicity.
Providing examples for neurotoxicity, hepatotoxicity, and respiratory toxicity assessments.
How are technical characterizations of NAMs confirmed? Companies should:
Describe test method details such as dose, preparation, detection, and instrumentation used.
Use appropriate statistical analysis and criteria.
Demonstrate predictive performance (sensitivity, specificity).
Document cell source, variability, and phenotype.
Justify reference compounds and controls.
Include details on culture conditions and assay stability.
For organ-on-chip platforms, consider flow, shear stress, scaffold properties, and material interactions.
How are NAMs fit-for-purpose use demonstrated?
NAMs should be shown to characterize risk as well as established methods
Benefits and limitations should be discussed that impact reliability
NAM findings should be explained how they contribute to risk assessments.
Where animal studies are replaced, provide additional proof or justify anima model limitations
What are some key considerations for manufacturers? Manufacturers need to show that their chosen NAMs are reliable and suitable for the specific product they’re developing. This means carefully documenting how these methods work, why they’re appropriate, and how they compare to older more established techniques. Companies must think about how these new methods will impact the quality and safety of their products. Transparency and thoroughness are key as companies will need to provide clear evidence that their NAMs can accurately predict how their product will behave in humans and that the results are reproducible.
With new methods, there are new risks. The FDA’s guidance emphasizes the importance of understanding and managing these risks. Manufacturers should assess whether each NAM is applied to each component and how they interact, as well as if it could miss important safety signals or create uncertainties about how their product will work. Companies should document proper risk management plans and consider extra testing or monitoring to ensure robust data is built. This means extra attention to risk assessments, documentation, and communication with the FDA to ensure everything meets the regulations.
Keep checking back as we continue following industry trends and how it may impact your company!
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