As FDA accelerates its shift away from traditional animal studies, regulatory and clinical development teams face immediate practical questions: which non-animal methods does the Agency currently accept, under what validation standards, and how should NAM-derived data be submitted? The answers have significant consequences for study design, IND strategy, and resource allocation across drug and biologic pipelines.
The analysis below examines the cluster of CDER draft guidances issued in 2025 and 2026 that define NAMs, establish the validation framework sponsors must satisfy, and specify how NAM data should be structured within eCTD submissions—providing a consolidated view of where FDA policy currently stands and what it expects from sponsors seeking to reduce or replace animal testing.
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FDA and New Approach Methodologies (NAMs): Building Alternatives to Animal Testing Into Drug and Biologic Programs
New Approach Methodologies (NAMs) have moved from a research aspiration to an active line of FDA policy. Across 2025 and 2026, the Center for Drug Evaluation and Research (CDER) issued a cluster of draft guidances that define what a NAM is, how sponsors should validate one for regulatory use, and how specific product classes can cut back on animal studies. The Agency has also updated its submission infrastructure so that NAM-derived data has a defined home in the eCTD. The direction is consistent: where a non-animal method can accurately characterize the relevant human risk, FDA wants sponsors to use it.
What FDA means by a NAM
CDER's framing is deliberately broad. In its March 2026 draft guidance, General Considerations for the Use of New Approach Methodologies in Drug Development, the Agency defines NAMs as a range of methods spanning complex in vitro systems, conventional 2D in vitro assays, in chemico approaches, and in silico (computational) studies 1. The stated purpose is to give drug developers a validation framework for NAMs "to improve predictive toxicology in humans and move away from reliance on animal testing," explicitly in alignment with CDER's Roadmap to Reducing Animal Testing in Preclinical Safety Studies 1.
The operational vocabulary is even wider in the June 2026 Study Data Technical Conformance Guide, which enumerates the method types FDA now expects to receive: microphysiological systems (MPS, including microfluidic "organ-chip" systems), complex in vitro methods (CIVM), 3D models such as organoids, spheroids, organ chips and organotypic cultures, stem-cell systems including induced pluripotent stem cells (iPSCs), co-culture and tri-culture models, engineered tissues such as reconstructed human epidermis and bioprinted tissue, multi-electrode arrays (MEA), computational methods including quantitative structure-activity relationship (QSAR) modeling, and non-traditional in vivo or humanized models such as zebrafish and transgenic or engrafted rodents 21.
The anchor document: a validation framework, not a method catalogue
The General Considerations draft is the connective tissue of FDA's NAMs policy. Rather than endorsing particular assays, it sets out how any NAM should be validated for a regulatory purpose, and it draws a clear line between two concepts sponsors often conflate. Validation is the process of establishing the accuracy, reliability and relevance of a method for a specific context of use; qualification is a separate determination that a drug development tool and its proposed context of use can be relied upon in review 1. CDER will consider data from both qualified and validated NAMs, but treats validation as the critical step for establishing reliability, and it points sponsors to other guidance for the formal qualification pathway 1.
The guidance organizes its recommendations around four features of any validation approach 1:
- Context of use (COU) — a clear statement of the regulatory purpose and the specific development decision the NAM is meant to inform. Worked examples include supporting the extent of patient monitoring in a trial, supporting dosage selection (first-in-human or later chronic use), and addressing a mechanistic question 1.
- Human biological relevance — whether the model meaningfully reflects human biology, which is where human-cell and human-tissue systems are positioned as potentially more predictive than traditional animal models 1.
- Technical characterization — the analytical and performance characterization of the method.
- Fit-for-purpose — whether the method adequately addresses the specific concern at hand.
Two points matter for regulatory strategy. First, a NAM does not have to be formally validated to be reviewed: a fit-for-purpose NAM, even if not validated, may adequately address a specific toxicological concern, and it is always assessed within a weight-of-evidence framework that accounts for prior knowledge and existing preclinical data 1. Second, the Agency signals a phased trajectory: as FDA gains confidence in a given tool, it "could be formally adopted to reduce or replace specific animal tests" 1. CDER encourages NAM use in submissions, particularly where the method improves predictivity, reliability and human relevance, and where a non-animal method has been shown to accurately characterize the relevant risk, FDA encourages moving to scientifically validated non-animal methods 1. The guidance is scoped to validation principles and does not address specific NAMs or the use of NAMs in drug discovery 1.
Product-class guidances that reduce animal use
Alongside the cross-cutting framework, FDA has issued targeted guidances that let particular product classes streamline or avoid animal studies.
Monoclonal antibodies. The December 2025 draft Monoclonal Antibodies: Streamlined Nonclinical Safety Studies addresses monospecific antibodies that recognize a single molecular target 19. Because most antibodies are pharmacologically active only in non-human primates (NHPs), conventional programs default to NHP toxicology; the guidance is intended to facilitate development while streamlining that reliance 19. It supplements existing streamlined pathways, including the guidances on severely debilitating or life-threatening hematologic disorders (March 2019) and rare diseases (December 2023), and it deliberately excludes multispecific antibodies, conjugated antibodies such as antibody-drug conjugates (ADCs), and antibody constructs such as single-chain variable fragments 19.
Oncology biologics and conjugated products. The May 2026 draft from the Oncology Center of Excellence and CDER, Oncology Pharmaceuticals: Streamlined Nonclinical Safety Studies for Biologics and Conjugated Products, is framed around "avoiding unnecessary animal use" in cancer drug development 8. Its recommendations are informed by data analysis of general toxicology studies and by practices developed during the COVID-19 pandemic specifically to reduce use of NHPs, combined with an integrated, knowledge-based risk assessment 8. It builds on the ICH S9 framework, under which chronic effects of oncology products may be assessed with 3-month studies in one or two species 8.
Model-informed and in silico methods
The in silico end of the NAM spectrum is where FDA has the longest track record, and recent drafts extend it further.
- PBPK modeling. The 2018 final guidance Physiologically Based Pharmacokinetic Analyses — Format and Content standardizes how sponsors submit PBPK analyses across INDs, NDAs, BLAs and ANDAs, and notably does not endorse any particular modeling software 24. A 2020 draft extends PBPK into biopharmaceutics applications for oral drug product development, manufacturing changes and controls 25.
- QSP for first-in-human dose selection. The June 2026 draft Quantitative Systems Pharmacology (QSP)-Based Dose Selection for Minimum Anticipated Biological Effect Level (MABEL) in First-in-Human (FIH) Trials describes using a QSP model to estimate a MABEL dose 26. The model integrates diverse inputs — in vitro assays in human cells (target binding affinity, receptor occupancy and activation, cytokine release), in vivo animal PK/PD, ex vivo and in silico data — into a single predictive framework to estimate a dose expected to produce a minimal but measurable biological effect in humans 26. This is a concrete example of computational and human-cell methods jointly informing a decision that has traditionally leaned on animal data.
The submission plumbing: making NAM data reviewable
A recurring obstacle for alternative methods has been that FDA reviewers had no consistent way to receive the data. The June 2026 Study Data Technical Conformance Guide addresses this directly by assigning defined file tags for NAM and "alternative" study types — MPS, CIVM, 3D organoid and organ-chip models, iPSC systems, engineered tissues, MEA, QSAR and other in silico methods, and humanized or zebrafish models — and by indicating where they belong in the eCTD (for example, modules 4.2.1 and 4.2.3.7) 21. In practical terms, this turns NAMs from an unstructured narrative attachment into taggable, reviewable study data.
What this means for regulatory teams
- The center of gravity is CDER's drug and biologics programs. The most developed, most recent policy is the General Considerations validation framework 1, reinforced by product-class streamlining for antibodies and oncology biologics 198 and by model-informed methods 242526.
- Almost all of the substantive NAMs policy is currently in draft form (March 2026, December 2025, May 2026, June 2026) 119826. It signals FDA's current thinking and the direction of travel, but sponsors relying on it should engage the relevant review division and, where a program hinges on replacing a specific animal study, confirm the approach through a formal interaction rather than treating the drafts as settled expectations 1.
- Context of use is the pivot. FDA will evaluate a NAM against a specific, well-defined decision it is meant to support, inside a weight-of-evidence assessment 1. A method offered without a crisp COU is unlikely to move a review.
- The validation-versus-qualification distinction is strategically important: validation establishes reliability for a stated COU, while qualification is the durable, reusable determination handled through a separate pathway 1.
- Submission mechanics now exist. Teams generating NAM data should tag and place it per the Study Data Technical Conformance Guide so it is reviewable as structured study data 21.
A note on scope: this overview reflects the guidance that surfaces most strongly for NAMs today, which is concentrated in CDER's drug and biologic programs plus the Agency-wide submission infrastructure. Device-specific NAMs policy (for example, alternatives in biocompatibility testing under CDRH) is a distinct thread worth a dedicated follow-up, as is the formal drug-development-tool qualification pathway that the General Considerations guidance references but does not itself cover 1.