Phasing Out Animal Testing: Responding to FDA and EMA’s Strategic Shifts

Authors: Zhang S, Suarez-Sharp S, Shoda L, Zhou H, Fraczkiewicz G, Lukacova V, Kalra P, Krause A, Jones J, Stefanovic B
Keywords: animal testing, drug development, European Medicines Agency (EMA), modeling and simulation, New Approach Methodologies (NAMs), U.S. Food and Drug Administration (FDA)
Division: Cheminformatics, PBPK, Quantitative Systems Pharmacology (QSP), Regulatory Strategies

Introduction: Regulatory Momentum Driving Change

Both the U.S. Food and Drug Administration (FDA) (1) and the European Medicines Agency (EMA) (2) have articulated clear regulatory expectations for the implementation and advancement of non-animal methods, known as new approach methodologies (NAMs). Central to this evolution is an emphasis on the use of integrated, probabilistic, and mechanistically driven approaches that leverage modern computational tools, in vitro assays and systems biology. The recent guidelines encourage moving beyond single-test replacements to integrated testing strategies (ITS), reverse dosimetry/pharmacology, and weight of evidence (WoE) frameworks.

The FDA’s 2025 roadmap adopts an action-oriented stand, outlining specific steps, pilot programs, and regulatory updates designed to facilitate the integration of NAMs. It emphasizes near-term implementation, regulatory adaptability, and the practical application of emerging technologies, such as organ-on-chip systems, artificial intelligence, within specific therapeutic areas.

In contrast, the EMA’s 2024 Reflection Paper takes a more exploratory and consultative approach. It provides a comprehensive assessment of current regulatory requirements across various testing domains and highlights potential opportunities for refinement, though it remains less prescriptive in terms of immediate implementation pathways. Notably, it provides a comprehensive review where animal testing may be waived or refined, especially in chronic toxicity and genotoxicity assessments.

 

Potential Path Forward

Differences of the key focus topics were identified in the EMA’s reflection paper and the NAMs listed in the FDA’s roadmap. Building on this alignment, the integrated solutions from Simulations Plus designed to address complex challenges in drug product development through innovative mechanistically driven approaches are presented in Table 1.

Table 1: Summary of near-term opportunities for M&S tools based on EMA’s Reflection Paper and the FDA’s Roadmap to Reducing Animal Testing, and examples of solutions from Simulations Plus

EMA 2024 Reflection Paper FDA 2025 Roadmap Simulations Plus Solution
Regulatory pathway The Regulatory Strategies Center of Excellence, consisting of multidisciplinary SMEs across all aspects of drug development, helps designing product development options tailored to industry. Examples include:

  • Risk-based assessment implementation of model influence on regulatory decisions
  • Implementation of context-of-use frameworks for model evaluation
  • Knowledge of techniques and limitations of IVIVE models
  • Interpretation of model outputs vs. historical animal data
PBPK
  • Human pharmaceuticals
    • Repeated dose toxicity (RTD)
    • Carcinogenicity
    • Toxicokinetics
    • Pharmacokinetics
    • Non-Clinical Evaluation of Anticancer Pharmaceuticals
    • Safety testing of biologicals
    • Safety pharmacology
    • Immunotoxicity
    • Phototoxicity
    • Dependence Potential
    • Testing in Juvenile Animals
    • Qualification of impurities
  • Advanced therapy medicinal products (ATMPs)
    • Requirements to support clinical trials for
  • Gene therapy medicinal products
    • Non-clinical pharmacology and toxicology
    • Tumorigenicity/oncogenicity
  • to inform first-in-human dosing and to justify waiving animal studies
  • to predict how differences between patients (e.g. body weight, disease state) might affect a drug’s PK further enhancing safety margins
  • in vitro in vivo extrapolation
 GastroPlus®,
ADMET Predictor®,
MonolixSuite™,
DDDPlus™,
MembranePlus™

  • predicting relevant input parameters (such as pKa, logP, dissolution profiles, permeability, and lysosomal trapping) for PBPK modeling and simulation
  • Mechanistic in vitro-in vivo extrapolation of processes impacting drug ADME
  • first in human PK prediction
  • model-based meta-analysis (MBMA)
ML and AI Predictive Models
  • to predict immunogenicity based on amino acid sequence
  • to predict toxicities (like acute systemic toxicity, off-target binding, or cytokine release potential)
 ADMET Predictor®,
High-throughput Pharmacokinetic (HTPK) Simulation

  • to predict carcinogenicity, sensitivity and environmental toxicities
  • to provide high throughput PK predictions for lead compounds
QSP
  • to predict efficacious dose ranges and potential toxic outcomes
  • reduce reliance on animal disease models by providing a virtual human on which to test “what-if” scenarios (reverse dosimetry approaches)
 Library of autoimmune, oncology, and metabolic disease QSP models:

  • to predict efficacious dose ranges and potential toxic outcomes (e.g., cytopenias, cytokine release syndrome, nausea
  • to reduce reliance on animal disease models

Organ toxicity models, DILIsym®, RENAsym®, BIOLOGXsym™:

  • to inform mechanisms of drug toxicity
  • to predict dosing protocols that reduce safety risks
Bioinformatics and in silico Off-target Screening
  • to screen a product’s sequence for any unintended targets (such as cross-reactivity to human tissues)
  • analyze whether the drug might bind to similar epitopes in the human proteome, in lieu of animal tissue cross-reactivity studies or broad receptor binding panels
 ADMET Predictor®,
High-throughput Pharmacokinetic (HTPK) Simulation

  • to predict cardiac (hERG binding), hepatotoxicity (liver enzymes elevation), endocrine (estrogen and androgen binding), and other toxicities

SME: subject matter expert; ITF: innovation task forces; DDT: drug development tool; IVIVE: in vitro to in vivo extrapolation; PBPK: physiologically based pharmacokinetic; QSP: quantitative systems pharmacology; QST: quantitative systems toxicology; ML: machine learning; AI: artificial intelligence; RTD: repeated dose toxicity; HTPK: high-throughput pharmacokinetic; ATMPs: advanced therapy medicinal products; MBMA: model-based meta-analysis.

 

Conclusion: Modeling as the Future of Drug Product Development

The parallel efforts of the FDA and EMA signal a pivotal regulatory shift towards reducing reliance on animal testing through the implementation of NAMs. For our clients, this means a growing opportunity to design development programs that are faster, less expensive, more ethical, and better aligned with future regulatory expectations.

Simulations Plus is positioned to lead this transformation through NAMVantage™, an end-to-end solution combining advanced software, predictive modeling, QSP/PBPK tools, customized coaching, and regulatory expertise. This empowers sponsors to design NAM-informed programs that meet regulatory expectations, enhance confidence in first-in-human (FIH) risk assessments, reduce development timelines, and support safer, more ethical drug development pathways.

Looking ahead, the adoption of NAMs is expected to become a cornerstone of global drug development strategies. While rigorous validation, global regulatory harmonization, data infrastructure development, and cultural shifts among FDA staff and industry will require significant effort and resources, these initiatives are positioned to transform drug development. As regulatory agencies continue to harmonize standards and offer more structured pathways for NAM qualification, we envision a future where digital twins, AI-driven disease models, and virtual human simulations will be routinely used to predict efficacy and safety. As stakeholders across the pharmaceutical and biotech industries continue to lead the way in drug development, we are committed to supporting them with next-generation platforms and expanded regulatory partnerships, enabling ethical science, speed, and precision to advance together. Stay tuned for additional analysis of the regulatory landscape, case studies, and tools for aligning your programs with FDA and EMA guidance.

If you are interested in modeling and regulatory insight and guidance now, schedule a time to meet with our experts.

References

  1. FDA. Roadmap to Reducing Animal Testing in Preclinical Safety Studies. 2025 Available from: https://www.fda.gov/media/186092/download?attachment.
  2. EMA. Reflection paper on the current regulatory testing requirements for medicinal products for human use and opportunities for implementation of the 3Rs. 2024 Available from: https://www.ema.europa.eu/en/documents/scientific-guideline/draft-reflection-paper-current-regulatory-testing-requirements-medicinal-products-human-use-opportunities-implementation-3rs-revision-1_en.pdf.