Litcius/Paper detail

Integrating New Approach Methodologies (NAMs) into Preclinical Regulatory Evaluation of Oncology Drugs

Maryam Sadat Mirlohi, Tooba Yousefi, Amir Reza Aref, Amir Seyfoori

2025Biomimetics12 citationsDOIOpen Access PDF

Abstract

Traditional animal-based preclinical models, including xenografts and genetically engineered mice, have been used for assessing pharmacodynamics, toxicity, efficacy, and safety for decades. Despite their limited ability to mimic human tumor heterogeneity, immune interactions, and microenvironmental complexity, over 90% of oncology candidates that succeed in animal studies fail in clinical trials. The New Approach Methodologies (NAMs), which include patient-derived organoids, organ-on-chip platforms, and AI-driven computational models, provide human-relevant solutions that can improve predictive validity, mechanistic insight, and ethics. Through these technologies, it will be possible to replicate tumor biology specific to patients, to support co-clinical trial designs, and to facilitate biomarker discovery while reducing animal testing. Several recent regulatory reforms, including the Food and Drug Administration (FDA) Modernization Act 2.0 and the European Medicines Agency's NAM qualification framework, have established clear pathways for the integration of validated NAMs into preclinical drug evaluation. Critically evaluating the scientific rationale, comparative performance, and regulatory context of key NAM platforms in oncology, this review highlights opportunities for synergistic integration, technical refinement, and global harmonization in order to accelerate the development of clinically effective cancer therapeutics based on preclinical findings.

Topics & Concepts

HarmonizationPreclinical testingContext (archaeology)Regulatory scienceDrug developmentMedicineRisk analysis (engineering)Food and drug administrationPreclinical researchClinical trialSystems pharmacologyDrug discoveryComputational biologyHuman useExpert opinionPersonalized medicineDrug approvalCancer treatmentBiomarker discoverySystems biologyIntensive care medicineDrugPharmacologyCancerBiomarkerBioinformaticsMedical physicsAnimal modelComputer scienceInvestigational DrugsDrug administrationStandardizationTrastuzumabBiopharmaceuticalCancer Cells and Metastasis3D Printing in Biomedical ResearchMathematical Biology Tumor Growth