DOI: 10.1177/08853282261505008 ISSN: 0885-3282
Animal models to organoids for PK/PD studies of nanomedicines using advanced biomaterials for pancreatic cancer: A review
Shona Sara Shaji, Kaladhar Kamalasanan
Nanomedicines built on advanced biomaterials are emerging as promising solutions for cancer therapy due to their potential for faster clinical translation. Selecting appropriate animal or
in vitro
models is critical to accelerating this translation while improving affordability and accessibility. This scoping review examines the preclinical model landscape for Pancreatic Ductal Adenocarcinoma (PDAC), a malignancy projected to become the second leading cause of cancer-related death by 2030. Early diagnosis and timely treatment substantially reduce reliance on surgical intervention and improve survival, underscoring the need for models that support development of early-diagnostic tools and less invasive nanomedicine-based therapies. This review classifies preclinical models ranging from immunocompromised to non-immunocompromised rodents (mice, rats, hamsters) and porcine systems according to their suitability for studying pharmacokinetics/pharmacodynamics (PK/PD) of nanomedicines, and for analyzing mutagenesis, tumor growth, engraftment, metastasis, and tumor heterogeneity. Chemotherapeutic agents and nanodrug delivery systems are compared across these models, with chemically induced rat models identified as particularly robust for PK/PD evaluation. We further assess emerging
in vitro
organoid models derived from cell lines, primary human tissue, xenografts, and organoid-rodent hybrid systems for their capacity to accelerate drug and nanomedicine screening. Our analysis indicates that
in vitro
organoid models combined with rat models offer the most efficient platform for demonstrating nanomedicine efficacy, safety, and ability to overcome therapeutic resistance in PDAC. It also highlight opportunities to integrate organoid systems with Artificial Intelligence and Machine Learning ( AI/ML) approaches to further accelerate translational timelines, offering a roadmap for aligning model selection with specific clinical endpoints in future nanomedicine development.