Abstract

ANIMAL MODEL IN PERCLINICAL RESEARCH FOR ANTI CANCER

M. Aruna*, Dr. R. Manivannan, S. Gopala Krishnan, G. Gopika, S. Gowtham,

Abstract

Cancer remains one of the major causes of death across the world, which creates a constant need for better and safer treatment options. Before any new drug is tested in humans, it must first go through detailed preclinical studies to evaluate its safety, effectiveness, pharmacokinetics, and possible toxic effects. At this stage, animal models are extremely important because they allow researchers to study tumor behavior, disease progression, and treatment responses within a living biological system. Various animal models, ranging from small rodents to larger mammals, provide valuable information about cancer development and how drugs function inside the body. Small animals such as mice and rats are widely used because they reproduce quickly, are relatively affordable to maintain, and share several genetic similarities with humans. More advanced models like genetically engineered mice, xenografts, and patient-derived xenografts have significantly improved the reliability of cancer research. Larger animals including pigs, dogs, and rabbits are also useful because their physiological characteristics often resemble those of humans, making them suitable for pharmacokinetic and translational studies. Despite these advantages, animal models also present certain limitations, mainly due to biological differences between species and ethical concerns regarding their use. To address these issues, researchers follow the 3R principles— Replacement, Reduction, and Refinement—to improve both scientific quality and animal welfare. In addition, modern technologies such as artificial intelligence, molecular imaging, and genomic analysis are helping increase the accuracy and predictive value of animal studies. This review outlines the importance, different types, applications, advantages, and limitations of animal models in anticancer drug development, while also discussing emerging technologies that are shaping the future of preclinical cancer research.

Keywords: Cancer, Animal Models, Preclinical Research, Anticancer Drugs, Xenograft, AI in Oncology.