Non-animal and Non-human Cancer Models for Drug Screening

Abstract

Cancer remains a major source of morbidity and mortality despite decades of scientific and clinical research and trials of promising new treatments. It is one of the leading causes of death worldwide, estimated to be the cause of the deaths of more than 600,000 individuals in the United States alone. Even many years after the discovery of cancer and the numerous research undertaken on it, the identification of anticancer medications continues to be a difficult undertaking. In addition, the development of drug and multidrug resistance hinders drug development. Therefore, continuous drug screening and testing should be undertaken in order to discover the treatment for this disease. Consequently, extensive investigations into cancer models are required for drug screening. One of these models comprises silico models which are inaccurate, unclear, and not time-effective. Next is animal models, which cannot accurately anticipate human reactions and are expensive, time-consuming, and challenging to work with. Human models are alternative models that, despite their ability to accurately predict human behavior, are far more expensive, demanding, and unethical. However, there is yet another model known as the microbial model. They are less costly, less time-intensive, more manageable, simple to cultivate, and straightforward to work with. In this study, we look into the major flaws of animal and human models and provide a new and more effective method for testing anticancer medications and combating anticancer drug resistance.