EXAMINING THE UTILITY OF MODELS IN EVALUATING ANTICANCER THERAPIES: FROM LAB TO CLINIC

Abstract

Evaluating anticancer therapies necessitates a comprehensive understanding of their efficacy and safety profiles before clinical translation. Models are pivotal in bridging the gap between laboratory research and clinical applications by providing valuable insights into treatment outcomes. This review explores the utility of different models in assessing anticancer therapies and their potential to guide clinical decision-making. Preclinical models, including cell lines and animal models, offer controlled environments for initial evaluations but face challenges in replicating the complex dynamics of human tumors. Patient-derived models, such as organoids and xenografts, offer personalized assessments of therapy response and enable the investigation of tumor heterogeneity. However, challenges related to scalability, standardization, and ethical considerations exist. This review discusses the strengths and limitations of these model types, their complementary roles, and the importance of their integration in comprehensive therapy evaluation. Furthermore, future perspectives and challenges are highlighted, including enhanced model integration, incorporation of real-world heterogeneity, improved predictive power and personalization, validation and standardization efforts, and ethical and regulatory considerations. By addressing these challenges, model-based evaluations can enhance the translation of promising anticancer therapies from the laboratory to the clinic, ultimately benefiting cancer patients.