Preclinical screening models in anticancer drug development: strengths, limitations, and translational challenges

Cancer is one of the leading causes of morbidity and mortality worldwide, accounting for a considerable global health burden and approximately 10 million deaths every year. There have been monumental breakthroughs in cancer research; but translating promising preclinical data into successful evolving drug therapies continues to have an enormous challenge. This challenge is further emphasised by the very high rate of attrition throughout clinical development, confirming the inadequacies of existing predictive screening platforms and emphasising the need for more predictive preclinical models. Therefore, this paper provides an overview of the various major types of preclinical models used to evaluate anticancer drugs, along with their respective strengths, weaknesses, and translational relevance. Classical in vitro cytotoxicity screens provide an essential element to early phase high-throughput cytotoxicity evaluations. More sophisticated 3D and 4D in vitro tumour models, patient-derived organoids, and organ-on-chip technologies allow for improved modelling of tumour structure and architecture, microenvironmental complexity, and drug penetration dynamics, improving accuracy in predicting in vivo activity of agents being screened in vitro. Further, in vivo model systems, provide essential in vivo data to dissect and understand the biology of tumours, pharmacokinetics, toxicity, and therapeutic efficacy of agents used to treat cancer. Rational drug discovery will be further enhanced through increasingly available emerging technologies such as bioinformatics, molecular docking, genomics and omics-based methods. Although traditional animal and cell line models are needed in drug discovery; the shortcomings of these systems, in their inability to reproduce the full complexity of human tumours means they account for a large proportion of translational failures. This comprehensive review shows how developing multi-faceted, human-comparable and technologically sophisticated screening platforms for test drugs will increase predictivity, speed up drug development for cancer treatment and improve clinical benefit from tested drugs.