Traditional oncology drug development strategies are failing – oncology agents have a higher attrition rate than other therapeutic areas, with activity rather than safety being the main clinical trial stumbling block. There is a clear need for improved methods and more predictive models, to fully understand preclinically which subgroups of patients will respond and the reasons why, to improve chances of clinical success.
Mouse Clinical Trials (MCTs) using patient-derived xenograft (PDX) models are a key example of a more predictive and translatable approach. PDXs are recognized as the most predictive preclinical model, closely recapitulating patient molecular and histopathology, as well as treatment response. Utilizing large cohorts of these models in a small number of animals within an MCT closely reflects clinical trials, providing a better perspective of patient-to-patient heterogeneity while assessing treatment response.
MCTs also provide the perfect framework for biomarker discovery, which is growing ever more important as personalized medicine progresses, and biomarkers become a crucial component in clinical trial success.
