Predicting whether a patient will respond to treatment is the holy grail of cancer therapy. Response or resistance, however, is dependent on the tumor microenvironment, which is comprised of malignant cells, normal stroma, and an immune landscape; features that are unique to each individual patient. This is particularly true for emerging anticancer drugs, such as immune checkpoint inhibitors, which recalibrate the body’s own immune defense. Here, we describe a novel platform technology that replicates the tumor microenvironment from a single patient outside the body (CANscriptTM). This clinically-validated model integrates an algorithm-driven method to predict clinical response to therapy, which accurately predicts patient response in refractory, aggressive, metastatic and relapse-prone disease. Additionally, we will discuss how CANscript enables a complete dissection of the tumor microenvironment as it behaves under drug pressure, including immunotherapies such as immune checkpoint inhibitors, providing insight into the biological mechanisms of cancer treatment at the individual patient level.