Researchers developed a clinically applicable mathematical model that can predict patient outcomes to immunotherapy, while also acting as a tool for personalized oncology and for engineering proper immunotherapy regimens, according to a study published in Science Advances.1-2
This model calculates a predicted response on a per-patient basis, enabling it to provide a framework for individualized treatment strategies.2 More, the parameters of the model successfully differentiate between pseudo-progression from true progression, ultimately providing unidentified insights into the characteristics of pseudo-progression.
“This paper applied a refined mechanistic mathematical model of immunotherapy response to a prospective clinical trial of checkpoint inhibitor therapy, validated with two separate cohorts representing various immunotherapy drugs, drug mechanisms, and cancer types, to…
