Cancer is a leading cause of death and despite many new drugs, a major diagnostic challenge remains knowing which drug will work best for a patient. A new class of drugs called immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, current diagnostic methods (e.g. PDL1, MSI and TMB) do not accurately predict which patients will respond.
Elephas is developing a diagnostic platform using small 3D Live Tumor Fragments (LTFs) from participants for accurate prediction of drug response with a focus on ICIs such as Pembrolizumab (Keytruda). These LTFs contain both tumor cells and infiltrating immune cells, which are critical in determining response to ICIs and other immunotherapies.
In this observational clinical trial, 200 Non-Small Cell Lung Cancer (NSCLC) participants will be recruited and their actual clinical response to ICIs (using RECIST 1.1) will be compared to the platform's predictive Artificial Intelligence (AI) score that is based on RNA, clinical data, and 3D microscopy images. The sensitivity and specificity of the platform's score will be determined and compared to current diagnostic methods for ICIs like PDL1, MSI, and TMB.