The National Cancer Institute (NCI) awarded a $419,133 Project Grant under CFDA 93.394 Cancer Detection and Diagnosis Research to the Massachusetts Institute of Technology (MIT) to develop an "AscitesPredict" technology platform. This platform uses single-cell analysis and machine learning to evaluate cell identities and therapeutic sensitivities in patient-derived ascites samples, which can provide insights to overcome cancer drug resistance. The 3-year project aims to further validate the technical and biological performance of this zero-passage "ex vivo tumor biosensor" technology, and demonstrate its ability to evaluate the effects of a wider range of therapeutic agents, including those targeting immune and stromal cells. The goal is to prepare this technology for broader deployment in research settings to support preclinical drug development, and ultimately enable its launch as a clinical companion diagnostic.