Glioblastoma (GBM) remains among the most difficult-to-treat cancers with 5-year survival rates of <5% despite intensive standard-of-care therapy. The grim reality is that virtually all clinical trials failed over the past 20 years, which can be attributed to the large differences among GBM patients and the heterogeneous and plastic nature of each individual tumor. The identification of small groups of exceptional responding patients in many trials highlights that better selection procedures could significantly improve clinical outcomes. While the classical approach of matching patients and therapies by bulk genomic profiling did not lead to improvements in GBM outcome, functional precision oncology (FPO) assays offer an attractive alternative to speed up the gathering of actionable insights. In this project, we aim at founding a new spin-off company that leverages on next-generation FPO assays using single-cell drug response profiling in GBM, for which workflows and instrumentation will be developed. Using this FPO workflow, we will collect single-cell molecular signatures related to a multitude of therapeutic perturbations in patient-derived GBM cultures and fresh surgical samples and link these to clinical outcome by performing an observational clinical trial. The resulting algorithms will lay the foundation for a new diagnostic framework to better match patients to the most active drug/combination. Finally, by incrementally collecting thousands to millions of single-cell drug response profiles in the ‘Single-cell drUg ResPonse AnalySiS’ (SURPASS) database, we will create a state-of-the-art data framework against which newly designed drug/combinations can be mapped/screened (as part of a service to academia and pharma end users), while enabling our company to identify novel drug targets using advanced artificial intelligence screening.