Most patients with advanced ovarian cancer (OC) relapse and progress despite systemic therapy, pointing to the need for improved and tailored therapy options. Functional precision medicine can help to identify effective therapies for individual patients in a clinically relevant timeframe. Here, we present a scalable functional precision medicine platform: DETECt (Drug Efficacy Testing in Ex vivo 3D Cultures), where the responses of primary patient cells to drugs and drug combinations are tested with live-cell imaging. We demonstrate the delivery of individual drug sensitivity profiles in 20 samples from 16 patients with ovarian cancer in both 2D and 3D culture formats, achieving over 90% success rate in providing actionable data six days after operation. All patients in this cohort received carboplatin as treatment and the ex vivo carboplatin drug response scores were significantly different between patients with a complete clinical response and those with a partial response or progression (p<0.05). In addition, carboplatin ex vivo response also predicted progression free interval (PFI) of patients (p<0.05). We find that the 3D culture format better retains proliferation and characteristics of the in vivo setting. Using the DETECt platform we evaluate 27 tailored combinations with results ready 10 days after operation. Notably, carboplatin and A-1331852 (Bcl-xL inhibitor) showed an additive effect in four of eight OC samples tested. Interestingly, afatinib treatment led to an increase of BIM and Bcl-xL expression in OC cells, which could be reversed by Bcl-xL inhibition, leading to increased cell death and synergy in 5/7 OC models. In conclusion, our 3D DETECt platform can rapidly define potential, clinically relevant data on efficacy of existing drugs in OC for precision medicine purposes, as well as provide insights on emerging drugs and drug combinations that warrant testing in clinical trials.