Selective scoring of drug effects in multicellular co-culture systems

Abstract

Multicellular co-culture screening reveals compound effects that depend on cell-cell interactions. Standard dose-response metrics fail to resolve effects that arise either from target-effector cell interactions or from non-specific toxic effects. Here, we developed Co-culture Efficacy Score (CES), a robust computational framework that enables systematic identification of compounds that selectively modulate cellular interactions in multicellular assays. CES framework supports both therapeutic scoring that penalizes direct effector cell toxicity, as well as a mechanistic discovery that estimates immunomodulatory effects by adjusting for effector cell responses. When screening 527 compounds across 10 hematological cancer models co-cultured with natural killer (NK) cells, CES distinguished co-culture-specific immunomodulatory effects from NK cell toxicity and cancer cell inhibitory responses, recovering systematic enhancer and inhibitory patterns. We further assessed CES robustness using higher-resolution validation screens and demonstrated its applicability to identify selective compounds in anti-CD19 CAR T-cell and antiviral host-pathogen screens. To facilitate its broad use, we implemented CES as an interactive web-application for quantitative analysis of compound responses in co-culture assays, providing a widely applicable scoring framework for cancer immunotherapy, antiviral screening and drug discovery.