A Proximity-Dependent Biosensor System for Visualizing Cell-Cell Interactions Induced by Therapeutic Antibodies.

Despite the promise of therapeutic antibodies in engaging the immune system to eliminate malignant cells, many aspects of the complex interplay between immune cells and cancer cells induced by antibody therapy remain incompletely understood. This study aimed to develop a biosensor system that can evaluate direct cell-cell physical contact and interactions between immune effector and target cells induced by therapeutic antibodies in physiologically relevant environments. The system uses two structural complementary luciferase units (SmBit and LgBit) expressed on the respective membranes of effector and target cells. Upon cell-cell contact, the two subunits form active NanoLuc, generating a luminescent signal, allowing for real-time monitoring of cell-cell interactions and quantitatively assessing the pharmacological effects of therapeutic antibodies. We optimized the system to ensure selectivity by adjusting the spacer lengths between two luciferase units to minimize interference from nonspecific intercellular contact. The system was applied to quantitatively monitor cell-cell interactions between NK and target cells induced by rituximab and between T and target cells induced by blinatumomab in a 3D cell culture system. The biosensor system has the potential to characterize antibody pharmacology through a deeper understanding of antibody-mediated cell-cell interactions.

Development of bispecific T cell engagers: harnessing quantitative systems pharmacology.

Bispecific T cell engagers (bsTCEs) have emerged as a promising class of cancer immunotherapy. Several bsTCEs have achieved marketing approval; dozens more are under clinical investigation. However, the clinical development of bsTCEs remains rife with challenges, including nuanced pharmacology, limited translatability of preclinical findings, frequent on-target toxicity, and convoluted dosing regimens. In this opinion article we present a distinct perspective on how quantitative systems pharmacology (QSP) can serve as a powerful tool for overcoming these obstacles. Recent advances in QSP modeling have empowered developers of bsTCEs to gain a deeper understanding of their context-dependent pharmacology, bridge gaps in experimental data, guide first-in-human (FIH) dose selection, design dosing regimens with expanded therapeutic windows, and improve long-term treatment outcomes. We use recent case studies to exemplify the potential of QSP techniques to support future bsTCE development.