ABSTRACT Monoclonal antibody therapies now account for the majority of blockbuster drugs and the number and breadth of diseases tackled by this therapeutic modality are expected to rapidly grow in the coming decade. However, existing discovery technologies force users to choose between performance and cost. There is a need for advanced discovery tools that provide a better functional picture of performance during initial high-throughput screening. An ideal solution that can democratize antibody discovery would also be easily accessible, leveraging existing equipment in pharmaceutical, biotech, and research laboratories. Partillion is developing and commercializing a specialized hydrogel microparticle reagent (“nanovials”) that enables ultra high-throughput sorting of single antibody secreting cells based on functional properties of secreted antibodies, all using standard lab equipment and widely-available flow cytometers. Expanding on Phase I work and successful demonstration of antibody discovery from plasma cells based on antigen-specific binding, in this Phase II proposal Partillion will develop nanovial workflows to enable single-cell functional assays (binding of secreted antibodies to cell-surface expressed targets and receptors that triggers signaling pathway activation) for our end users. These capabilities can provide dramatic improvements in discovery workflows by minimizing the number of non-functional sequences that have to be synthesized, introduced into cell lines, produced, and tested in large well-plate formats downstream. Here we propose to develop on-nanovial functional screening assays for (i) binding to cell-surface- expressed targets and (ii) receptor agonism, and benchmark the antibody sequences discovered with these approaches against sequences recovered using standard hybridoma, and direct B cell Receptor (BCR) antigen baiting workflows. Enabling more companies and institutes to access cutting-edge drug discovery capabilities economically will also drive further development of therapeutic candidates for rare diseases and more crowded “common diseases”, which ultimately will yield cost savings to the health systems and better outcomes for more patients.