Nanopore-based quantification of viral vectors and nanoparticles as an analytical tool for gene therapy products.

Abstract

Gene therapy, gene editing, and cell therapy are the new frontiers of medicine, delivering treatments to diseases that no conventional therapeutic (small molecule drugs) could effectively target. These therapeutic technologies typically leverage viral vector-based carrier particles to deliver the gene therapy cargo to the target cells and tissues. A significant challenge in this field lies in process development and optimization, where the parameters involved in the production of the particles can be standardized and tuned to improve the efficacy or yield of the final therapeutic product. However, analytical tools that track the properties of the particles produced in each iteration and connecting them to biological efficacy are currently lacking. In this work, we demonstrate a proof-of-concept study of our device which leverages multi-channel measurements of solid-state nanopores to obtain properties of protein-decorated fluorescent beads (reference sample) as well as lentiviral vectors (therapeutic sample). The nanopore measurements provide single-particle metrics such as size and relative density, as well as bulk metrics such as particle concentration, average surface charge, and aggregation rates. Existing quantification methods of viral vectors rely on fluorescent reporter genes in infectious titer experiments or antibody-based potency assays, which do not directly inform the developer of the composition of the viral batch. These methods are labor and material intensive, lack sufficient precision, require many assay design iterations for each product, and often do not translate to development of the final therapeutic product (once the reporter genes are replaced with therapeutic cargo). Our nanopore-based quantification device can substitute in for many of these assays during upstream development to enable well-informed, rapid optimization of process parameters on the viral vector, which may ultimately improve the translatability, efficacy, time-to-market, and success of breakthrough gene therapies.