(572c) Efficient Intracellular Delivery of CRISPR Payloads Mediated By a Polymeric Vehicle Discovered through Combinatorial Design and High-Throughput Experimentation
AIChE Annual Meeting
Wednesday, November 18, 2020 - 8:30am to 8:45am
The current paradigm of polymer design involves inefficient empirical approaches centered on synthesizing, characterizing and evaluating âone-structure-at-a-timeâ . On the other hand, ab initio prediction of gene editing efficiency directly from polymerl structure faces roadblocks due to limited mechanistic understanding. To accelerate de novo discovery of polymeric vectors, we must diversify the pool of candidate materials and build statistical frameworks that systematically capture biophysical trends correlating structure, properties, and performance in disease-relevant tissues. To this end, a chemically diverse library of well-defined statistical copolymers was synthesized and complexed with clinically relevant genetic payloads such as plasmid DNA and ribonucleoprotein complexes (RNP). These formulations were subjected to high-throughput screening assays to identify hit polymers for each payload. The hit polymer was benchmarked against commercial reagents marketed for RNP delivery, an was found to outperform state-of-the-art reagents such as Lipofectamine 2000, Lipofectamine CRISPRMAX, JetCRISPR and JetPEI. While Lipofectamine CRISPRMAX achieved editing in only 26% of cells, our hit formulations resulted in gene editing in up to 58% of cells. Further, preliminary data indicates that in addition to facilitating gene knockouts via non-homologous end joining (NHEJ), our polymer can co-deliver donor DNA plasmids with the RNP payload to achieve gene knock in via homology-directed repair (HDR) pathways.
Subsequently, we deployed statistical tools to identify the structural drivers for cellular internalization of RNP payloads, cell viability and transfection efficiency and mined structure-function correlations. These predictive relationships shed light on the critical role played by hydrophobic design motifs in mediating efficient gene editing and can aid experimentalists engaged in polymer synthesis for diverse gene therapy applications .This data-driven approach has yielded an efficient vector discovery pipeline and led to the identification of a delivery system that does not conform to traditional heuristics.