(572c) Efficient Intracellular Delivery of CRISPR Payloads Mediated By a Polymeric Vehicle Discovered through Combinatorial Design and High-Throughput Experimentation | AIChE

(572c) Efficient Intracellular Delivery of CRISPR Payloads Mediated By a Polymeric Vehicle Discovered through Combinatorial Design and High-Throughput Experimentation


Kumar, R. - Presenter, University of Mi
Le, N., University of Minnesota
Tan, Z., University of Minnesota
Reineke, T. M., University of Minnesota
The evolution of genome editing strategies such as CRISPR/Cas9 is rapidly transforming genetic research and personalized medicine. Despite the emergence of sophisticated gene editing tools with increasing specificity and safety, clinical translation has been hindered by challenges in engineering delivery vehicles. Vehicles must juggle multiple functions: package multiple payloads into nanostructures that undergo efficient cellular internalization, provide storage stability and maintain payload integrity by preventing degradation, and finally release the payload at the target tissue within a desirable spatiotemporal window. While current viral vectors, including adenoassociated viruses (AAVs), have provided clinical success for treating several diseases, the astronomical costs per dose ($0.4M–$2.1M for current FDA-approved therapies) is likely to cause immense financial strain on the healthcare system. These costs are driven in part by the expensive and lengthy processes to optimize and mass-manufacture clinical grade viral carriers. Moreover, the limited cargo capacity of viral carriers and immune responses provoked at higher doses has driven this field towards synthetic substitutes that offer lower costs, scalability, and safer clinical outcomes for repeat administration.

The current paradigm of polymer design involves inefficient empirical approaches centered on synthesizing, characterizing and evaluating “one-structure-at-a-time” . 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.