Modeling the Kinetics of Lipid-Nanoparticle- Mediated Delivery of Multiple siRNAs to Evaluate the Effect on Competition for Ago2.

Drug combinations can improve the control of diseases involving redundant and highly regulated pathways. Validating a multi-target therapy early in drug development remains difficult. Small interfering RNAs (siRNAs) are routinely used to selectively silence a target of interest. Owing to the ease of design and synthesis, siRNAs hold promise for combination therapies. Combining siRNAs against multiple targets remains an attractive approach to interrogating highly regulated pathways. Currently, questions remain regarding how broadly such an approach can be applied, since siRNAs have been shown to compete with one another for binding to Argonaute2 (Ago2), the protein responsible for initiating siRNA-mediated mRNA degradation. Mathematical modeling, coupled with in vitro and in vivo experiments, led us to conclude that endosomal escape kinetics had the highest impact on Ago2 depletion by competing lipid-nanoparticle (LNP)-formulated siRNAs. This, in turn, affected the level of competition observed between them. A future application of this model would be to optimize delivery of desired siRNA combinations in vitro to attenuate competition and maximize the combined therapeutic effect.

Stabilization of Ostwald ripening in low molecular weight amino lipid nanoparticles for systemic delivery of siRNA therapeutics.

Lipid nanoparticles (LNPs) represent the most clinically advanced technology for the systemic delivery of therapeutic siRNA in vivo. Toward this end, a novel class of LNPs comprising low molecular weight (MW) ionizable amino lipids having asymmetric architecture was recently reported.1 LNPs of these amino lipids, termed asymmetric LNPs, were shown to be highly efficacious and well tolerated in vivo; advances were enabled by improved endosomal escape, coupled with enhanced amino lipid metabolism and clearance. In this work, we show that, in contrast to their desirable pharmacological performance, asymmetric LNPs present a significant pharmaceutical developability challenge, namely physical instability limiting extended shelf life. Using orthogonal characterization methods, we identify the mechanism of LNP instability as Ostwald ripening and establish it to be driven predominantly by the asymmetric amino lipid component. Through rational optimization of LNP physical and macromolecular properties, we are able to significantly attenuate or entirely eliminate the Ostwald ripening instability. Modulation of LNP size, for example, effectively halts particle growth. Similarly, optimization of LNP macromolecular packing through deliberate selection of structurally matched colipids significantly diminishes the rate of ripening. This later experimental observation is substantiated by molecular dynamics simulations of LNP self-assembly, which establish a quantitative dependence of LNP macromolecular order on colipid structure. In totality, the experimental and molecular dynamics outcomes of this work support the rational design of LNP physical and chemical properties leading to effective Ostwald ripening stabilization and enable the advance of asymmetric LNPs as a clinic-ready platform for siRNA therapeutics.

Mechanism of macromolecular structure evolution in self-assembled lipid nanoparticles for siRNA delivery.

Lipid nanoparticles (LNPs) are a leading platform for therapeutic delivery of small interfering RNAs (siRNAs). Optimization of LNPs as therapeutic products is enabled by the development of structure-activity relationships (SAR) linking LNP physiochemical and macromolecular properties to bioperformance. Methods by which LNP properties can be rationally manipulated are thus critical enablers of this fundamental knowledge build. In this work, we present a mechanistic study of LNP self-assembly via a rapid antisolvent precipitation process and identify critical physiochemical and kinetic parameters governing the evolution of LNP three-dimensional macromolecular structure as a biorelevant SAR feature. Using small-angle X-ray scattering, LNPs are shown to undergo a temporal evolution in macromolecular structure during self-assembly, rearranging from initially disordered phases after precipitation into well-ordered structures following a necessary annealing stage of the assembly sequence. The ability of LNPs to undergo structural reorganization is shown to be effected by the chemical nature of the aqueous antisolvent used for precipitation. Antisolvents of varying buffering species differentially influence LNP macromolecular features, revealing a new participatory role of buffer ions in LNP self-assembly. Furthermore, the formation of macromolecular structure in LNPs is shown to improve the efficiency of siRNA encapsulation, thereby offering a simple, nonchemical route for preparation of high-payload LNPs that minimize the dose of lipid excipients. The developed LNP precipitation process and mechanistic understanding of self-assembly are shown to be generalizable, enabling the production of LNPs with a tunable range of macromolecular features, as evidenced by the cubic, hexagonal, and oligo-lamellar phase LNPs exemplarily generated.

Polydispersity characterization of lipid nanoparticles for siRNA delivery using multiple detection size-exclusion chromatography.

The development of lipid nanoparticle (LNP) based small interfering RNA (siRNA) therapeutics presents unique pharmaceutical and regulatory challenges. In contrast to small molecule drugs that are highly pure and well-defined, LNP drug products can exhibit heterogeneity in size, composition, surface property, or morphology. The potential for batch heterogeneity introduces a complexity that must be confronted in order to successfully develop and ensure quality in LNP pharmaceuticals. Currently, there is a lack of scientific knowledge in the heterogeneity of LNPs as well as high-resolution techniques that permit this evaluation. This article reports a size-exclusion chromatography (SEC) method that permits the high-resolution analysis of LNP size distribution in its native solution condition. When coupled with multiple detection systems including UV-vis, multi-angle light scattering, and refractive index, on-line characterization of the distributions in size, molecular weight, and siRNA cargo loading of LNPs could be achieved. Six LNPs with sizes in the rang of 60-140 nm were evaluated and it was found that the SEC separation is efficient, highly reproducible, and can be broadly applied to a diverse range of LNPs. A comparison between the current SEC method and asymmetric field flow fractionation (FFF) shows that the current method provides similar size distribution results on LNPs compared to FFF. Two representative LNPs with similar bulk properties were evaluated in-depth using the SEC method along with two other sizing techniques-dynamic light scattering and cryo-TEM. Profound differences in batch polydispersity were observed between them. Despite the similarity in the particle assembly process, it was found that one LNP (A) possessed a narrow size and molecular weight distribution while the other (B) was polydisperse. The present results suggest that LNP drug products are highly complex and diverse in nature, and care should be taken in examining and understanding them to ensure quality and consistency. The method developed here can not only serve as a method for understanding LNP product property, permitting control on product quality, but also could serve as a potential manufacturing method for product purification. Understandings obtained in this work can help to facilitate the development of LNPs as a well-defined pharmaceutical product.

Analysis of lipid nanoparticles by Cryo-EM for characterizing siRNA delivery vehicles.

Lipid nanoparticles are self-assembling, dynamic structures commonly used as carriers of siRNA, DNA, and small molecular therapeutics. Quantitative analysis of particle characteristics such as morphological features can be very informative as biophysical properties are known to influence biological activity, biodistribution, and toxicity. However, accurate characterization of particle attributes and population distributions is difficult. Cryo-Electron Microscopy (Cryo-EM) is a leading characterization method and can reveal diversity in particle size, shape and lamellarity, however, this approach is traditionally used for qualitative review or low throughput image analysis due to inherent EM micrograph contrast characteristics and artifacts in the images which limit extraction of quantitative feature values. In this paper we describe the development of a semiautomatic image analysis framework to facilitate reliable image enhancement, object segmentation, and quantification of nanoparticle attributes in Cryo-EM micrographs. We apply this approach to characterize two formulations of siRNA-loaded lipid nanoparticles composed of cationic lipid, cholesterol, and poly(ethylene glycol)-lipid, where the formulations differ only by input component ratios. We found Cryo-EM image analysis provided reliable size and morphology information as well as the detection of smaller particle populations that were not detected by standard dynamic light scattering (DLS) analysis.

Synthesis of a stable analog of the phosphorylated form of CheY: phosphono-CheY.

The chemical modification of a cysteinyl residue of D57C CheY by the addition of a phosphonomethyl group, (HO)(2)P(O)-CH(2)-, is described. This modification produces a nonlabile analog of an aspartyl phosphate residue in the active form of CheY. The chemically modified protein, phosphono-CheY, is suitable for structural and functional studies. An extensive discussion of the synthetic methodology and purification strategy is presented. A detailed protocol is given.