High throughput method for preparing lipid nanoparticles and uses thereof - Patents.com

Abstract

Provided herein are high-throughput methods and uses thereof for optimizing and producing various lipid nanoparticle (LNP) compositions. In some embodiments, the present disclosure provides a high-throughput screening method for producing LNP compositions, comprising obtaining at least two mixable solutions containing a payload and a plurality of molecules capable of self-assembly, and mixing the at least two solutions under a set of controlled conditions, whereby the order, speed, volume, phase ratio and duration of mixing of the at least two solutions are varied. In various embodiments, the present disclosure allows for determining optimal encapsulation efficiency, particle size distribution, purification and particle recovery, and formulation stability. The methods disclosed herein allow for efficient optimization of manufacturing conditions for the preparation of LNP-based therapeutics.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 272,136, filed October 26, 2021, the contents of which are incorporated by reference in their entirety into this specification. [Background technology]

[0002] Lipid nanoparticles (LNPs) have been widely developed as a biocompatible and stable pharmaceutical delivery platform. The lipids used to prepare lipid nanoparticles are usually physiological lipids (biocompatible and biodegradable) with low toxicity. The physicochemical diversity and biocompatibility of lipids and their ability to enhance oral bioavailability of drugs make lipid nanoparticles very attractive carriers for drug delivery. Furthermore, lipid-based formulations can positively affect drug absorption in several ways, including increasing solubilization capacity, preventing drug precipitation upon intestinal dilution, enhancing membrane permeability, inhibiting efflux transporters, reducing CYP enzymes, enhancing chylomicron production and lymphatic transport. LNPs are the leading non-viral carriers for siRNA delivery and are used in 70% of nanomedicine clinical trials as of 2019. Anselmo S et al.,2019,Bioeng.Transl.Med.4(3):e10143.

[0003]

[0003] Lipid-based nanocarriers bring additional challenges in the quality control of drug products, due in part to their complex physicochemical properties. According to the guidance on liposomal drug products recently published by the US FDA, these formulations should be specified for quality attributes including particle structure and size distribution, physicochemical properties of the particle surface, lipid content, amount of free API and encapsulation efficiency, and physical and chemical stability. Different preparation conditions and parameters can affect the quality attributes of LNP formulations. For example, lipid composition, especially the incorporation of different amounts and / or molecular weights of PEGylated lipids, significantly affected the colloidal stability, cellular uptake, and pharmacokinetics of liposomes (see, e.g., Allen et al., 1991, Biochem Biophys Acta, 1066(1):29-36; Garbuzenko et al., 2005, Chem Phys Lipids, 135(2):117-29; Immordino et al., Int J Nanomedicine 1(3)(2006)297-315), while siRNA or ASO loading can be controlled by charge-mediated interactions with cationic lipids. Schroeder et al., 2010, J Intern Med 267(1):9-21; Cullis et al., 2017, Mol Ther 25(7):1467-1475. The downstream performance of LNPs is also highly dependent on their quality attributes. Therefore, screening of these parameters at various levels is in high demand for a high-throughput approach with easy procedures and multiple analytical outputs.

[0004]

[0004] LNP structure and cargo delivery are regulated by four major components: ionizable lipids, helper phospholipids, cholesterol, and polyethylene glycol lipids (PEG-lipids). Cationic ionizable lipids promote encapsulation of negatively charged nucleic acids during LNP formulation and aid in cytoplasmic delivery of cargo at the endosomal pH range of 5.5-6.5. Helper lipids and cholesterol enhance structural stability, promote membrane fusion, and facilitate endosomal escape of LNPs. The effect of PEG-lipid addition is multifaceted and contributes to what is called the "PEG-dilemma." PEG-lipids are necessary to control particle size and prevent particle aggregation during self-assembly. However, the hydrophilic PEG corona may hinder interaction of the particle surface with lipophilic cell membranes, resulting in poor cellular internalization. The presence of PEG may also hinder surface binding of transport proteins required for LNP cellular internalization via receptor-mediated endocytosis. Additionally, PEG-lipids extend LNP circulation time in vivo by acting as a steric barrier to adsorption of plasma proteins, including opsonins. Although extending half-life increases exposure to therapeutics, increasing LNP circulation may induce the generation of anti-PEG antibodies that can lead to adverse allergic reactions.

[0005] Thus, achieving effective intracellular delivery is highly dependent on understanding the effectiveness of multivalent PEG-lipids to overcome the PEG dilemma. Previous studies have shown that adjusting the size, structure, content, carbon tail type, and length of PEG modulates the efficacy of LNPs. Summary of the Invention

[0006] To address the need for screening and optimization of lipid-based nanomedicines, the present disclosure provides a high-throughput screening (HTS) workflow for preparing such lipid-based nanoparticles encapsulating various therapeutic payloads. In various embodiments, the present invention provides an optimized solvent injection method for facile self-assembly of LNPs using a robotic liquid handler. In various embodiments, optimal lipid composition, total lipid concentration, and payload loading are described.

[0007]

[0007] In various embodiments, the present disclosure relates to an optimized high throughput screening method for producing lipid nanoparticle (LNP) preparations, the method comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having various compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to obtain a lipid nanoparticle (LNP) preparation using the robotic liquid handler under conditions suitable for LNP formation. obtaining lipid nanoparticles encapsulating erode, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, phase, buffer type and pH selection, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration are varied among different wells by mixing the first solution and the second solution to obtain lipid nanoparticles; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0008]

[0008] As described herein, lipid nanoparticles (LNPs) are increasingly being utilized to improve the delivery efficiency and therapeutic efficacy of nucleic acids. It has been found that various formulation parameters can affect the quality attributes of these nanoparticle formulations. However, currently, there is a lack of effective systematic screening approaches to address these challenges. In accordance with the present invention, an automated high-throughput screening (HTS) workflow has been developed for the streamlined preparation and analytical characterization of LNPs, e.g., loaded with antisense oligonucleotides (ASOs). In accordance with the present invention, this characterization can be performed in as little as 3 hours for an entire 96-well plate.

[0009] According to the present invention, ASO-loaded LNPs were formulated by automated solvent injection using a robotic liquid handler and evaluated for particle size distribution, encapsulation efficiency, and stability with different formulation compositions and ASO loadings. The results presented herein show that the PEGylated lipid content significantly influences the particle size distribution, and the ionizable lipid / ASO charge ratio influences the ASO encapsulation efficiency. Furthermore, the results of our HTS approach correlate with the results of state-of-the-art scale-up methods using microfluidic formulators, providing a novel method for robust formulation development and experimental method design. This method can reduce material usage by approximately 10-fold, thereby improving analytical results and information accumulation by approximately 100-fold.

[0010] A novel HTS workflow was developed to prepare ASO-LNPs and analyze the relationship between their PEG-lipid content and particle size distribution. Using a high-throughput liquid handler, a library of ASO-LNPs containing multiple PEG-lipids spanning the phosphoglyceride, diglyceride, and ceramide families was created and formulated with various PEG-lipid molar ratios (1-5 mol%). Herein, we describe the influence of PEG-lipid parameters including molecular weight (mw), carbon tail length, and molar ratio. Additionally, we describe a number of additional PEG-lipid variables, including PEG structure, lipid tail saturation, PEG-lipid charge, and linker chemistry.

[0011]

[0011] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 500 and 3000 nucleotides. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0012] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0013] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic or ionizable lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0014] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0015]

[0015] In various embodiments, the present disclosure relates to a high throughput method for optimizing a process for producing lipid nanoparticle (LNP) preparations, the method comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to form LNPs using the robotic liquid handler. obtaining lipid nanoparticles encapsulating a payload, comprising: mixing the first solution and the second solution to obtain lipid nanoparticles, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration are varied among different wells; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0016]

[0016] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0017] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0018] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0019] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0020]

[0020] In various embodiments, the present disclosure relates to an optimized high throughput method for encapsulating a payload in a lipid nanoparticle (LNP) preparation, the method comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to form LNPs using the robotic liquid handler. obtaining lipid nanoparticles encapsulating a payload, comprising: mixing the first solution and the second solution to obtain lipid nanoparticles, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration are varied among different wells; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0021]

[0021] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0022] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0023] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0024] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0025]

[0025] In various embodiments, the present disclosure relates to a method of administering an LNP preparation to a patient in need thereof, the LNP preparation comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to encapsulate the payload using the robotic liquid handler under conditions suitable for LNP formation. obtaining lipid nanoparticles by mixing the first solution and the second solution under at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration, varying between different wells; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0026]

[0026] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0027] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0028] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0029] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0030]

[0030] In various embodiments, the present disclosure relates to an optimized high throughput method for encapsulating a payload in a lipid nanoparticle (LNP) preparation, the method comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to form LNPs using the robotic liquid handler. obtaining lipid nanoparticles encapsulating a payload, comprising: mixing the first solution and the second solution to obtain lipid nanoparticles, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration are varied among different wells; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0031]

[0031] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0032] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0033] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0034] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0035]

[0035] In various embodiments, the present disclosure relates to an optimized high throughput screening method for producing lipid nanoparticle (LNP) preparations, the method comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having various compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to obtain a lipid nanoparticle (LNP) preparation using the robotic liquid handler under conditions suitable for LNP formation. obtaining lipid nanoparticles encapsulating erode, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, phase, buffer type and pH selection, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration are varied among different wells by mixing the first solution and the second solution to obtain lipid nanoparticles; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0036]

[0036] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0037] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0038] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0039] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0040]

[0040] In various embodiments, the present disclosure relates to an optimized high throughput method for encapsulating a payload in a lipid nanoparticle (LNP) preparation, the method comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to form LNPs using the robotic liquid handler. obtaining lipid nanoparticles encapsulating a payload, comprising: mixing the first solution and the second solution to obtain lipid nanoparticles, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration are varied among different wells; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0041]

[0041] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0042] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0043] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0044] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0045] In various embodiments, the present disclosure provides a method for preparing lipid nanoparticles comprising the steps of: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to obtain lipid nanoparticles encapsulating the payload using the robotic liquid handler under conditions suitable for LNP formation, wherein the following conditions are met: the first solution is a lipid nanoparticle capable of self-assembly; f. mixing the first solution and the second solution to obtain lipid nanoparticles, wherein at least one of the composition ratio of the self-assembling molecules, the ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration is varied between different wells; f. measuring at least one of the encapsulation efficiency, particle size distribution, purification and particle recovery, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0046]

[0046] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0047] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0048] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0049] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0050] In various embodiments, the present disclosure relates to an optimized high throughput method for encapsulating a payload in a lipid nanoparticle (LNP) preparation, the method comprising: a. obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; c. dissolving at least one payload molecule in either the first solution or the second solution; d. preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; e. mixing the first solution and the second solution to form LNPs using the robotic liquid handler. obtaining lipid nanoparticles encapsulating a payload, comprising: mixing the first solution and the second solution to obtain lipid nanoparticles, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration are varied among different wells; f. measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery rate, and formulation stability of the LNPs; g. determining optimal parameters for producing the LNP preparation; and h. producing the LNP preparation based on the optimal parameters.

[0051]

[0051] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. In various embodiments, the oligonucleotide is between about 10 and about 30 nucleotides in length. In various embodiments, the payload is an mRNA. In various embodiments, the size of the mRNA is between about 1 kb and about 2 kb. In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and about 10,000 Da. In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da.

[0052] In various embodiments, the payload is dissolved in a first solution. In various embodiments, the payload is dissolved in a second solution. In various embodiments, the first solution is an aqueous buffer. In various embodiments, the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer. In various embodiments, the organic phase of the second solution comprises methanol. In various embodiments, the organic phase of the second solution comprises ethanol.

[0053] In various embodiments, the self-assembling molecule comprises at least one lipid component comprised of at least one lipid molecule. In various embodiments, the at least one lipid molecule is selected from cationic lipid species, non-cationic lipid species, and phospholipid species. In various embodiments, the second solution comprises two or more lipid species. In various embodiments, the total lipid concentration varies. In various embodiments, the total lipid concentration varies between about 0.4 mM and about 4 mM. In various embodiments, the percentage of lipid that is PEGylated varies. In various embodiments, the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5.

[0054] In various embodiments, the LNP is a polymeric lipid nanoparticle. In various embodiments, the LNP is a liposome. In various embodiments, the LNP is a lipoprotein nanoparticle. In various embodiments, the first solution is injected into the second solution. In various embodiments, the second solution is injected into the first solution. In various embodiments, the optimal parameters are those that result in greater than 80% payload encapsulation efficiency. In various embodiments, the optimal parameters are those that result in LNPs with a monomodal size distribution and a polydispersity of less than about 30% and an average diameter of 80-200 nm. In various embodiments, the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

[0055]

[0055] In various embodiments, the present disclosure relates to a workflow for HTS screening of multiple parameters for LNP formation, comprising: (i) a robotic liquid handler; (ii) at least one instrument capable of measuring desired LNP properties; and (iii) at least one microplate containing a plurality of microwells, wherein the robotic liquid handler is capable of injecting a plurality of solutions into each of the microwells; the parameters are systematically varied among microwells; and the desired LNP properties can be measured for each microwell.

[0056] In various embodiments, the parameters are selected from total lipid content, type of self-assembling molecules; composition ratio of the self-assembling molecules; ratio and / or concentration of the self-assembling molecules to the payload; selection of phase, buffer type and pH, injection sequence, volume and rate, and mixing duration. In various embodiments, the desired LNP properties are selected from the group consisting of average particle size, particle size distribution, encapsulation efficiency, and particle stability. In various embodiments, the instrument is capable of either dynamic light scattering (DLS), ultraviolet-visible (UV-Vis) spectroscopy, or fluorescence spectroscopy. [Brief description of the drawings]

[0057] [Figure 1A-F]

[0057] Data for homogeneous LNPs with high ASO loading produced by rapid ethanol-buffer injection followed by multiple mixing. LNPs composed of 0.4 μmol total lipid and 1.5 mol% DSPE-PEG2000 were mixed with ASO-1 under an N / P ratio of 1 using different mixing conditions. Using a TECAN® robot, the reverse injection order (ethanol to buffer or buffer to ethanol) at rates of 0.1, 0.5, or 0.9 ml / s followed by 10 mixing iterations (Figures 1A-1C), or ethanol to buffer injection at rates of 0.5 or 0.9 ml / s followed by 10 or 20 mixing iterations (Figures 1D-1F) were investigated. Particle size (Figures 1A and 1D) and polydispersity (Figures 1B and 1E) were measured by dynamic light scattering (DLS). Free ASO-1 was measured by OD260 and calculated for encapsulation efficiency (Figures 1C and 1F). Results are means ± SD, n = 3; ns, not significant, ****P < 0.0001, analyzed by two-way (Figures 1A-1C) or one-way (Figures 1D-1F) ANOVA followed by Tukey's multiple comparisons. [Diagram 2]

[0058] HTS workflow for ASO-loaded LNP formulations is shown. 96 samples (32 conditions, n=3) varying 4 levels of lipid composition, 2 levels of total lipid concentration, and 4 levels of ASO loading were prepared by automated solvent injection using a TECAN® liquid handler, followed by characterization of particle size distribution by DLS and ASO encapsulation by absorbance at 260 nm. A representative LEA (Laboratory Execution and Analysis) Library Studio design layout is shown for the sample plate. [Figure 3A-E]

[0059] HTS analysis of ASO-1-loaded LNP formulations. Figure 3A is an image showing the screening design. Formulation parameters including total lipid concentration (2 levels), PEGylated lipid content incorporated in the lipid composition (4 levels), and loading ratio of ASO (4 levels) were screened in 96-well plates with triplicate replicates for each condition. Figures 3B-3D show that samples were diluted in PBS and characterized for particle size distribution by DLS. Figure 3B is a graph showing representative size distributions, showing small particle populations with increasing amounts of PEGylated lipid added in the lipid composition. Figures 3C-3D are heat maps showing that LNPs had mean diameters of 45-145 nm and %PDs of 10-50%, except for large aggregates (diameters of 500-1500 nm) with a multimodal size distribution when DSPE-PEG2000 was not incorporated in the lipid composition, as indicated by the "out of range" black dots. Quantitative analysis was also shown for samples with a total lipid concentration of 2 mM. Figure 3E is a bar graph showing sample aliquots (total lipid concentration of 2 mM) of unencapsulated ASOs measured by OD260 to calculate encapsulation efficiency. Results are mean ± SD, n = 3; ns, not significant, *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 (analyzed by two-way ANOVA followed by Tukey's multiple comparisons). The data was confirmed by LC. [Figure 4]

[0060] 1 is a bar graph showing that LNPs prepared without PEGylated lipids produced large aggregates. Average particle size of ASO-1-loaded LNPs prepared without DSPE-PEG2000 (conditions screened are shown in columns A and E of Figures 3C-3D) is shown as mean ± SD, n = 3; ns, not significant, *P < 0.05, and ***P < 0.001 (analyzed by two-way ANOVA followed by Sidak's multiple comparisons). [Figure 5A-C]

[0061] HTS analysis of ASO-1 loaded, cationic LNP formulations. The screened cationic LNPs showed similar trends to MC3 LNPs with respect to mean diameters of 60-120 nm (Figure 5A), polydispersity of 10-50% (Figure 5B), and increasing amounts of PEGylated lipid. In the absence of DSPE-PEG2000, large aggregates with multimodal size distribution were produced, as indicated by the "out of range" black dots, or incomplete measurements (due to large aggregates) indicated by the white dots. Quantitative analysis was also shown for samples with a total lipid concentration of 2 mM. (Figure 5C) Samples were measured for the amount of unencapsulated ASO by OD260 to calculate encapsulation efficiency. Results are means ± SD, n = 3; ns, not significant, *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 (analyzed by two-way ANOVA followed by Tukey's (Figures 5A-5B) or Sidak's (Figure 5C) multiple comparisons). [Figure 6A-C]

[0062] HTS analysis of ASO-2-loaded LNPs formulated with ionizable lipids at 2 mM total lipid concentration, different amounts of DSPE-PEG2000, and different oligonucleotide loadings. Results showed similar trends to ASO-1-loaded LNPs (Figures 3A-3E) in terms of ASO particle size (Figure 6A), polydispersity (Figure 6B), and encapsulation efficiency (Figure 6C). Results are mean ± SD, n=3; ns, not significant, *P<0.05, **P<0.01, ***P<0.001, and ****P<0.0001 (analyzed by two-way ANOVA followed by Tukey's multiple comparisons). [Figure 7A-E]

[0063] HTS analysis results correlated with results from microfluidic preparation using NanoAssemblr®. Figure 7A is a graph showing the correlation of decreasing particle size and increasing polydispersity with increasing amount of PEGylated lipid. LNPs were prepared with different molar ratios of DSPE-PEG2000 and a fixed N / P ratio of 2. Figure 7B is a graph showing that particle size was stable under high total lipid concentration. LNPs were prepared under 0.4, 0.7, 1, or 2 mM total lipid concentration, fixed DSPE-PEG2000 of 1.5 mol%, and N / P ratio of 2. Figures 7C-7D show that particle size (Figure 7C) was stable while %EE of ASO (Figure 7D) decreased under high ASO loading and excess ASO loading. LNPs were prepared under N / P ratio = 5, 2, 1, or 0.5, and 1.5 mol% DSPE-PEG2000. Figure 7E shows representative cryo-TEM images of ASO-1-loaded LNPs prepared by nanoassemblr® or high-throughput solvent injection with different formulation parameters. The magnified images showed similar structural patterns of representative LNPs (indicated by blue arrows) prepared with the same formulation parameters using the two approaches. The HTS results in panels (Figures 7A, 7C, and 7D) are from the same screening experiment shown in Figure 3. Results are mean ± SD, n = 3 except for n = 1 for the microfluidic results in Figure 7D. [Figure 8A-B]

[0064] Figure 8 shows the stability of ASO-1-loaded MC3 LNPs prepared by high-throughput solvent injection or NanoAssemblr® at 4°C for 2 weeks. Figure 8A shows the mean particle size and Figure 8B is a graph showing the polydispersity over 2 weeks. Total lipid concentration was 2 mM, N / P ratio was 1 (HTS samples) or 0.5 (NanoAssemblr® samples), and PEG amount varied from 1.5 to 5 mol%. Results are mean ± SD, n=3; *P<0.05 and **P<0.01 versus day 0 results within each group, analyzed by one-way ANOVA followed by Dunnett's multiple comparisons. A subsequent study (not shown) showed similar results after 1 month of storage at 4°C. [Figure 9]

[0065] 8A-8B are graphs showing the stability of the HTS LNPs shown in FIGS. 8A-8B over a 2-week period at 40° C. Results are mean±SD, n=3; *P<0.05 versus day 0 results within each group, analyzed by one-way ANOVA followed by Dunnett's multiple comparisons. [Figure 10]

[0066] 1 is a graph showing ASO leakage from LNPs at 40° C. ASO-1 released from LNPs within 2 weeks was measured by OD260. Results are mean ± SD, n=3; *P<0.05 and ns, not significant, versus 1.5 mol% DSPE-PEG2000 group, analyzed by two-way ANOVA followed by Turkey's multiple comparisons. [Figure 11]

[0067] We show that the HTS approach significantly saved raw materials and improved analytical output compared to microfluidic preparation of ASO-loaded LNPs. The materials required were calculated for a typical sample with 2 mM total lipid containing 1.5 mol% DSPE-PEG 2000 and an N / P ratio (based on MC3 and ASO-1) of 1. [Figure 12A-B]

[0068] An alternative method of quantifying ASO encapsulation is shown. Figure 12A is a schematic of the workflow. ASO-loaded LNPs were prepared by high-throughput solvent injection method, mixed with the fluorescent probe Sybr-gold, and then quantified using a fluorescent plate reader (Ex / Em=495 / 550 nm). Figure 12B is a graph showing the comparable encapsulation efficiency % of two different LNP formulations prepared under different N / P ratios. Results are mean ± SD, n=2; ns, not significant. [Figure 13A]

[0069] We present the HTS workflow for HiBiT peptide-loaded liposome formulations. Two purification methods were compared, including high-throughput gel filtration and dialysis in a 96-well plate format. LNPs were synthesized by high-throughput solvent injection method followed by characterization of particle size distribution by DLS and free cargo amount by UV-Vis, luminescence and fluorescence. LNPs were then purified using either high-throughput gel filtration or dialysis followed by analysis of purification efficiency, particle recovery and size stability using UV-Vis, fluorescence and DLS, respectively. [Figure 13B]

[0070] 1 is an image showing the screening design. Formulation parameters including DPPC LNPs without MC3, DPPC LNPs with MC3, DSPC LNPs without MC3, and DSPC LNPs with MC3 containing both a shielded PEGylated lipid conjugated with azide and a PEGylated lipid were screened in 96-well plates in triplicate for each condition. [Figure 13C]

[0071] Heat map showing that LNPs had average diameters between 50 and 200 nm, except for large aggregates with a multimodal size distribution when DSPE-PEG2000 was not incorporated into the lipid composition, as indicated by the "out of range" black dots. [Fig. 13D-F]

[0072] Table showing quantification of free peptide concentration before (FIG. 13D) and after purification. Gel filtration and dialysis resulted in average purification efficiencies of about 98% (FIG. 13E) and about 61% (FIG. 13F), respectively. 96 small column plates with 40 kD MWCO were used for gel filtration and elution with PBS. A 96-well dialysis plate with 10 kD MWCO was used for dialysis in 3 L PBS overnight with 3 medium changes. Missing data points after dialysis were due to low sample recovery. [Fig. 13G-H]

[0073] Data showing quantification of particle recovery and size after purification by gel filtration. In Figure 13G, recoveries were generally between 80-120%, except for lower values ​​with aggregated samples prepared without PEGylated lipid. In Figure 13H, particle size distribution remained constant after purification by gel filtration. [Figure 14]

[0074] The general procedure described herein is shown, including LNP preparation by automated solvent injection using a robotic liquid handler (top left) and high-throughput screening (bottom left), followed by analysis of quality attributes such as particle size distribution (top right), ASO encapsulation (bottom center) and LNP stability (bottom right). [Figure 15A-F]

[0075] Schematic diagram of the ASO-LNP formulation library. A liquid-handling robot was used to form ASO-LNPs by rapidly mixing an aqueous phase containing ASO with an ethanol phase containing dissolved lipid mixtures of various PEG-lipid compositions (FIG. 15A). Each lipid mixture contained a distinct PEG-lipid selected from the phosphoglyceride, diglyceride, or ceramide (FIG. 15B) family in combination with the ionizable lipid MC3 (FIG. 15C), cholesterol (FIG. 15D), and the helper lipid DSPC (FIG. 15E), generating an ASO-LNP library with 54 different formulations. [Figure 16A-F]

[0076] Particle size distribution of ASO-LNPs. ASO-LNPs were prepared with varying types and amounts of PEGylated lipids using a liquid handling robot. The PEG-lipid analogs used in each ASO-LNP formulation are indicated with a # under the x-axis label and can be referenced from Table 1. The particle library was characterized using dynamic light scattering in a 96-well plate setup to identify particle size (Figures 16A-16C) and polydispersity trends (Figures 16D-16F) across different subsets of anionic (linear, branched) and neutral PEG-lipids as a function of PEG size (Da) shown by the x-axis value, C-tail type shown by the different colored backgrounds, and PEG-lipid content (mol%) in the ASO-LNPs shown by the color of the respective bars. [Figure 17]

[0077] The behavioral trends across the ASO-LNP HTS library are shown in Figures 16A-16C, where the mean particle diameters are represented using color-coded heat maps. [Figure 18]

[0078] We demonstrate the conversion of hit ASO-LNPs to scale-up formulations. ASO-LNP formulations were identified from 1, 3, and 5 mol% data from our HTS library and scaled up using a microfluidic mixer. The scale and technique of the two formulations were verified to allow smooth conversion by comparing their particle size distributions. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0058]

[0079] Lipid nanoparticle (LNP) manufacturing for drug delivery is challenging due to complex physicochemical properties that are influenced by various formulation parameters. Control of particle structure and size distribution, particle surface physicochemical properties, lipid content, amount and encapsulation efficiency of free API, and physical and chemical stability in LNP manufacturing are difficult and complex. Screening of LNP formulation parameters including lipid species, percentage, concentration and drug loading by traditional batch methods requires significant time and raw materials. Therefore, a high-throughput screening approach with minimal material input and efficient preparation and analysis output would be preferred to determine lead formulation candidates with optimal quality attributes. Robotic liquid handlers have been mainly used for liquid addition and transfer, and have not been used as LNP formulators with precisely tuned equipment parameters. Furthermore, there is a lack of streamlined high-throughput workflows that integrate both LNP preparation and analysis. Provided herein is a high-throughput method for optimizing LNP manufacturing based on desired properties using a robotic liquid handler for injection-based LNP formation. Further provided herein are optimized LNP particles and methods for their manufacture.

[0059]

[0080] It is to be understood that the descriptions herein are exemplary and explanatory only and are not intended to be limiting of the invention as claimed. In this application, the use of the singular includes the plural unless specifically stated otherwise.

[0060]

[0081] The section headings used herein are for organizational purposes only and should not be construed as limiting the subject matter described. All documents, or portions of documents, cited in this application, including patents, patent applications, articles, books, and papers, are expressly incorporated herein by reference in their entirety for any purpose. The following terms, when utilized in accordance with this disclosure, shall be understood to have the following meanings, unless otherwise indicated:

[0061]

[0082] In this application, the use of "or" means "and / or" unless otherwise stated. Furthermore, the use of the term "including" and other forms such as "includes" and "included" is not limiting. Additionally, terms such as "element" or "component" encompass both elements and components that include one unit or element, and components that include more than one subunit, unless otherwise specified.

[0062]

[0083] As used herein, the term "subject" refers to any animal (e.g., mammal), including but not limited to humans, non-human primates, rodents, etc., that will be the recipient of a particular treatment. Typically, the terms "subject" and "patient" are used interchangeably herein in reference to human subjects.

[0063]

[0084] The terms "polynucleotide", "nucleotide", or "nucleic acid" include both single-stranded and double-stranded nucleotide polymers. The nucleotides that comprise a polynucleotide can be ribonucleotides or deoxyribonucleotides, or modified forms of either type of nucleotide. The modifications include base modifications such as bromouridine and inosine derivatives, ribose modifications such as 2',3'-dideoxyribose, and internucleotide linkage modifications such as phosphorothioates, phosphorodithioates, phosphoroselenoates, phosphorodiselenoates, phosphoroanilothioates, phosphoroaniladates, and phosphoroamidates.

[0064]

[0085] The term "oligonucleotide" refers to a polynucleotide containing 200 or fewer nucleotides. Oligonucleotides can be single-stranded or double-stranded, for example, for use in constructing mutant genes. Oligonucleotides can be sense or antisense oligonucleotides. Oligonucleotides can include labels, including radioactive labels, fluorescent labels, hapten or antigen labels, for detection assays. Oligonucleotides can be used, for example, as PCR primers, cloning primers or hybridization probes.

[0065]

[0086] The term "polypeptide" or "protein" refers to a polymer having the amino acid sequence of a protein, including deletions, additions, and / or substitutions of one or more amino acids of the native sequence. The terms "polypeptide" and "protein" specifically encompass antigen-binding molecules, antibodies, or sequences having deletions, additions, and / or substitutions of one or more amino acids of an antigen-binding protein. The term "polypeptide fragment" refers to a polypeptide having an amino-terminal deletion, a carboxyl-terminal deletion, and / or an internal deletion compared to the full-length native protein. Such fragments can also contain modified amino acids compared to the native protein. Useful polypeptide fragments include immunologically functional fragments of antigen-binding molecules.

[0066]

[0087] The term "isolated" means: (i) free from at least some other proteins with which it is normally found; (ii) essentially free from other proteins from the same source, e.g., the same species; (iii) separated from at least about 50% of the polynucleotides, lipids, carbohydrates, or other materials with which it is naturally associated; (iv) in operative association (by covalent or noncovalent interactions) with polypeptides with which it is not naturally associated; or (v) not found in nature.

[0067]

[0088] A "variant" of a polypeptide (e.g., an antigen-binding molecule) includes an amino acid sequence in which one or more amino acid residues have been inserted, deleted, and / or substituted into the amino acid sequence compared to another polypeptide sequence. Variants include, for example, fusion proteins.

[0068]

[0089] The term "identity" refers to the relationship between the sequences of two or more polypeptide molecules or two or more nucleic acid molecules, as determined by aligning and comparing the sequences. "Percent identity" means the percent of identical residues between the amino acids or nucleotides in the compared molecules, and is calculated based on the size of the smallest of the molecules being compared. For these calculations, gaps in the alignment, if any, are preferably addressed by a specific mathematical model or computer program (i.e., an "algorithm").

[0069]

[0090] To calculate percent identity, the sequences to be compared are typically aligned to obtain the maximum match between sequences. One example of a computer program that can be used to determine percent identity is the GCG program package, which includes GAP (Devereux et al., Nucl. Acid Res., 1984, 12, 387; Genetics Computer Group, University of Wisconsin, Madison, Wis.). The computer algorithm GAP is used to align two polypeptides or polynucleotides whose percent sequence identity is to be determined. The sequences are aligned for optimal matching of their respective amino acids or nucleotides (the "match span" determined by the algorithm). In certain embodiments, standard comparison matrices are also used by the algorithm (e.g., for the PAM 250 comparison matrix, see Dayhoff et al., 1978, Atlas of Protein Sequence and Structure, 5:345-352; for the BLO-SUM 62 comparison matrix, see Henikoff et al., 1992, Proc. Natl. Acad. Sci. USA, 89, 10915-10919).

[0070]

[0091] The term "derivative" refers to a molecule that contains a chemical modification other than an amino acid (or nucleic acid) insertion, deletion, or substitution. In certain embodiments, a derivative contains a covalent modification, including but not limited to, chemical bonding with a polymer, lipid, or other organic or inorganic moiety. In certain embodiments, a chemically modified antigen-binding molecule can have a greater circulating half-life than an antigen-binding molecule that is not chemically modified. In some embodiments, a derivative antigen-binding molecule is covalently modified to contain one or more water-soluble polymer attachments, including but not limited to, polyethylene glycol, polyoxyethylene glycol, or polypropylene glycol.

[0071]

[0092] Peptide analogs are commonly used in the pharmaceutical industry as non-peptide drugs with properties similar to those of the template peptide. These types of non-peptide compounds are called "peptide mimetics" or "peptidomimetics." Fauchere, JL, 1986, Adv. Drug Res., 1986, 15, 29; Veber, DF & Freidinger, RM, 1985, Trends in Neuroscience, 8, 392-396; and Evans, BE, et al., 1987, J. Med. Chem., 30, 1229-1239, which are incorporated herein by reference for any purpose.

[0072]

[0093] The term "therapeutically effective amount" refers to an amount of immune cells or other therapeutic agent determined to produce a therapeutic response in a mammal. Such therapeutically effective amounts are readily ascertained by one of ordinary skill in the art.

[0073]

[0094] The terms "patient" and "subject" are used interchangeably and include human and non-human animal subjects, as well as subjects with a formally diagnosed disorder, subjects without a formally recognized disorder, subjects receiving medical attention, subjects at risk for developing a disorder, and the like.

[0074]

[0095] The terms "treat" and "treatment" include therapeutic treatments, prophylactic treatments, and applications that reduce the risk of a subject developing a disorder or other risk factors. Treatment does not require a complete cure of the disorder, but encompasses embodiments in which symptoms or underlying risk factors are alleviated. The term "prevent" does not require 100% elimination of the likelihood of an event. Rather, it indicates a reduced likelihood of the occurrence of an event in the presence of a compound or method.

[0075]

[0096] Standard techniques can be used for recombinant DNA, oligonucleotide synthesis, and tissue culture and transformation (e.g., electroporation, lipofection). Enzymatic reactions and purification techniques can be performed according to manufacturer's specifications or as commonly accomplished in the art or as described herein. The techniques and procedures described above can generally be carried out according to conventional methods well known in the art and as described in various general and more specific references cited and discussed throughout this specification. See, for example, Sambrook et al., Molecular Cloning: A Laboratory Manual (2d ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY (1989)), which is incorporated herein by reference for any purpose.

[0076]

[0097] As used herein, the term "substantially" or "essentially" refers to an amount, level, value, number, frequency, percentage, dimension, size, amount, weight or length that is about 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% higher than a reference amount, level, value, number, frequency, percentage, dimension, size, amount, weight or length. In one embodiment, the term "essentially the same" or "substantially the same" refers to about the same amount, level, value, number, frequency, percentage, dimension, size, amount, weight or length range as a reference amount, level, value, number, frequency, percentage, dimension, size, amount, weight or length.

[0077]

[0098] As used herein, the terms "substantially free" and "essentially free" are used interchangeably and, when used to describe a composition such as a cell population or culture medium, refer to a composition that is free of a particular substance, e.g., 95% free, 96% free, 97% free, 98% free, 99% free, or undetectable as measured by conventional means. A similar meaning can be applied to the term "absence," which refers to the absence of a particular substance or component of a composition.

[0078]

[0099] As used herein, the term "discernible" refers to an amount, level, value, number, frequency, percentage, dimension, size, amount, weight or length range, or an event that is easily detectable by one or more standard methods. The terms "non-discernible" and "non-discernible" and equivalents refer to an amount, level, value, number, frequency, percentage, dimension, size, amount, weight or length range, or an event that is not easily detectable or undetectable by standard methods. In one embodiment, an event is non-discernible if it occurs at a frequency of 5%, 4%, 3%, 2%, 1%, 0.1%, 0.001%, or less.

[0079]

[0100] Throughout this specification, unless the context requires otherwise, the words "comprise", "comprises" and "comprising" are understood to mean the inclusion of a stated step or element or group of steps or elements but not to the exclusion of any other step or element or group of steps or elements. In certain embodiments, the terms "include", "has", "contains" and "comprise" are used interchangeably.

[0080]

[0101] As used herein, "consisting of" means including and limited to what follows the phrase "consisting of." Thus, the phrase "consisting of" indicates that the listed elements are required or mandatory, and that other elements may not be present.

[0081]

[0102] "Consisting essentially of" means the inclusion of any elements listed after the phrase, limited to other elements that do not interfere with or contribute to the activity or function specified in this disclosure for the listed elements. Thus, the phrase "consisting essentially of" indicates that the listed elements are required or essential, but other elements are not optional and may or may not be present depending on whether they affect the activity or function of the listed elements.

[0082]

[0103] Throughout this specification, reference to "one embodiment," "an embodiment," "a particular embodiment," "a related embodiment," "a particular embodiment," "an additional embodiment," or "a further embodiment," or combinations thereof, means that the particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of such phrases in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0083]

[0104] As used herein, the term "about" or "approximately" refers to an amount, level, value, number, frequency, percentage, dimension, size, amount, weight, or length that varies by 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1% from a reference amount, level, value, number, frequency, percentage, dimension, size, amount, weight, or length. In certain embodiments, the term "about" or "approximately" when preceding a numerical value indicates a value within a range of 15%, 10%, 5%, or 1%, or any intervening range therein.

[0084] High-throughput screening methods for optimizing the production of lipid nanoparticles

[0105] To address the need for screening and optimization of lipid-based nanomedicines, the present disclosure provides a high-throughput screening (HTS) workflow for the preparation of lipid nanoparticles and for the characterization of their size distribution and payload encapsulation.

[0085]

[0106] In various embodiments, the present disclosure relates to a high-throughput screening method for optimizing the production of lipid nanoparticles (LNPs). In various embodiments, the method disclosed herein utilizes a high-throughput screening (HTS) screening workflow that includes (i) a robotic liquid handler, (ii) at least one device that can measure desired LNP properties, and (iii) at least one microplate that includes a plurality of microwells. In various embodiments, LNPs are formed by the above HTS screening workflow using a solvent injection method. See, for example, Gentine et al., 2012, J Liposome Res. 22, 18-30; Schubert and Muller-Goymann, 2003, Eur. J. Pharm. Biopharm. 55, 125-131.

[0086]

[0107] In various embodiments, the HTS workflow includes an instrument capable of measuring desired LNP properties. Such properties include encapsulation efficiency, average particle size, and particle size distribution. Physical stability can also be determined by measuring particle size and payload release at different time points after storage. Such analytical techniques are known in the art and include scanning / transmission electron microscopy (SEM / TEM), atomic force microscopy (AFM), analytical ultracentrifugation (AUC), dynamic light scattering (DLS), ultraviolet (UV) spectroscopy, and flow field fractionation (FFF). In various embodiments, the HTS workflow includes an instrument capable of DLS, UV-Vis, or fluorescence spectroscopy. In various embodiments, the methods disclosed herein utilize a high-throughput screening (HTS) screening workflow that includes (i) a robotic liquid handler, (ii) an instrument capable of performing DLS, (iii) an instrument capable of UV-Vis or fluorescence spectroscopy on samples, and (iv) at least one microplate containing a plurality of microwells.

[0087]

[0108] In various embodiments, the HTS workflow provides a method for optimizing LNP production using a solvent injection system. As used herein, "solvent injection system" refers to the rapid injection of a first solution containing lipid-containing self-assembling molecules into a second solution. In various embodiments, the solutions are mixable or miscible. In various embodiments, the first solution is a water-miscible solvent. In various embodiments, at least one solution is an organic phase solvent. Acetone, ethanol, isopropanol, and methanol are all suitable solvents for LNP preparation. In various embodiments, the first solution is an alcohol. In various embodiments, the first solution is ethanol. In various embodiments, the first solution is methanol.

[0088]

[0109] In various embodiments, the payload encapsulated by the LNP is dissolved in the second solution. In various embodiments, the payload encapsulated by the LNP is dissolved in the first solution. In various embodiments, the payload is encapsulated by a third water-miscible solvent.

[0089]

[0110] In various embodiments, at least two of the solutions are different phases. In various embodiments, there are three solutions that are injected into one another. In various embodiments, there are at least four solutions that are injected into one another. In various embodiments, there is at least one organic phase and at least one aqueous phase. In various embodiments, one of the solutions comprises an aqueous solvent, hi various embodiments, the aqueous solvent is an aqueous buffer.

[0090]

[0111] The injection of one solution into the other is controlled by a robotic liquid handler. As used herein, the term "robotic liquid handler" refers to a device that can automatically pipette, transfer, and mix liquids in parallel to multiple wells, microwells, or other liquid reservoirs. In various embodiments, the robotic liquid handler can deliver liquids of different compositions or amounts to different wells, microwells, or liquid reservoirs in parallel. In various embodiments, the robotic liquid handler can pipette, transfer, and mix liquids in parallel to different wells, microwells, or liquid reservoirs at different speeds or durations.

[0091]

[0112] In various embodiments, after injecting one solution into the second solution, the robotic liquid handler repeatedly picks up and re-injects the solution, thereby mixing at least two solutions. In various embodiments, the speed and duration of this injection and / or mixing is varied to determine optimal parameters for LNP formation. In various embodiments, the speed of injection and / or mixing varies from 0.1 ml / s to 0.9 ml / s. In various embodiments, the initial injection rate (i.e., the first injection of liquid) is performed at a rate of 0.1 ml / s to 0.9 ml / s. See FIG. 1. In various embodiments, subsequent injections / mixing are performed for 1 to 10 seconds (10x mixing at 0.1 ml / s to 0.9 ml / s).

[0092]

[0113] In various embodiments, LNP formation is completed in at least one microplate. In various embodiments, the microplate is composed of multiple microwells, and the formation conditions (e.g., lipid species, lipid composition, total lipid concentration, payload, payload loading ratio, phase species) vary between microwells. The microplate can be of any size and can contain any number of microwells. In various embodiments, the microplate contains 4, 6, 8, 12, 24, 48, 96, 384, 1536 microwells.

[0093]

[0114] One advantage of the HTS method provided herein is that LNP formation can occur rapidly in small volumes of solution. The method disclosed herein reduces material consumption by 10-fold and improves processing output by 100-fold (see FIG. 11). LNP formation in microwells uses significantly less material than LNPs formed using, for example, microfluidic-based preparations. In various embodiments, the microwells have a volume of about 10 μL, about 20 μL, about 30 μL, about 40 μL, about 50 μL, about 60 μL, about 70 μL, about 80 μL, about 90 μL, about 100 μL, about 125 μL, about 150 μL, about 175 μL, about 200 μL, about 250 μL, about 350 μL, about 360 μL, about 400 μL, about 500 μL, about 1000 μL, about 2000 μL, about 3000 μL, or about 4000 μL.

[0094] Lipid Nanoparticles (LNPs)

[0115] Provided herein are optimized lipid nanoparticles and methods for optimizing the production of these lipid nanoparticles "LNPs." As used herein, the term "lipid nanoparticle" or "LNP" refers to a composition comprising (i) a plurality of self-assembling molecules, the self-assembling molecules comprising a lipid component, and (ii) a payload. The LNPs optimized for production using the present invention can be used for any purpose. In various embodiments, the optimized LNPs can be used to deliver a vaccine. In various embodiments, the optimized LNPs can be used to deliver a drug to a patient in need thereof. The LNPs can carry any payload, including, but not limited to, nucleic acids, peptides, proteins, and small molecules. Furthermore, the LNPs can consist of only lipids (e.g., liposomes) or can include other components, such as polymers or proteins capable of self-assembly.

[0095]

[0116] In various embodiments, the LNP is an optimized LNP produced using the above techniques. In various embodiments, the optimized LNP comprises the steps of: (i) obtaining a first solution comprising an aqueous phase; (ii) obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; (iii) dissolving at least one payload molecule in either the first solution or the second solution; (iv) preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; (v) mixing the first solution and the second solution to obtain lipid nanoparticles encapsulating the payload using the robotic handler under conditions suitable for LNP formation, wherein the following conditions are met: (vi) mixing the first solution and the second solution to obtain lipid nanoparticles, wherein at least one of the type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, selection of phase, buffer type and pH, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration is varied among different wells; (vi) measuring at least one of encapsulation efficiency, particle size distribution, purification and particle recovery, and formulation stability of the LNPs; (vii) determining optimal parameters for producing the LNP preparation; and (viii) producing the LNP preparation based on the optimal parameters.

[0096]

[0117] In various embodiments, the present invention relates to a method for producing LNPs using a high throughput method, comprising the steps of: (i) obtaining a first solution comprising an aqueous phase; (ii) obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembly, wherein the first solution and the second solution are miscible; (iii) dissolving at least one payload molecule in either the first solution or the second solution; (iv) preparing and dispensing the phases having different compositions into a plurality of wells using a robotic liquid handler; and (v) mixing the first solution and the second solution to obtain lipid nanoparticles encapsulating the payload using the robotic handler under conditions suitable for LNP formation.

[0097] self-assembling molecules

[0118] As used herein, the term "self-assembling molecule" refers to any molecule capable of a defined arrangement without guidance or control from an external source. An optimized LNP may be composed of a single type of self-assembling molecule, or may be composed of multiple types of self-assembling molecules. In various embodiments, an optimized LNP comprises a lipid component having at least one type of lipid molecule. In various embodiments, an LNP may comprise polymer molecules and / or protein / peptide molecules. In various embodiments, the self-assembling molecules of an LNP may comprise only lipid molecules.

[0098]

[0119] The lipid component may comprise a single lipid species, or may comprise two or more lipid species.In various embodiments of the present invention, the relative composition of lipids in LNP preparations varies.In various embodiments, when considering the optimal parameters for the production of a given LNP formulation, different lipid species or combinations of different lipid species are evaluated.In various embodiments, at least one lipid molecule is PEGylated.In various embodiments, the lipid component may comprise phospholipids.

[0099]

[0120] In various embodiments, the LNP formulation may include one or more cationic or ionizable lipids. In some embodiments, the one or more cationic lipids are selected from the group consisting of cKK-E12, OF-02, C12-200, MC3, DLinDMA, DLinkC2DMA, ICE (imidazole-based), HGT5000, HGT5001, HGT4003, DODAC, DDAB, DMRIE, DOSPA, DOGS, DODAP, DODMA and DMDMA, DODAC, DLenDMA, DMRIE, CLinDMA, CpLinDMA, DMOBA, DOcarbDAP, DLinDAP, DLincarbDAP, DLinCDAP, KLin-K-DMA, DLin- K-XTC2-DMA, 3-(4-(bis(2-hydroxydodecyl)amino)butyl)-6-(4-((2-hydroxydodecyl)(2-hydroxyundecyl)amino)butyl)butyl)-1,4-dioxane-2,5-dione (Target 23), 3-(5-(bis(2-hydroxydodecyl)amino)pentan-2-yl)-6-(5-((2-hydroxydodecyl)(2-hydroxyundecyl)amino)pentan-2-yl)-1,4-dioxane-2,5-dione (Target 24), N1GL, N2GL, V1GL and combinations thereof.

[0100]

[0121] In some embodiments, the one or more cationic or ionizable lipids are amino lipids. In various embodiments, the amino lipids are primary, secondary, tertiary, quaternary amines, pyrrolidines or piperidines. Amino lipids suitable for use in the present invention include those described in WO2017180917, which is incorporated herein by reference. Exemplary amino lipids in WO2017180917 include those described in paragraph

[0744] , such as DLin-MC3-DMA (MC3), (13Z,16Z)-N,N-dimethyl-3-nonyldocosa-13,16-dien-1-amine (L608) and compound 18. Other amino lipids include compound 2, compound 23, compound 27, compound 10 and compound 20. Additional amino lipids suitable for use in the present invention include those described in WO2017112865, which is incorporated herein by reference. Exemplary amino lipids of WO2017112865 include compounds according to one of formulas (I), (Ial)-(Ia6), (lb), (II), (Ila), (III), (Ilia), (IV), (17-1), (19-1), (19-11), and (20-1), as well as the compounds of paragraphs

[0185] ,

[0201] , and

[0276] . In some embodiments, cationic lipids suitable for use in the present invention include those described in WO2016118725, which is incorporated herein by reference. Exemplary cationic lipids of WO2016118725 include KL22 and KL25, and the like. In some embodiments, cationic lipids suitable for use in the present invention include those described in WO2016118724, which is incorporated herein by reference. Exemplary cationic lipids in WO2016118725 include KL10, 1,2-dilinoleyloxy-N,N-dimethylaminopropane (DLin-DMA), and KL25.

[0101]

[0122] In some embodiments, the LNP formulation comprises one or more non-cationic lipids. In some embodiments, the one or more non-cationic lipids are selected from DSPC (1,2-distearoyl-sn-glycero-3-phosphocholine), DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine), DOPE (1,2-dioleyl-sn-glycero-3-phosphoethanolamine), DOPC (1,2-dioleyl-sn-glycero-3-phosphotidylcholine) DPPE (1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine), DMPE (1,2-dimyristoyl-sn-glycero-3-phosphoethanolamine), DOPG (1,2-dioleoyl-sn-glycero-3-phospho-(1'-rac-glycerol)).

[0102]

[0123] In some embodiments, the LNP formulation comprises one or more PEG-modified lipids. In some embodiments, the one or more PEG-modified lipids are C6-C 20 The PEG lipid comprises a poly(ethylene)glycol chain of up to 5 kDa length covalently attached to a lipid having a long alkyl chain. The PEG lipid can be selected from the non-limiting group consisting of PEG-modified phosphatidylethanolamine, PEG-modified phosphatidic acid, PEG-modified ceramide, PEG-modified dialkylamine, PEG-modified diacylglycerol, nad PEG-modified dialkylglycerol. For example, the PEG lipid can be a PEG-c-DOMG, PEG-DMG, PEG-DLPE, PEG-DMPE, PEG-DPPC or PEG-DSPE lipid.

[0103]

[0124] In various embodiments, the percentage of PEGylated lipids in the LNP (i.e., PEG density) varies. Polyethylene glycol (PEG) density in the LNP has been found to affect particle size, surface charge, and stability. In various embodiments, the PEG density varies between about 0.1% and about 10%. In various embodiments, the PEG density varies between about 0.2% and about 9%. In various embodiments, the PEG density varies between about 0.3% and about 8%. In various embodiments, the PEG density varies between about 0.4% and about 7%. In various embodiments, the PEG density varies between about 0.5% and about 6%. In various embodiments, the PEG density varies between about 0.5% and about 5%.

[0104]

[0125] In various embodiments, the total concentration of lipid components present in the solution for preparing LNP is varied to achieve the optimal properties of any given LNP.In various embodiments, the total concentration of lipid is varied between about 0.1 mM and about 8 mM.In various embodiments, the total concentration of lipid is varied between about 0.2 mM and about 7 mM.In various embodiments, the total concentration of lipid is varied between about 0.3 mM and about 6 mM.In various embodiments, the total concentration of lipid is varied between about 0.4 mM and about 4 mM.In various embodiments, the total concentration of lipid is varied between about 0.5 mM and about 3 mM.

[0105]

[0126] In various embodiments, the LNPs comprise more than one type of lipid. In various embodiments, the LNPs comprise at least two types of lipid. In various embodiments, the LNPs comprise at least three types of lipid. In various embodiments, the LNPs comprise at least four types of lipid. In various embodiments, the LNPs comprise at least five types of lipid. In various embodiments, the LNPs comprise at least six types of lipid. In various embodiments, the LNPs comprise at least seven types of lipid.

[0106]

[0127] The lipid component of the nanoparticle composition may include one or more structured lipids. The nanoparticle composition of the present invention may include a structured lipid (e.g., cholesterol, fecosterol, sitosterol, campesterol, stigmasterol, brassicasterol, ergosterol, tomatidine, tomatine, ursolic acid, or alpha-tocopherol).

[0107]

[0128] The lipid component of the nanoparticle composition may comprise one or more phospholipids, such as one or more (poly)unsaturated lipids. Generally, such lipids may comprise a phospholipid moiety and one or more fatty acid moieties.

[0108]

[0129] The phospholipid moiety may be selected from the non-limiting group consisting of phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylserine, phosphatidic acid, 2-lysophosphatidylcholine and sphingomyelin. The fatty acid moiety may be selected from the non-limiting group consisting of lauric acid, myristic acid, myristoleic acid, palmitic acid, palmitoleic acid, stearic acid, oleic acid, linoleic acid, alpha-linolenic acid, erucic acid, phytanic acid, arachidic acid, arachidonic acid, eicosapentaenoic acid, behenic acid, docosapentaenoic acid and docosahexaenoic acid. Non-natural species are also contemplated, including naturally occurring species with modifications and substitutions including branching, oxidation, cyclization and alkynes.

[0109]

[0130] In some embodiments, the nanoparticle composition may include 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), or both DSPC and DOPE. Phospholipids useful in the compositions and methods of the invention include DSPC, DOPE, 1,2-dilinoleoyl-sn-glycero-3-phosphocholine (DLPC), 1,2-dimyristoyl-sn-glycero-phosphocholine (DMPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), 1,2-diundecanoyl-sn-glycero-3-phosphocholine (DPPC), 1,2-diuretoyl-sn-glycero-3-phosphocholine (DMPC), 1,2-diuretoyl-sn-glycero-3-phosphocholine (DOPC), 1,2-diuretoyl-sn-glycero-3-phosphocholine (DP ... -glycero-phosphocholine (DUPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1,2-di-O-octadecenyl-sn-glycero-3-phosphocholine (18:0 diether PC), 1-oleoyl-2-cholesterylhemisuccinoyl-sn-glycero-3-phosphocholine (OChemsPC), 1-hexadecyl-sn-glycero-3-phosphocholine (C16 Lyso PC), 1,2-dilinolenoyl-sn-glycero-3-phosphocholine, 1,2-diarachidonoyl-sn-glycero-3-phosphocholine, 1,2-didocosahexaenoyl-sn-glycero-3-phosphocholine, 1,2-diphytanoyl-sn-glycero-3-phosphoethanolamine (ME 16.0 PE), 1,2-distearoyl-sn-glycero-3-phosphoethanolamine, 1,2-dilinolenoyl-sn-glycero-3-phosphoethanolamine, 1,2-dilinolenoyl-sn-glycero-3-phosphoethanolamine, 1,2-diarachidonoyl-sn-glycero-3-phosphoethanolamine, 1,2-didocosahexaenoyl-sn-glycero-3-phosphoethanolamine, 1,2-dioleoyl-sn-glycero-3-phospho-rac-(1-glycerol) sodium salt (DOPG), and sphingomyelin.

[0110]

[0131] The LNP composition may include one or more components in addition to those described in the previous section. For example, the nanoparticle composition may include one or more hydrophobic small molecules, such as a vitamin (e.g., vitamin A or vitamin E) or a sterol.

[0111]

[0132] The LNP compositions may also include one or more permeability enhancing molecules, carbohydrates, polymers, therapeutic agents, surface modifiers, or other components. Permeability enhancing molecules may be, for example, molecules described in U.S. Patent Application Publication No. 2005 / 0222064. Carbohydrates may include monosaccharides (e.g., glucose) and polysaccharides (e.g., glycogen and its derivatives and analogs).

[0112]

[0133] A polymer may be included in the LNP composition and / or used to encapsulate or partially encapsulate the LNP composition. The polymer may be biodegradable and / or biocompatible. The polymer may be selected from, but is not limited to, polyamines, polyethers, polyamides, polyesters, polycarbamates, polyureas, polycarbonates, polystyrenes, polyimides, polysulfones, polyurethanes, polyacetylenes, polyethylenes, polyethyleneimines, polyisocyanates, polyacrylates, polymethacrylates, polyacrylonitriles, and polyarylates. For example, polymers include poly(caprolactone) (PCL), ethylene vinyl acetate polymer (EVA), poly(lactic acid) (PLA), poly(L-lactic acid) (PLLA), poly(glycolic acid) (PGA), poly(lactic-co-glycolic acid) (PLGA), poly(L-lactic-co-glycolic acid) (PLLGA), poly(D,L-lactide) (PDLA), poly(L-lactide) (PLLA), poly(D,L-lactide-co-caprolactone), poly(D,L-lactide-co-caprolactone-co-glycolide), poly(D,L-lactide-co-PEO-co-D,L-lact ...L-lactide), polyalkylcyanoacrylates, polyurethanes, poly-L-lysine (PLL), hydroxypropyl methacrylate (HPMA), polyethylene glycol, poly-L-glutamic acid, poly(hydroxy acids), polyanhydrides, polyorthoesters, poly(ester amides), polyamides, poly(ester ethers), polycarbonates, polyalkylenes such as polyethylene and polypropylene, polyalkylene glycols such as poly(ethylene glycol) (EVA), polyalkylene oxides (PEO), polyalkylene terephthalates such as poly(ethylene terephthalate), polyvinyl alcohol (PVA), polyvinyl ethers, poly(vinyl acetate), polyvinyl halides such as poly(vinyl chloride) (PVC), polyvinylpyrrolidone, polysiloxanes, polystyrene (PS), polyurethanes, derivatized celluloses such as alkyl celluloses, hydroxyalkyl celluloses, cellulose ethers, cellulose esters, Nitrocellulose, hydroxypropylcellulose, carboxymethylcellulose, polymers of acrylic acid such as poly(methyl(meth)acrylate) (PMMA), poly(ethyl(meth)acrylate), poly(butyl(meth)acrylate), poly(isobutyl(meth)acrylate), poly(hexyl(meth)acrylate), poly(isodecyl(meth)acrylate), poly(lauryl(meth)acrylate), poly(phenyl(meth)acrylate), poly(methylacrylate), Poly(isopropyl acrylate), poly(isobutyl acrylate), poly(octadecyl acrylate) and their copolymers and mixtures, polydioxanone and its copolymers, polyhydroxyalkanoates, polypropylene fumarates, polyoxymethylenes, poloxamers, polyoxamines, poly(ortho)esters, poly(butyric acid), poly(valeric acid), poly(lactide-co-caprolactone) and trimethylene carbonate, polyvinylpyrrolidone may be mentioned.

[0113]

[0134] Therapeutic agents may include, but are not limited to, cytotoxic agents, chemotherapeutic agents, and other therapeutic agents. Cytotoxic agents may include, for example, taxol, cytochalasin B, gramicidin D, ethidium bromide, emetine, mitomycin, etoposide, teniposide, vincristine, vinblastine, colchicine, doxorubicin, daunorubicin, dihydroxyanthracin dione, mitoxantrone, mithramycin, actinomycin D, 1-dehydrotestosterone, glucocorticoids, procaine, tetracaine, lidocaine, propranolol, puromycin, maytansinoids, rachemicin, and analogs thereof. Radioactive ions may also be used as therapeutic agents, and may include, for example, radioactive iodine, strontium, phosphorus, palladium, cesium, iridium, cobalt, yttrium, samarium, and praseodymium. Other therapeutic agents may include, for example, antimetabolites (e.g., methotrexate, 6-mercaptopurine, 6-thioguanine, cytarabine, and 5-fluorouracil, and decarbazine), alkylating agents (e.g., mechlorethamine, thiotepa, chlorambucil, rachemycin, melphalan, carmustine, lomustine, cyclophosphamide, busulfan, dibromomannitol, streptozotocin, mitomycin C, and cis-dichlorodiamineplatinum(II) (DDP), and cisplatin), anthracyclines (e.g., daunorubicin and doxorubicin), antibiotics (e.g., dactinomycin, bleomycin, mithramycin, and anthramycin), and antimitotic agents (e.g., vincristine, vinblastine, taxol, and maytansinoids).

[0114]

[0135] Surface modifiers may include, but are not limited to, anionic proteins (e.g., bovine serum albumin), surfactants (e.g., cationic surfactants such as dimethyldioctadecylammonium bromide), sugars or sugar derivatives (e.g., cyclodextrins), nucleic acids, polymers (e.g., heparin, polyethylene glycol, and poloxamers), mucolytic agents (e.g., acetylcysteine, artemisia, bromelain, papain, clerodendrum, bromhexine, carbocysteine, eprazinone, mesna, ambroxol, sobrerol, domidol, lethostin, stepronin, tiopronin, gelsolin, thymosin 134, dornase alpha, neltenexin, and erdosteine), and DNases (e.g., rhDNase). Surface modifiers may be disposed (e.g., by coating, adsorption, covalent attachment, or other process) within the LNP and / or on the surface of the LNP composition.

[0115]

[0136] In addition to these components, the LNP compositions of the present invention may include any material useful in pharmaceutical compositions. For example, the LNP compositions may include one or more pharma- ceutically acceptable additives or auxiliary ingredients, such as, but not limited to, one or more solvents, dispersion media, diluents, dispersing aids, suspension aids, granulation aids, disintegrants, fillers, glidants, liquid vehicles, binders, surfactants, isotonicity agents, thickening or emulsifying agents, buffers, lubricants, oils, preservatives, and other species. Additives such as waxes, butters, colorants, coating agents, flavors, and fragrances may also be included. Pharmaceutically acceptable additives are well known in the art (e.g., Remington's The Science and Practice of Pharmacy, 21st Edition, AR Gennaro; Lippincott, Williams & Wilkins, Baltimore, Md., 2006).

[0116]

[0137] Examples of diluents may include, but are not limited to, calcium carbonate, sodium carbonate, calcium phosphate, dicalcium phosphate, calcium sulfate, calcium hydrogen phosphate, sodium phosphate, lactose, sucrose, cellulose, microcrystalline cellulose, kaolin, mannitol, sorbitol, inositol, sodium chloride, dry starch, corn starch, powdered sugar, and / or combinations thereof. The granulating and dispersing agents may be selected from the non-limiting list consisting of potato starch, corn starch, tapioca starch, sodium starch glycolate, clay, alginic acid, guar gum, citrus pulp, agar, bentonite, cellulose and wood products, natural sponge, cation exchange resins, calcium carbonate, silicates, sodium carbonate, cross-linked poly(vinylpyrrolidone) (crospovidone), sodium carboxymethyl starch (sodium starch glycolate), carboxymethylcellulose, cross-linked sodium carboxymethylcellulose (croscarmellose), methylcellulose, pregelatinized starch (starch 1500), microcrystalline starch, water insoluble starch, calcium carboxymethylcellulose, magnesium aluminum silicate (VEEGUM®), sodium lauryl sulfate, quaternary ammonium compounds, and / or combinations thereof.

[0117]

[0138] Surfactants and / or emulsifiers include, but are not limited to, natural emulsifiers (e.g., acacia, agar, alginic acid, sodium alginate, tragacanth, chondrux, cholesterol, xanthan, pectin, gelatin, egg yolk, casein, wool fat, cholesterol, wax, and lecithin), colloidal clays (e.g., bentonite [aluminum silicate] and VEEGUM® [magnesium aluminum silicate]), long chain amino acid derivatives, high molecular weight alcohols (e.g., stearyl alcohol, cetyl alcohol, oleyl alcohol, triacetin monostearate, ethylene glycol distearate, glyceryl monostearate, and propylene glycol monostearate, polyvinyl alcohol), carbomers (e.g., carboxypolymethylene, polyacrylic acid, acrylic acid polymers, and carboxyvinyl polymers), carrageenan, cellulose derivatives (e.g., sodium carboxymethylcellulose, powdered cellulose, hydroxymethylcellulose, hydroxypropylcellulose, hydroxypropylmethylcellulose, methylcellulose, hydroxypropyl ... ), sorbitan fatty acid esters (e.g., polyoxyethylene sorbitan monolaurate [TWEEN® 20], polyoxyethylene sorbitan [TWEEN® 60], polyoxyethylene sorbitan monooleate [TWEEN® 80], sorbitan monopalmitate [SPAN® 40], sorbitan monostearate [SPAN® 60], sorbitan tristearate [SPAN® 65], glyceryl monooleate, sorbitan monooleate [SPAN® 80]) , polyoxyethylene esters (e.g., polyoxyethylene monostearate [MYRJ® 45], polyoxyethylene hydrogenated castor oil, polyethoxylated castor oil, polyoxymethylene stearate, and SOLUTOL®), sucrose fatty acid esters, polyethylene glycol fatty acid esters (e.g., CREMOPHOR®), polyoxyethylene ethers (e.g., polyoxyethylene lauryl ether [BRIJ® 30]), poly(vinylpyrrolidone), diethylene glycol monolaurate,Triethanolamine oleate, sodium oleate, potassium oleate, ethyl oleate, oleic acid, ethyl laurate, sodium lauryl sulfate, PLURONIC® F 68, POLOXAMER® 188, cetrimonium bromide, cetylpyridinium chloride, benzalkonium chloride, docusate sodium, and / or combinations thereof may be included.

[0118]

[0139] The binders may be starches (e.g., corn starch and starch paste); gelatin; sugars (e.g., sucrose, glucose, dextrose, dextrin, molasses, lactose, lactitol, mannitol); natural and synthetic gums (e.g., acacia, sodium alginate, extract of Irish moss, panwar gum, ghatti gum, mucilage of isapol husk, carboxymethylcellulose, methylcellulose, ethylcellulose, hydroxyethylcellulose, hydroxypropylcellulose, hydroxypropylmethylcellulose, microcrystalline cellulose, cellulose acetate, poly(vinyl-pyrrolidone), magnesium aluminum silicate (VEEGUM®), and oat gum arabic); alginates; polyethylene oxide; polyethylene glycol; inorganic calcium salts; silicic acid; polymethacrylates; waxes; water; alcohol; and combinations thereof, or any other suitable binders.

[0119]

[0140] Preservatives include, but are not limited to, antioxidants, chelating agents, antibacterial preservatives, antifungal preservatives, alcohol preservatives, acidic preservatives, and / or other preservatives. Antioxidants include, but are not limited to, alpha tocopherol, ascorbic acid, acorbyl palmitate, butylated hydroxyanisole, butylated hydroxytoluene, monothioglycerol, potassium metabisulfite, propionic acid, propyl gallate, sodium ascorbate, sodium bisulfite, sodium metabisulfite, and / or sodium sulfite. Chelating agents include ethylenediaminetetraacetic acid (EDTA), citric acid monohydrate, disodium edetate, dipotassium edetate, edetic acid, fumaric acid, malic acid, phosphoric acid, sodium edetate, tartaric acid, and / or trisodium edetate. Antibacterial preservatives include, but are not limited to, benzalkonium chloride, benzethonium chloride, benzyl alcohol, bronopol, cetrimide, cetylpyridinium chloride, chlorhexidine, chlorobutanol, chlorocresol, chloroxylenol, cresol, ethyl alcohol, glycerin, hexetidine, imidurea, phenol, phenoxyethanol, phenylethyl alcohol, phenylmercuric nitrate, propylene glycol, and / or thimerosal. Antifungal preservatives include, but are not limited to, butylparaben, methylparaben, ethylparaben, propylparaben, benzoic acid, hydroxybenzoic acid, potassium benzoate, potassium sorbate, sodium benzoate, sodium propionate, and / or sorbic acid. Examples of alcohol preservatives include, but are not limited to, ethanol, polyethylene glycol, phenol, benzyl alcohol, phenolic compounds, bisphenol, chlorobutanol, hydroxybenzoate, and / or phenylethyl alcohol. Examples of acidic preservatives include, but are not limited to, vitamin A, vitamin C, vitamin E, beta-carotene, citric acid, acetic acid, dehydroascorbic acid, ascorbic acid, sorbic acid, and / or phytic acid.Other preservatives include, but are not limited to, tocopherol, tocopheryl acetate, desulfoxime mesylate, cetrimide, butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), ethylenediamine, sodium lauryl sulfate (SLS), sodium lauryl ether sulfate (SLES), sodium bisulfite, sodium metabisulfite, potassium sulfite, potassium metabisulfite, GLYDANT PLUS®, PHENONIP®, methylparaben, GERMALL® 115, GERMABEN® II, NEOLONE®, KATHON®, and / or EUXYL®.

[0120]

[0141] Examples of buffers include citrate buffer, acetate buffer, phosphate buffer, ammonium chloride, calcium carbonate, calcium chloride, calcium citrate, calcium glubionate, calcium gluconate, calcium gluconate, d-gluconic acid, calcium glycerophosphate, calcium lactate, calcium lactobionate, propanoic acid, calcium levulinate, pentanoic acid, dibasic calcium phosphate, phosphoric acid, tribasic calcium phosphate, calcium hydroxide phosphate, potassium acetate, potassium chloride, potassium gluconate, potassium mixture, dibasic potassium phosphate, monobasic potassium phosphate, potassium phosphate mixture, sodium acetate, sodium bicarbonate, sodium chloride, sodium citrate, sodium lactate, dibasic sodium phosphate, monobasic sodium phosphate, sodium phosphate mixture, tromethamine, amino-sulfonic acid buffers (e.g., HEPES), magnesium hydroxide, aluminum hydroxide, alginic acid, pyrogen-free water, isotonic saline, Ringer's solution, ethyl alcohol, and / or combinations thereof. The lubricant may be selected from the non-limiting group consisting of magnesium stearate, calcium stearate, stearic acid, silica, talc, malt, glyceryl behenate, hydrogenated vegetable oils, polyethylene glycol, sodium benzoate, sodium acetate, sodium chloride, leucine, magnesium lauryl sulfate, sodium lauryl sulfate, and combinations thereof.

[0121]

[0142] Examples of oils include, but are not limited to, almond, apricot kernel, avocado, babassu, bergamot, black current seed, borage, cade, chamomile, canola, caraway, carnauba, castor, cinnamon, cocoa butter, coconut, cod liver, coffee, corn, cottonseed, emu, eucalyptus, evening primrose, fish, flaxseed, geraniol, gourd, grape seed, hazelnut, hyssop, isopropyl myristate, jojoba, kukui nut, lavandin, lavender, lemon, lily of the valley, macadamia nut, mallow, mango seed, meadowfoam seed, mink, nutmeg, olive, orange, orange roughy, palm, palm kernel, peach kernel, and peanut. , poppy seed, pumpkin seed, rapeseed, rice bran, rosemary, safflower, sandalwood, sasuna, savory, sea buckthorn, sesame, shea butter, silicone, soybean, sunflower, tea tree, thistle, camellia, vetiver, walnut, and wheat germ oils, as well as butyl stearate, caprylic triglyceride, capric triglyceride, cyclomethicone, diethyl sebacate, dimethicone 360, simethicone, isopropyl myristate, mineral oil, octyldodecanol, oleyl alcohol, silicone oil, and / or combinations thereof.

[0122]

[0143] In various embodiments, the LNPs can be liposomes. In various embodiments, the LNPs can be polymer-lipid nanoparticles. In various embodiments, the LNPs can include additional protein or peptide molecules.

[0123] payload

[0144] The LNPs of the present invention are manufactured to encapsulate a payload. The term "payload" refers to any chemical entity, pharmaceutical, drug (such drugs can be, but are not limited to, small molecules, inorganic solids, polymers, or biopolymers), small molecules, nucleic acids (e.g., DNA, RNA, siRNA, etc.), proteins, peptides, etc., that forms a complex with the lipid nanoparticle formulations described in this disclosure. Payloads also encompass candidates (e.g., candidates of unknown structure and / or function) for treating or preventing diseases, illnesses, disorders, or disorders of bodily functions, including, but not limited to, test compounds that are both known and potential therapeutic compounds. Test compounds can be determined to be therapeutic by screening using the screening methods of the present disclosure.

[0124]

[0145] In various embodiments, the payload consists of one or more nucleotides. For example, in various embodiments, the payload is an oligonucleotide. In various embodiments, such payload-encapsulated LNPs can be characterized by the N:P ratio. As used herein, "N / P ratio" refers to the ratio of positively charged polymeric amine (N=nitrogen) groups to negatively charged nucleic acid phosphate (P) groups. The N / P ratio plays an important role in intracellular payload delivery. In various embodiments, the N:P ratio of the payload varies. In various embodiments, the N:P ratio varies between about 0.5 and about 5. In various embodiments, the N:P ratio varies between about 0.25 and about 10. In various embodiments, the N:P ratio is about 0.1, about 0.2, about 0.25, about 0.5, about 1, about 1.5, about 2, about 2.5, about 3, about 3.5, about 4, about 4.5, about 5, about 6, about 7, about 8, about 9, or about 10.

[0125]

[0146] In various embodiments, the payload is an oligonucleotide. In various embodiments, the oligonucleotide is an antisense molecule. In various embodiments, the oligonucleotide is an siRNA. In various embodiments, the oligonucleotide is an shRNA. The oligonucleotide can be of various lengths. In various embodiments, the oligonucleotide is about 1, about 2, about 3, about 4, about 5, about 6, about 7, about 8, about 9, about 10, about 11, about 12, about 13, about 14, about 15, about 16, about 17, about 18, about 19, about 20, about 21, about 22, about 23, about 24, about 25, about 26, about 27, about 28, about 29, about 30, about 31, about 32, about 33, about 34, about 35, about 36, about 37, about 38, about 39 or about 40 nucleotides long. In various embodiments, the oligonucleotide is between about 2 and about 40 nucleotides long. In various embodiments, the oligonucleotide is between about 4 and about 35 nucleotides long. In various embodiments, the oligonucleotides are between about 10 and about 30 nucleotides in length. In various embodiments, the oligonucleotides are between about 12 and about 17 nucleotides in length.

[0126]

[0147] In various embodiments, the payload is an mRNA. In various embodiments, the mRNA is about 500-3000 nucleotides in length. In various embodiments, the mRNA is 500 nucleotides, 1000 nucleotides, 1500 nucleotides, 2000 nucleotides, 2500 nucleotides, 3000 nucleotides in length. In various embodiments, the mRNA encodes an antigenic peptide. In various embodiments, the mRNA is part of a vaccine.

[0127]

[0148] In various embodiments, the payload is a polypeptide. In various embodiments, the polypeptide is between about 1,000 Da and 10,000 Da. In various embodiments, the polypeptide is about 500 Da, about 600 Da, about 700 Da, about 800 Da, about 900 Da, about 1,000 Da, about 1,500 Da, about 2,000 Da, about 2,500 Da, about 3,000 Da, about 3,500 Da, about 4,000 Da, about 4,500 Da, about 5,000 Da, about 5,500 Da, about 6,000 Da, about 6,500 Da, about 7,000 Da, about 7,500 Da, about 8,000 Da, about 8,500 Da, about 9,000 Da, about 9,500 Da, about 10,000 Da, about 15,000 Da or about 20,000 Da.

[0128]

[0149] In various embodiments, the payload is a small molecule. In various embodiments, the small molecule is between about 100 Da and 1000 Da. In various embodiments, the small molecule is about 50 Da, about 60 Da, about 70 Da, about 80 Da, about 90 Da, about 100 Da, about 150 Da, about 200 Da, about 250 Da, about 300 Da, about 350 Da, about 400 Da, about 450 Da, about 500 Da, about 550 Da, about 600 Da, about 650 Da, about 700 Da, about 750 Da, about 800 Da, about 850 Da, about 900 Da, about 950 Da, about 1,000 Da, about 1,500 Da, or about 2,000 Da.

[0129] Pharmaceutical Preparations

[0150] In various embodiments, the optimized lipid nanoparticles may be formulated in whole or in part as a pharmaceutical preparation. The pharmaceutical preparation of the present invention may include one or more nanoparticle compositions. For example, the pharmaceutical composition may include one or more nanoparticle compositions that include one or more different payloads. The pharmaceutical composition of the present invention may further include one or more pharma- ceutically acceptable additives or auxiliary components, such as those described herein. General guidelines for the formulation and manufacture of pharmaceutical compositions and medicaments are available, for example, in Remington's The Science and Practice of Pharmacy, 21st Edition, AR Gennaro; Lippincott, Williams & Wilkins, Baltimore, Md., 2006. Conventional additives and auxiliary components may be used in any pharmaceutical composition of the present invention, except to the extent that any conventional additive or auxiliary component may be incompatible with one or more components of the nanoparticle composition of the present invention. An additive or auxiliary component may be incompatible with a component of the nanoparticle composition if combination with that component may result in any undesirable biological effect or other adverse effect.

[0130]

[0151] In some embodiments, one or more additives or auxiliary ingredients may comprise more than 50% of the total mass or volume of the pharmaceutical composition comprising the nanoparticle composition of the present invention. For example, one or more additives or auxiliary ingredients may comprise 50%, 60%, 70%, 80%, 90% or more of pharmaceutical practice. In some embodiments, a pharma-ceutically acceptable additive is at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% pure. In some embodiments, the additive is approved for human use and veterinary use. In some embodiments, the additive is approved by the U.S. Food and Drug Administration. In some embodiments, the additive is pharmaceutical grade. In some embodiments, the additive meets the standards of the United States Pharmacopoeia (USP), the European Pharmacopoeia (EP), the British Pharmacopoeia and / or the International Pharmacopoeia.

[0131]

[0152] The relative amounts of one or more nanoparticle compositions, one or more pharma- ceutically acceptable additives, and / or any additional components in a pharmaceutical composition according to the present disclosure will vary depending on the identity, size, and / or condition of the subject being treated, as well as the route by which the composition is administered. By way of example, a pharmaceutical composition may contain between 0.1% and 100% (wt / wt) of one or more nanoparticle compositions.

[0132]

[0153] Nanoparticle compositions and / or pharmaceutical compositions comprising one or more nanoparticle compositions may be administered to any patient or subject, including those who may benefit from a therapeutic effect provided by delivery of mRNA to one or more specific cells, tissues, organs, or systems or groups thereof, such as the renal system. Although the description of nanoparticle compositions and pharmaceutical compositions comprising nanoparticle compositions provided herein is primarily directed to compositions suitable for administration to humans, it will be understood by those skilled in the art that such compositions are generally suitable for administration to any other mammal. Modifications of compositions suitable for administration to humans to make them suitable for administration to various animals are well understood, and a veterinary pharmacologist of skill in the art can design and / or perform such modifications with no more than routine experimentation, if any. Subjects to which administration of the compositions is contemplated include, but are not limited to, humans, other primates, and other mammals, including commercially relevant mammals such as cows, pigs, horses, sheep, cats, dogs, mice, and / or rats.

[0133]

[0154] Pharmaceutical compositions containing one or more nanoparticle compositions may be prepared by any method known or hereafter developed in the art of pharmacology. In general, such methods of preparation include bringing the active ingredient into association with an excipient and / or one or more other accessory ingredients, and then dividing, shaping, and / or packaging the product into the desired single or multiple dosage units, as desired or necessary.

[0134]

[0155] Pharmaceutical compositions according to the present disclosure may be prepared, packaged, and / or sold in bulk, as single unit doses, and / or as a plurality of single unit doses. As used herein, a "unit dose" is a discrete amount of a pharmaceutical composition (e.g., a nanoparticle composition) that contains a predetermined amount of an active ingredient. The amount of the active ingredient is generally equal to the dosage of the active ingredient that would be administered to a subject and / or a convenient fraction of such a dosage, for example, one-half or one-third of such a dosage.

[0135]

[0156] The pharmaceutical composition of the present invention can be prepared in various forms suitable for various routes and methods of administration. For example, the pharmaceutical composition of the present invention can be prepared in liquid dosage forms (e.g., emulsions, microemulsions, nanoemulsions, solutions, suspensions, syrups, and elixirs), injectable dosage forms, solid dosage forms (e.g., capsules, tablets, pills, powders, and granules), dosage forms for topical and / or transdermal administration (e.g., ointments, pastes, creams, lotions, gels, powders, solutions, sprays, inhalants, and patches), suspensions, powders, and other forms.

[0136]

[0157] Liquid dosage forms for oral and parenteral administration include, but are not limited to, pharma- ceutically acceptable emulsions, microemulsions, nanoemulsions, solutions, suspensions, syrups, and / or elixirs. In addition to the active ingredient, liquid dosage forms may contain inert diluents commonly used in the art, such as water or other solvents, solubilizers and emulsifiers, such as ethyl alcohol, isopropyl alcohol, ethyl carbonate, ethyl acetate, benzyl alcohol, benzyl benzoate, propylene glycol, 1,3-butylene glycol, dimethylformamide, oils (especially cottonseed oil, peanut oil, corn oil, germ oil, olive oil, castor oil, and sesame oil), glycerol, tetrahydrofurfuryl alcohol, polyethylene glycol, and fatty acid esters of sorbitan, and mixtures thereof. In addition to inert diluents, oral compositions may contain adjuvants, such as wetting agents, emulsifying and suspending agents, sweeteners, flavoring agents, and / or perfuming agents. In certain embodiments for parenteral administration, the composition is mixed with a solubilizing agent such as Cremophor®, alcohols, oils, modified oils, glycols, polysorbates, cyclodextrins, polymers, and / or combinations thereof.

[0137]

[0158] Injectable preparations, for example, sterile injectable aqueous or oleaginous suspensions, can be formulated according to known techniques using suitable dispersants, wetting agents, and / or suspending agents. Sterile injectable preparations can be sterile injectable solutions, suspensions, and / or emulsions in non-toxic parenterally acceptable diluents and / or solvents, for example, solutions in 1,3-butanediol. Acceptable additives and solvents that can be used include water, Ringer's solution, USP, and isotonic sodium chloride solution. Sterile fixed oils are conventionally used as solvents or suspending media. For this purpose, any non-irritating fixed oil can be used, including synthetic monoglycerides or diglycerides. Fatty acids, such as oleic acid, can be used in the preparation of injectables.

[0138]

[0159] Injectable preparations can be sterilized, for example, by filtration through a bacterial-retaining filter and / or by incorporating sterilizing agents in the form of sterile solid compositions which can be dissolved or dispersed in sterile water or other sterile injectable medium prior to use.

[0139]

[0160] In order to prolong the effect of an active ingredient, it is often desirable to slow the absorption of the active ingredient from subcutaneous or intramuscular injection. This can be accomplished by using a liquid suspension of crystalline or amorphous material with poor water solubility. The rate of absorption of the drug then depends on the dissolution rate of the drug, which in turn may depend on the crystal size and crystalline form. Alternatively, delayed absorption of a parenterally administered drug form is accomplished by dissolving or suspending the drug in an oil vehicle. Injectable depot forms are produced by forming microencapsulated matrices of the drug in biodegradable polymers such as polylactide-polyglycolide. Depending on the ratio of drug to polymer and the nature of the specific polymer used, the rate of drug release can be controlled. Examples of other biodegradable polymers include poly(orthoesters) and poly(anhydrides). Depot injectable formulations are prepared by entrapping the drug in liposomes or microemulsions that are compatible with body tissues.

[0140]

[0161] Compositions for rectal or vaginal administration are typically prepared by mixing the composition with a suitable non-irritating excipient, such as cocoa butter, polyethylene glycol or a suppository wax, which is solid at ambient temperature but liquid at body temperature and therefore will melt in the rectum or vagina and release the active ingredient.

[0141]

[0162] Solid dosage forms for oral administration include capsules, tablets, pills, films, powders, and granules. In such solid dosage forms, the active ingredient is mixed with at least one inert pharma- ceutically acceptable excipient such as sodium citrate or dicalcium phosphate and / or fillers or extenders (e.g., starches, lactose, sucrose, glucose, mannitol, and silicic acid), binders (e.g., carboxymethylcellulose, alginates, gelatin, polyvinylpyrrolidinone, sucrose, and acacia), humectants (e.g., glycerol), disintegrating agents (e.g., agar-agar, calcium carbonate, potato or tapioca starch, alginic acid, certain silicates, and sodium carbonate), solution retarders (e.g., paraffin), absorption accelerators (e.g., quaternary ammonium compounds), wetting agents (e.g., cetyl alcohol and glycerol monostearate), absorbents (e.g., kaolin and bentonite clays, silicates), and lubricants (e.g., talc, calcium stearate, magnesium stearate, solid polyethylene glycols, sodium lauryl sulfate), and mixtures thereof. In the case of capsules, tablets and pills, the dosage forms may also comprise buffering agents.

[0142]

[0163] Similar types of solid compositions can be used as fillers in soft and hard gelatin capsules using additives such as lactose or milk sugar, and high molecular weight polyethylene glycols. Tablets, dragees, capsules, pills, and granules solid dosage forms can be prepared with coatings and shells, such as enteric coatings and other coatings known in the pharmaceutical formulation art. They can also optionally contain opacifying agents and be of a composition that they release one or more active ingredients only, or preferentially, in a certain part of the intestinal tract, optionally in a delayed manner. Examples of embedding compositions that can be used include polymeric substances and waxes. Similar types of solid compositions can be used as fillers in soft and hard gelatin capsules using additives such as lactose or milk sugar, and high molecular weight polyethylene glycols.

[0143]

[0164] Dosage forms for topical and / or transdermal administration of the composition may include ointments, pastes, creams, lotions, gels, powders, solutions, sprays, inhalants and / or patches. In general, the active ingredient is mixed under sterile conditions with pharma- ceutically acceptable additives and / or any necessary preservatives and / or buffers as needed. In addition, the present disclosure contemplates the use of transdermal patches, which often have the added advantage of providing controlled delivery of the compound to the body. Such dosage forms may be prepared, for example, by dissolving and / or dispensing the compound in a suitable medium. Alternatively or additionally, the rate may be controlled by providing a rate-controlling membrane and / or dispersing the compound in a polymer matrix and / or gel.

[0144]

[0165] Suitable devices for use in delivering the intradermal pharmaceutical compositions described herein include short needle devices, such as those described in U.S. Pat. No. 4,886,499; U.S. Pat. No. 5,190,521; U.S. Pat. No. 5,328,483; U.S. Pat. No. 5,527,288; U.S. Pat. No. 4,270,537; U.S. Pat. No. 5,015,235; U.S. Pat. No. 5,141,496; and U.S. Pat. No. 5,417,662. The intradermal composition can be administered by a device that limits the effective penetration length of the needle into the skin, such as those described in WO 99 / 34850 and its functional equivalents. Jet injection devices that deliver liquid compositions to the dermis via a liquid jet injector and / or via a needle that pierces the stratum corneum and creates a jet that reaches the dermis. Jet injection devices are described, for example, in U.S. Pat. Nos. 5,480,381; 5,599,302; 5,334,144; 5,993,412; 5,649,912; 5,569,189; 5,704,911; 5,383,851; 5,893,397; 5,466,220; and 5,466,221. ,339,163; U.S. Pat. No. 5,312,335; U.S. Pat. No. 5,503,627; U.S. Pat. No. 5,064,413; U.S. Pat. No. 5,520,639; U.S. Pat. No. 4,596,556; U.S. Pat. No. 4,790,824; U.S. Pat. No. 4,941,880; U.S. Pat. No. 4,940,460; and WO 97 / 37705 and WO 97 / 13537. Ballistic powder / particle delivery devices that use compressed gas to accelerate the vaccine in powder form through the outer layer of the skin to the dermis are suitable. Alternatively or additionally, a conventional syringe may be used in the classical Mantoux method of intradermal administration.

[0145]

[0166] Formulations suitable for topical administration include, but are not limited to, liquid and / or semi-liquid formulations, such as liniments, lotions, oil-in-water and / or water-in-oil emulsions, such as creams, ointments and / or pastes, and / or solutions and / or suspensions. Topically administrable formulations may contain, for example, about 1% to about 10% (wt / wt) of active ingredient, although the concentration of the active ingredient may be as high as the solubility limit of the active ingredient in the solvent. Formulations for topical administration may further include one or more additional ingredients described herein.

[0146]

[0167] Pharmaceutical compositions may be prepared, packaged, and / or sold in a formulation suitable for pulmonary administration via the buccal cavity. Such formulations may comprise dry particles comprising the active ingredient and having a diameter in the range of about 0.5 nm to about 7 nm or about 1 nm to about 6 nm. Such compositions are conveniently in the form of a dry powder for administration using a device comprising a dry powder reservoir into which a stream of propellant can be directed to disperse the powder, and / or using a self-propelling solvent / powder dispensing container, such as a device comprising the active ingredient dissolved and / or suspended in a low boiling propellant in a sealed container. Such powders comprise particles in which at least 98% of the particles (by weight) have a diameter greater than 0.5 nm and at least 95% of the particles (by number) have a diameter less than 7 nm. Alternatively, at least 95% of the particles (by weight) have a diameter greater than 1 nm and at least 90% of the particles (by number) have a diameter less than 6 nm. Dry powder compositions may comprise a solid fine powder diluent, such as sugar, and are conveniently provided in a unit dose form.

[0147]

[0168] Low boiling propellants generally include liquid propellants having a boiling point below 65° F. at atmospheric pressure. Generally, the propellant may comprise 50% to 99.9% (wt / wt) of the composition and the active ingredient may comprise 0.1% to 20% (wt / wt) of the composition. The propellant may further comprise additional ingredients such as liquid nonionic and / or solid anionic surfactants and / or solid diluents (which may have a particle size on the same order as the particles containing the active ingredient).

[0148]

[0169] Pharmaceutical compositions formulated for pulmonary delivery may provide the active ingredient in the form of droplets of a solution and / or suspension. Such formulations may be prepared, packaged, and / or sold as aqueous and / or dilute alcoholic solutions and / or suspensions (optionally sterile) containing the active ingredient, and may be conveniently administered using any nebulizer and / or atomizer device. Such formulations may further comprise one or more additional ingredients, including, but not limited to, flavoring agents such as sodium saccharin, volatile oils, buffers, surfactants, and / or preservatives such as methyl hydroxybenzoate. The droplets provided by this route of administration may have an average diameter in the range of about 1 nm to about 200 nm.

[0149]

[0170] The formulations described herein as being useful for pulmonary delivery are useful for intranasal delivery of pharmaceutical compositions. Another formulation suitable for intranasal administration is a coarse powder comprising the active ingredient and having an average particle size of about 0.2 μm to 500 μm. Such formulations are administered in the manner of a snuff dose, i.e., by rapid inhalation through the nasal passages from a container of the powder held close to the nose.

[0150]

[0171] Formulations suitable for nasal administration may contain, for example, as little as about 0.1% (wt / wt) to as much as 100% (wt / wt) of the active ingredient, and may include one or more additional ingredients described herein. Pharmaceutical compositions may be prepared, packaged, and / or sold in a formulation suitable for buccal administration. Such formulations may be, for example, in the form of tablets and / or lozenges manufactured using conventional methods, and may contain, for example, 0.1% to 20% (wt / wt) of the active ingredient, the remainder comprising an orally soluble and / or degradable composition, and optionally, one or more additional ingredients described herein. Alternatively, formulations suitable for buccal administration may comprise a powder and / or an aerosolized and / or atomized solution and / or suspension comprising the active ingredient. Such powdered, aerosolized, and / or aerosolized formulations, when dispersed, may have an average particle and / or droplet size in the range of about 0.1 nm to about 200 nm, and may further comprise one or more of any additional ingredients described herein.

[0151]

[0172] The pharmaceutical compositions may be prepared, packaged, and / or sold in a formulation suitable for ophthalmic administration. Such formulations may be in the form of, for example, eye drops comprising a 0.1 / 1.0% (wt / wt) solution and / or suspension of the active ingredient in an aqueous or oily liquid additive. Such drops may further comprise one or more of buffering agents, salts, and / or any of the additional ingredients described herein. Other ophthalmically administrable formulations that are useful include those comprising the active ingredient in microcrystalline form and / or in a liposomal preparation. Ear drops and / or eye drops are contemplated to be within the scope of the present disclosure.

[0152]

[0173] Nanoparticle compositions comprising one or more payloads may be administered by any route. In some embodiments, the compositions of the present invention, including preventive, diagnostic, or imaging compositions comprising one or more nanoparticle compositions of the present invention, are administered by one or more of a variety of routes, including oral, intravenous, intramuscular, intraarterial, intramedullary, intrathecal, subcutaneous, intracerebroventricular, transdermal or intradermal, interdermal, rectal, intravaginal, intraperitoneal, topical (e.g., powder, ointment, cream, gel, lotion, and / or drops), mucosal, nasal, buccal, enteral, intravitreal, intratumoral, sublingual, intranasal; by intratracheal instillation, bronchial instillation, and / or inhalation; as oral spray and / or powder, nasal spray and / or aerosol, and / or via a portal vein catheter. In some embodiments, the compositions may be administered intravenously, intramuscularly, intradermally, or subcutaneously. However, the present disclosure encompasses the delivery of the compositions of the present invention by any suitable route, taking into account possible advances in the science of drug delivery. Generally, the most appropriate administration route will depend on a variety of factors, including the properties of the nanoparticle composition comprising one or more mRNAs (e.g., its stability in various bodily environments, such as the bloodstream and digestive tract), the condition of the patient (e.g., whether the patient can tolerate a particular administration route), and the like.

[0153]

[0174] In certain embodiments, the compositions according to the present disclosure provide a therapeutically effective amount of 5 mg / kg to about 10 mg / kg, about 0.0001 mg / kg to about 10 mg / kg, about 0.001 mg / kg to about 10 mg / kg, about 0.005 mg / kg to about 10 mg / kg, about 0.01 mg / kg to about 10 mg / kg, about 0.1 mg / kg to about 10 mg / kg, about 1 mg / kg to about 10 mg / kg, about 2 mg / kg to about 10 mg / kg, about 5 mg / kg to about 10 mg / kg, about 0.0001 mg / kg to about 5 mg / kg, about 0.001 mg / kg to about 5 mg / kg, about 0.005 mg The nanoparticle compositions of the present invention may be administered at a dosage level sufficient to deliver about 0.005 mg / kg to about 5 mg / kg, about 0.01 mg / kg to about 5 mg / kg, about 0.1 mg / kg to about 10 mg / kg, about 1 mg / kg to about 5 mg / kg, about 2 mg / kg to about 5 mg / kg, about 0.0001 mg / kg to about 1 mg / kg, about 0.001 mg / kg to about 1 mg / kg, about 0.005 mg / kg to about 1 mg / kg, about 0.01 mg / kg to about 1 mg / kg, or about 0.1 mg / kg to about 1 mg / kg, with a 1 mg / kg dose providing 1 mg of the composition per kg of subject body weight. In certain embodiments, a dose of about 0.005 mg / kg to about 5 mg / kg of the nanoparticle composition of the present invention may be administered. Doses may be administered once or multiple times daily in the same or different amounts to obtain the desired level of mRNA expression and / or therapeutic, diagnostic, prophylactic, or imaging effect. The desired dosage can be delivered, for example, 3 times a day, 2 times a day, 1 time a day, every other day, every 3 days, every week, every 2 weeks, every 3 weeks, or every 4 weeks.In certain embodiments, the desired dosage can be delivered using multiple administrations (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or more administrations).In some embodiments, a single dose can be administered, for example, before or after surgery, or in the case of acute disease, disorder, or symptoms.

[0154]

[0175] Nanoparticle compositions containing one or more payloads may be used in combination with one or more other therapeutic, prophylactic, diagnostic, or imaging agents. "In combination with" does not mean that the agents must be administered simultaneously and / or formulated for delivery together, although these delivery methods are within the scope of the present disclosure. For example, one or more nanoparticle compositions containing one or more different mRNAs may be administered in combination. The compositions may be administered simultaneously with, prior to, or after one or more other desired therapeutic agents or medical procedures. In general, each agent is administered at a dose and / or time schedule determined for that agent. In some embodiments, the present disclosure encompasses delivery of the compositions of the present invention or imaging, diagnostic, or prophylactic compositions thereof in combination with agents that improve bioavailability, reduce and / or modify metabolism, inhibit excretion, and / or modify distribution in the body.

[0155]

[0176] It will be further understood that therapeutic, prophylactic, diagnostic, or imaging active agents utilized in combination may be administered together in a single composition or may be administered separately in different compositions. In general, it is expected that agents utilized in combination will be utilized at levels that do not exceed the levels at which they are utilized individually. In some embodiments, the levels utilized in combination may be lower than the levels at which they are utilized individually.

[0156]

[0177] The particular combination of treatments (therapeutic agents or procedures) to use in a combination regimen will take into account the compatibility of the desired therapeutic agents and / or procedures and the desired therapeutic effect to be achieved. It will also be understood that the treatments used may achieve a desired effect for the same disorder (e.g., a composition that is useful for treating cancer may be administered simultaneously with a chemotherapeutic agent) or may achieve a different effect (e.g., control of any adverse effects). EXAMPLES

[0157]

[0178] The following examples are presented to provide further information and support for the present invention, without intending to be limiting. The following examples demonstrate that HTS methods for optimizing LNP formation for optimal payload loading and particle size distribution can be directly translated to scaled-up manufacturing methods, such as microfluidic-based approaches. This HTS approach reduced material consumption by approximately 10-fold and improved processing output by approximately 100-fold. These results demonstrate the robustness and utility of HTS methods for optimizing LNP manufacturing, thus facilitating their clinical translation.

[0158] Materials and Methods material

[0179] 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (DSPE-PEG 2000 Lipids including cationic 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) were purchased from Avanti Polar Lipids (AL, USA). The ionizable lipid dilinoleylmethyl-4-dimethylaminobutyrate (DLin-MC3-DMA, MC3) was obtained from MCE (NJ, USA) and cholesterol from Sigma (MO, USA). Two model ASOs, ASO-1 (13mer, Na salt form) and ASO-2 (16mer, Na salt form), were synthesized in-house. All other reagents were at least reagent grade and DNase / RNAse free.

[0159] High-throughput preparation of ASO-loaded LNPs

[0180] LNP formulations were screened for various lipid compositions, total lipid concentrations, and ASO loading amounts designed in a 96-well plate matrix using LEA Library Studio software (Unchained Labs, CA, USA). In a typical screen of ASO-1-loaded MC3 LNPs, ASO was dissolved in citrate buffer (25 mM, pH 4) at concentrations corresponding to N / P ratios of 5, 2, 1, and 0.5 and dispensed into 96-well plates (Greiner Bio One 655101, NC, USA) at 150 μl / well using a robotic liquid handler (TECAN® Freedom EVO, NC, USA). Various total lipid amounts (0.2 or 0.4 μmol / well) and DSPE-PEG were added. 2000 Lipid mixtures with lipid content (0, 1.5, 3, or 5 mol% of total lipid) were prepared by mixing individual lipid stocks (20 mg / ml in ethanol) and diluting with ethanol using a TECAN® robot. 50 μl of lipid was then rapidly dispensed at 0.5 ml / s into the ASO plate, followed by phase mixing by 10 pipettings (100 μl each time) using the TECAN® robot to promote self-assembly of ASO-loaded LNPs. The resulting plate contained 96 LNP samples (200 μl / well) that were varied in 32 conditions in parallel (4 levels of ASO loading, 2 levels of total lipid concentration, and 4 levels of lipid composition, n=3). In other experiments, the ionizable lipid MC3 was replaced by the permanent cationic lipid DOTAP, or the 13-mer ASO-1 was replaced by the 16-mer ASO-2, and screened for similar formulation parameters. Reverse dispensing order (injection of ASO solution into lipid mixture) as well as different mixing speeds and times were also investigated to optimize the phase mixing process.

[0160] Characterization of ASO-loaded LNPs

[0181] The structure of ASO-loaded LNPs was determined by cryo-transmission electron microscopy (cyro-TEM). DLS was used to measure particle size distribution. Briefly, ASO-loaded LNPs were diluted 40-fold in phosphate-buffered saline (PBS, pH 7.4) in 96-well glass-bottom microplates (Greiner Bio One 655892, NC, USA) using a TECAN® robot and analyzed for mean particle size and particle size distribution (expressed as polydispersity%, PD%) using a DynaPro® plate reader III (Wyatt Technology, CA, USA). A 60 μl aliquot was adjusted to neutral pH by adding 15 μl of 0.5 M phosphate buffer (pH 7.4) and then transferred to a filter plate (MWCO 100 kD; AcroPrep, PALL, NY, USA) and filtered by centrifugation (2,000×g, 10 min). The unencapsulated ASOs in 50 μl of the filtrate were then analyzed by OD using a UV plate reader (TECAN® Spark, NC, USA). 260 and the percent encapsulation efficiency (%EE) of ASO was calculated: TIFF2024541897000001.tif10170

[0161]

[0182] ASO standards were prepared in the same buffer and subjected to the same filtration process as the LNP samples. For stability experiments, 60 μl of LNPs prepared under an N / P ratio of 1 were directly diluted 10-fold with PBS, stored at 4 or 40° C., and analyzed for particle size and ASO release over a period of 2 weeks.

[0162] Microfluidic preparation of ASO-loaded LNPs

[0183] A microfluidic approach was used for the scale-up preparation of ASO-loaded LNPs screened by the high-throughput approach described above. Briefly, various concentrations of ASO-1 (dissolved in citrate buffer) and total lipid and DSPE-PEG concentrations were used. 2000Varying contents of lipid (dissolved in ethanol) were mixed by a microfluidic device (NanoAssemblr®, Precision NanoSystems, BC, Canada) at an aqueous buffer / ethanol phase ratio of 3 / 1 and a constant total flow rate of 12 ml / min. The collected LNPs were purified by centrifugation-based (2,000×g, 30 min) ultrafiltration (MWCO 10 kD; Amicon, MilliporeSigma, MA, USA) to remove free ASO and lipids, followed by buffer exchange with PBS. LNPs were analyzed for particle size distribution by DLS and ASO encapsulation by hydrophilic interaction liquid chromatography (HILIC). Briefly, encapsulated ASO was extracted from purified LNPs by dissolving in 0.75% Triton solution. A HILIC column (Waters ACQUITY UPLC BEH Amide, 130 Å, 1.7 μm, 3 mm x 50 mm), mobile phase A (80 / 20 (v / v) acetonitrile / 25 mM ammonium acetate in water), and mobile phase B (40 / 60 (v / v) acetonitrile / 25 mM ammonium acetate in water) were used with gradient elution from 0 to 100% of phase B within 10 min, at a flow rate of 0.8 ml / min, a column temperature of 40 °C, and a detection wavelength of 260 nm.

[0163] statistical analysis

[0184] All results are presented as mean ± SD (n = 3). Data were analyzed by one-way or two-way analysis of variance (ANOVA) followed by Turkey, Sidak or Dunnett's post-hoc tests for comparison of multiple groups using Prism 8.0 (GraphPad Software). P values ​​less than 0.05 were considered statistically significant.

[0164] Example 1 Optimizing Phase Mixing Processes with Robotic Liquid Handlers

[0185] To develop a high-throughput solvent injection method for LNP preparation, the effect of phase mixing on particle size and ASO encapsulation was first investigated. ASO-1 was mixed with 0.4 μmol of total lipid and 1.5 mol% DSPE-PEG 2000LNPs composed of ASO were loaded by charge-mediated complexation under an N / P ratio of 1. The ethanol phase containing lipids was dispensed and mixed with the aqueous ASO phase and vice versa using a TECAN® liquid handler at different pipetting speeds ranging from a minimum of 0.1 ml / s to a maximum of 0.9 ml / s according to the instrument settings. Ethanol-buffer injections produced similar LNPs with a mean diameter of 145 nm (Figure 1A), a %PD of 18% (Figure 1B), and a %EE of ASO of 83% (Figure 1C) under slow, medium, or fast speeds for injection and subsequent mixing for 10 times. In contrast, buffer-ethanol injections at slow speed (0.1 ml / s) produced larger (mean diameter 220 nm) and more polydisperse (%PD 41%) particles with a lower %EE (43%) (Figures 1A-1C). However, increasing the injection rate produced similar LNPs as the ethanol-buffer injection, suggesting that the formation of ASO-loaded LNPs requires rapid dissipation of concentrated lipids in the aqueous buffer. Next, LNPs were prepared under ethanol-buffer injection, followed by phase mixing at different pipetting times and speeds. A medium speed (0.5 ml / s) and 10 times of mixing were sufficient to produce homogenous LNPs with high ASO loading, while further increase in mixing speed or times did not affect particle size and %EE (Figure 1D-1F). Therefore, for the following studies, we selected the condition of ethanol-buffer injection followed by 10 times of mixing at 0.5 ml / s.

[0165] Example 2 HTS of ASO-loaded LNP formulations

[0186] To investigate the effect of formulation parameters on the key quality attributes of LNPs, we designed an HTS workflow that allows for streamlined preparation and characterization of these formulations (Figure 2). ASOs were first dissolved in citrate buffer at pH 4.0, which is lower than the pKa of MC3 (6.4), so that the lipids are positively charged and promote charge-mediated complexation. The pH of the solution was then adjusted to neutral by phosphate buffer before analysis.

[0166]

[0187] For a typical screen, 32 different samples (three replicates each) varying at two levels of total lipid concentration, four levels of ASO loading adjusted by N / P ratio, and four levels of PEGylated lipid content were screened in parallel in a 96-well plate (Figure 3A). Among the three formulation parameters investigated, PEGylated lipid was essential for LNP formation, as multimodal large aggregates were generated when no PEG was incorporated into the lipid composition (Figure 3C-3D, Figure 4). Significantly increasing the PEGylated lipid content (P<0.0001) decreased the mean particle size, i.e., at 1.5, 3, and 5 mol% DSPE-PEG. 2000 Lipids containing 5 mol% DSPE-PEG resulted in LNP diameters of approximately 120, 80, and 60 nm, respectively (Figures 3C-3D). However, polydispersity also increased, with the addition of 5 mol% DSPE-PEG. 2000 is probably a small DSPE-PEG 2000 It even produced a subpopulation due to the formation of micelles (Figure 3C). See, e.g., Johnsson et al., 2003, Biophys J 85(6):3839-47; Gill et al., 2015, J Drug Target 23(3):222-31.

[0167]

[0188] On the other hand, the %EE of ASO was mainly determined by the N / P ratio. An N / P ratio higher than 1 with excess complexing sites in MC3 resulted in a %EE of over 80%. Meanwhile, a two-fold excess of ASO-1 above the charge equilibrium point significantly reduced the %EE to about 50% (Figure 3E). Similar results were seen when MC3 was replaced with another cationic lipid, DOTAP (Figures 5A-5C), or when ASO-1 was replaced with ASO-2 (Figures 6A-6C), demonstrating the robustness of the HTS results.

[0168] Example 3 Validation of HTS results with scaled-up LNP preparation

[0189] The impact of the screened formulation parameters on LNP quality attributes was then verified by comparing the results from the HTS approach with those from the microfluidic formulator. The two methods showed similar results: (1) with increasing PEG content, LNP size decreased but polydispersity increased (Figure 7A); (2) LNP size was stable with increasing total lipid concentration up to 2 mM (Figure 7B); (3) LNP size remained stable when N / P ratio < 2 (Figure 7C); (4) excessive ASO loading (N / P ratio < 1) resulted in a significant decrease in %EE (Figure 7D); and (5) LNPs prepared with the same N / P ratio and PEGylated lipid content showed similar structures (Figure 7E). Furthermore, the HTS approach demonstrated a linear regression R 2 The dependence of particle size and polydispersity on PEGylated lipid content was successfully predicted, as shown by a strong correlation of >0.9 (Figure 7A).

[0169] Example 4 Stability screening of ASO-loaded LNPs

[0190] To further investigate the effect of different particle sizes on formulation stability, ASO-1-loaded LNPs prepared with various PEG contents were diluted 10-fold in PBS and incubated at 4 °C or 40 °C to monitor particle size distribution over a 2-week period. The N / P ratio was kept above 1 and the %EE of ASO was approximately 90%, allowing quantification of ASO leakage from LNPs during stability testing. As shown in Figures 8A-8B, 1.5 mol% or 3 mol% DSPE-PEG LNPs prepared by high-throughput solvent injection or NanoAssemblr® were used for the analysis of ASO-1-loaded LNPs. 2000 LNPs containing 1.5 mol% DSPE-PEG similarly maintained their initial mean particle size (Figure 8A) and polydispersity (Figure 8B) during incubation at 4°C. 2000 LNPs containing 1.5 mol% DSPE-PEG showed an increase in particle size after 1 week, but the polydispersity remained constant (Figure 9). 2000 LNPs containing DSPE-PEG also showed minimal ASO leakage within the first 3 days, but after 2 weeks, LNPs containing 3 and 5 mol% DSPE-PEG 2000The LNPs showed similar levels of ASO leakage as the LNPs containing 100% glycerol (Figure 10). No ASO leakage was detected over a one-month period at 4°C.

[0170]

[0191] The solvent injection method was selected for the high-throughput preparation of LNP formulations because the phase mixing process could be performed by a robotic liquid handler. Compared with manual pipetting, the multichannel liquid handler enabled high-throughput parallel processing of 96 samples and achieved uniform liquid dispensing and mixing across the wells. The key process involved rapid and thorough mixing of mutually miscible phases, e.g., ethanol to dissolve lipids and aqueous buffer to dissolve nucleic acids, to promote lipid self-assembly into spherical lipid layers and nanoparticle structures. This method has been widely used to prepare liposomes and produced uniform nanoparticles when the ethanol phase was adjusted to less than 50% by volume. Increasing the ethanol phase ratio and / or lipid concentration produced large particles or aggregates, likely due to inefficient phase mixing, as also shown by the results of slow buffer-ethanol injection (Figures 1A-1B). Findings from the automated mixing process by the liquid handler were highly correlated with the results of LNPs prepared by the microfluidic method. Flow rate ratio (FRR, aqueous to organic flow rate) is one of the important formulation parameters during microfluidic preparation, with a low FRR producing larger particles. Buffer-ethanol injection at a low speed showed a condition of low FRR. Therefore, we optimized the automated mixing conditions, setting the ethanol-buffer injection at 0.5 ml / s under a 1 / 3 ethanol / aqueous volume ratio (25% ethanol by volume), followed by pipetting 10 times to achieve efficient phase mixing and produce uniform particles with high encapsulation efficiency.

[0171]

[0192] We then developed a streamlined workflow to screen formulation variables, including total lipid concentration, lipid composition, and ASO loading amount, for optimal quality attributes of ASO-loaded LNPs. To this end, ASO particle size distribution and %EE were measured using high-throughput DLS and OD spectroscopy, respectively. 260The conditions under which uniform nanoparticles with high ASO loading could be produced were determined. The screening results showed that the PEGylated lipid content significantly affected the particle size distribution (Figures 3B-3D, 5A-5B, 6A-6B). DSPE-PEG incorporated at 1.5 mol% of the total lipids 2000 produced unimodal nanoparticles with an average diameter of about 120 nm, while more PEG increased polydispersity. Ionizable lipids consisting of tertiary amine structures are increasingly used in lipid-based delivery systems for nucleotides, and show better intracellular delivery efficiency and lower cytotoxicity than permanently charged cationic lipids. See, for example, Cullis & Hope, 2017, Mol. Ther. 25(7):1467-1475, Sabnis et al. 2018, Mol Ther. 26(6):1509-1519; Semple et al., 2010, Nature Biotechnology, 28(2):172-176. Consistent with a loading mechanism of charge-mediated complexation, screening results showed ASO encapsulation determined by the N / P ratio, with %EE of approximately 90% at an N / P ratio of 1 (Figures 3E, 5C, 6C), corresponding to a loading capacity of 0.29 mg RTR3833 / mg lipid (1.5 mol% DSPE-PEG 2000 (containing 2 mM total lipid).

[0172]

[0193] Importantly, results from the HTS approach successfully predicted results from microfluidic formulators, which are increasingly being utilized to prepare nanoparticle formulations with scalable generation. See, for example, Belliveau et al., 2012, Mol. Ther. Nucleic Acids, 1, e37; van Swaay & de Mellow, 2013, Lab Chip 13(5):752-67. Both methods showed similar dependence of LNP size on PEGylated lipid content (Figure 7A), total lipid concentration (Figure 7B), and N / P ratio (Figure 7C), and the %EE of ASO was similarly controlled by the N / P ratio (Figure 7D). The two methods also produced LNPs with similar structures under the same formulation parameters (Figure 7E). Furthermore, these ASO-loaded LNPs showed stable particle size distributions (Figures 8A-8B) and approximately 20% leakage of encapsulated ASO over 2 weeks of storage at 40 °C (Figure 10). However, compared to microfluidic preparation, the HTS approach showed significant advantages in saving about 10-fold of raw materials while increasing preparation and analysis output by about 100-fold (parallel processing of 96 samples in a microplate compared to a single microfluidic run), indicating great potential for early-stage formulation screening (Figure 11). Based on the screening results, it was determined that 1.5 mol% DSPE-PEG2000 and N / P ratio ≥ 1 produced optimal LNP formulations with uniform and stable particle size and high ASO loading. After introducing different lipids and other ASOs into the HTS system, the same opinion was still valid, suggesting that this screening platform could be expanded to various types of carriers and cargoes such as siRNA and single guide RNA.

[0173]

[0194] The HTS screening approach demonstrated a reproducible formulation platform for preparing LNPs. The translatable results from the automated injection platform to microfluidic preparations created a seamless workflow to support screening and scale-up formulations, avoiding bridge studies resulting from formulation inconsistencies. The next step is to integrate the current workflow with downstream in vitro screening to correlate physicochemical attributes of ASO-loaded LNPs with therapeutic efficacy. In addition, the workflow can be further improved to address more formulation attributes, such as simultaneous quantification of both API and excipients by zeta potential and liquid chromatography strategies. Yamamoto et al.,2011 J Chromatogr B Analyt Technol Biomed Life Sci 879(20),3620-5,Li et al.,2019,J Chromator A 1601:145-154.

[0174]

[0195] In this example, a high-throughput approach was developed to screen formulation parameters and address quality attributes of ASO-loaded LNPs. A streamlined workflow beginning with automated liquid dispensing and mixing, followed by high-throughput analysis of particle size and ASO encapsulation, identified PEGylated lipid content and N / P ratio as major determinants of particle size distribution and encapsulation efficiency, respectively. Furthermore, HTS results successfully predicted results from scale-up preparations using microfluidics. The robust screening results, as well as significant material savings and improved analytical output, suggest great promise for this approach to advance the development of lipid-based nanoparticle formulations.

[0175] Example 5 Alternative methods for quantification of ASO inclusion

[0196] Quantification of ASO encapsulation was determined using a fluorescence plate reader. Briefly, ASO-loaded LNPs were prepared by high-throughput solvent injection method, then diluted 50-fold in TE buffer, mixed with an equal volume of 5000-fold diluted fluorescent probe Sybr-gold, and non-encapsulated ASO was quantified using a fluorescence plate reader (Ex / Em=495 / 550 nm). LNPs were then disrupted by direct addition of an equal volume of 10000-fold diluted Sybr-gold in 1% Triton TE (i.e., the final probe dilution was kept at 10000-fold and the Triton concentration was 0.5% by volume) (Figure 12A). Fluorescence measurements were then performed to quantify total ASO. Encapsulation efficiency (%EE) was calculated as follows: TIFF2024541897000002.tif10170

[0176]

[0197] Calculations showed comparable %EE results for two different LNP formulations prepared at different N / P ratios using fluorescence and UV-Vis methods (Figure 12B). Results are expressed as mean ± SD, n = 2; ns, not significant (analyzed by two-way ANOVA followed by Sidak's multiple comparisons).

[0177] Example 6 HTS of HiBiT peptide-loaded LNP formulations

[0198] To investigate the influence of formulation parameters on key quality attributes of liposomes, we designed an HTS workflow that allows streamlined preparation and characterization of these formulations. HiBiT was first dissolved in 20 mM histidine-acetate buffer supplemented with 150 mM NaCl (pH 5.5) and dispensed into a microwell plate using a robotic liquid handler. Lipid mixtures were prepared as in Example 2 (Figure 13A).

[0178]

[0199] For a typical screen, 32 different samples (three replicates each) varying across four LNP formulations and eight combinations of PEGylated lipids, shielded PEGylated lipids, and PEGylated lipids conjugated with azides were screened in parallel in a 96-well plate (Figure 13B). Among the eight formulation parameters investigated, PEGylated lipids were necessary for LNP formation, as multimodal large aggregates were generated when PEG was not incorporated into the lipid composition (Figure 13C). Quantification of free peptide concentrations before and after purification yielded average purification efficiencies of approximately 98% and 61% for gel filtration and dialysis, respectively (Figures 13D-13F). Particle recoveries were generally between 80-120%, except for low values ​​with aggregated samples prepared without PEGylated lipids (Figure 13G). Moreover, particle size distributions remained constant after purification by gel filtration (Figure 13H).

[0179] Example 7 HTS identified the effect of various PEG-lipid attributes on the size distribution of ASO-LNPs.

[0180] HTS preparation and characterization of ASO-loaded LNPs

[0200] Cholesterol, 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), and all linear PEGylated lipids for LNP formulation were purchased from Avanti Polar Lipids (AL, USA). The branched PEGylated lipid N-[2',3'-bis(methylpolyoxyethyleneoxy)propane-1'-oxycarbonyl]-1,2-distearoyl-sn-glycero-3-phosphoethanolamine (DSPE-2arm-PEG-2k) was obtained commercially from NOF America Corporation (NY, USA). The complete list of PEGylated lipids is listed in Table 1 below. TIFF2024541897000003.tif255169TIFF2024541897000004.tif215170

[0201] The ionizable lipid dilinoleylmethyl-4-dimethylaminobutyrate (DLin-MC3-DMA; MC3) for LNP formulation was purchased from MedChemExpress (New Jersey, USA). A 17-mer ASO (MW 5635 Da, Na salt form) with a phosphorothioate backbone was custom synthesized by BioSpring GmbH (Frankfurt, Germany) using solid-phase synthesis. All other reagents were DNase / RNase free and commercially available and used without further purification.

[0181]

[0202] LNPs with various PEGylated lipids were prepared using a previously reported high-throughput approach. Briefly, ASO was dissolved in citrate buffer (25 mM, pH 4.0) at 93.9 μg / mL and dispensed into a 96-well plate (Greiner Bio One 655101, NC, USA) at 150 μL / well using a TECAN Freedom EVO® robotic liquid handler (Tecan Life Sciences, NC, USA). Using an automated setup, different lipid mixtures consisting of MC3, DSPC, cholesterol, and the respective PEG-lipid analogs were prepared in ethanol at a molar ratio of 40:10:(50-X):X, where X=1, 3, or 5, and the total lipid concentration was 4 mM to maintain N:P=2 in the resulting ASO-LNPs. N:P is defined as the molar ratio of positively charged amine (N) groups in the ionizable lipids to negatively charged phosphate (P) groups on the nucleic acid backbone. The lipid mixture was transferred to a 12-channel reservoir plate (Axygen RES-MW12-LP or -HP, NC, USA) and 50 μL of lipid phase was injected into the ASO solution in a 96-well plate using a robot (speed = 0.5 mL / s followed by 10 cycles of mixing at 0.1 mL / cycle) to obtain 1 mM total lipid per well with an ethanol:aqueous phase volume ratio of 1:3. Each LNP formulation was prepared in triplicate. ASO-loaded LNPs were diluted with phosphate-buffered saline (PBS, pH 7.4) to a final concentration of 1 mM total ASO per well. A small aliquot of each sample was transferred to a glass-bottom 96-well plate (Greiner Bio One 655892, NC, USA) and further diluted 50-fold with PBS for characterization of particle size distribution by dynamic light scattering (DLS) using a DynaPro® plate reader III (Wyatt Technology, CA, USA).

[0182] Microfluidic preparation and characterization of ASO-loaded LNPs

[0203] A microfluidic mixing method was used for the scale-up preparation of selected positive and negative hit ASO-LNP formulations identified by the HTS approach. Different lipid mixtures consisting of MC3, DSPC, cholesterol, and selective PEG-lipid analogs were dissolved in ethanol at a molar ratio of 40:10:(50-X):X, where X=1, 3, or 5, and the total lipid concentration was 4 mM. The ethanol flow was then mixed in a microfluidic laminar flow mixing device (NanoAssemblr). TM The LNPs were rapidly mixed with a water stream containing 93.9 μg / mL ASO dissolved in citrate buffer (25 mM, pH 4.0) using a Benchtop (Precision NanoSystems, BC, Canada) at a volume ratio of 1:3 and a total flow rate of 12 mL / min. The formulated LNPs were purified by centrifugal ultrafiltration (MWCO 10 kD; Amicon, MilliporeSigma, MA, USA) at 2,000 g for 30 min to remove free ASO and lipids, followed by buffer exchange with RNase-free PBS. The purified formulations were analyzed for particle size distribution using DLS.

[0183] statistical analysis

[0204] Data plotting and statistical analysis were performed using Prism 9.2.0 (GraphPad Software, San Diego, CA). All results are expressed as mean ± SEM. n=3 includes the average of three internal replicates.

[0184] Diverse PEG-lipids used in the ASO-LNP formulation library

[0205] In our HTS lipid library design, we selected DLin-MC3-DMA (MC3), DSPC, and cholesterol as the constituent lipids for all ASO-LNP formulations, but varied the PEG-lipid content (Figures 15A and 15B). The combination of MC3, DSPC, and cholesterol was used in ONPATTRO®, the first FDA-approved siRNA-LNP formulation, and has been used as a benchmark for oligonucleotide delivery in many preclinical LNP model systems. To systematically understand the impact of PEG-lipids on LNP cargo delivery, several PEG-lipid analogs were used in combination with MC3, DSPC, and cholesterol during ASO-LNP formation (Table 1). PEG-lipids commonly used in drug delivery applications were chosen from biologically relevant lipid families, including anionic phosphoglycerides, neutrally charged diglycerides, and ceramides. For each PEG-lipid type, we included multiple analogs that varied the length of the C-tail or the size of the PEG chain (Figure 15B). In this study, the effects of structure (linear or branched) and PEG-lipid C-tail saturation were also evaluated.

[0185]

[0206] In addition to testing individual PEG-lipid characteristics, PEG-lipid concentrations were also varied to assess their impact on formulation properties and cargo delivery. The molar ratio of PEG-lipid in the LNPs was adjusted to 1, 3, and 5 mol% by adjusting the molar ratio of cholesterol in the lipid mixture. Using these PEG-lipid parameters, a library of 54 different ASO-LNP formulations was prepared in a 96-well plate-based HTS workflow for physicochemical characterization and in vitro evaluation of ASO delivery.

[0186] PEG content affects particle size distribution of ASO-LNPs

[0207] The mean hydrodynamic diameters of 54 different ASO-LNP formulations ranged between 52 and 212 nm as measured by DLS, showing a general trend of decreasing particle size as the molar ratio of PEGylated lipids increased from 1% to 5% (Figures 16A-16C). LNPs formulated with 1 mol% of short PEG-lipids (MW < 1000 Da), e.g. #6 and #10, had the largest particle diameter of 212 nm. In contrast, 5 mol% of long PEG lipids (#9) produced the smallest particles (52 nm), likely due to increased steric hindrance by the PEG chains, which hindered particle growth. Specifically, anionic PEG lipids showed a clear decrease in particle size as the PEG size increased, as did the PEG molar ratio in the LNP composition (Figure 16A). In contrast, LNPs prepared with neutral diglyceride and ceramide PEG lipids showed no correlation between particle size and PEG content, especially for formulations #13 and #16 (Figure 16B). These findings suggest that repulsion between charged head groups plays a major role in determining the particle size of anionic PEGylated LNPs, alongside the steric barrier of the PEG chains. Furthermore, a comparison of linear and branched DSPE-PEG2k variants (#8 and #9) showed no significant effect of PEG structure on the hydrodynamic diameter (Figure 16C). The mean particle diameters were also shown in a color-coded heat map to indicate particle size trends (see Figure 17).

[0187]

[0208] Increasing the PEG-lipid molar ratio has a charge-dependent effect on particle diameter, but PEG-lipid content has an overall positive correlation with LNP polydispersity (%PD) (Figures 16D-16F). Notable exceptions to this trend are #6, #15, and #16. PEG-lipids #15 and #16 are from the neutrally charged ceramide-C8 PEG-lipid family, which also showed no correlation between PEG-lipid content and particle size. Consistent with our previous data, PEG-lipids formulated at 5 mol% with long PEG arms (2000 Da) had a highly polydisperse size distribution, likely due to the presence of a micellar PEG-lipid subpopulation.

[0188]

[0209] We also compared the effect of lipid anchor groups with different C-tail lengths (DMPE / DPPE / DSPE, DSG / DMG, and Cer-C8 / Cer-C16), saturation levels (DSPE / DOPE), and PEG-linker chemistries (DMPE / DMG and DSPE / DSG). The hydrophobic tail of the PEG-lipid did not significantly affect the size or polydispersity index of the LNPs. This is in contrast to the importance of the hydrophilic PEG component of the PEG-lipid. Similar observations have been previously reported for siRNA-LNPs prepared with PEG-lipids containing 14, 16, and 18 carbon chains.

[0189] Regression analysis of LNP particle size

[0210] Linear regression models confirmed the significance (p<0.05) of PEG-lipid charge, molar ratio, and PEG size on LNP particle size distribution compared to non-significant effects of different C-tail attributes (Tables 2 and 3).

[0190]

[0211] Linear regression model for anionic PEG-lipids: Hydrodynamic diameter of ASO-LNP (nm) = 225.71-0.44*carbon tail length (#C)-0.05*PEG size (Da)-14.12*PEG-lipid mol%. TIFF2024541897000005.tif55170

[0191]

[0212] Model Overview: R-squared = 0.869, adjusted R-squared = 0.857, standard error = 15.37, number of observations = 36. ANOVA: Significance F = 3.16 x 10 -14

[0192]

[0213] Linear regression model for neutral PEG-lipid: Hydrodynamic diameter of ASO-LNP (nm) = 172.68 + 1.29 * carbon tail length (#C) - 0.03 * PEG size (Da) - 6.21 * PEG-lipid mol%. TIFF2024541897000006.tif55170

[0193]

[0214] Model Overview: R-squared = 0.700, adjusted R-squared = 0.636, standard error = 15.74, number of observations = 18. ANOVA: Significance F = 5.9 x 10 -4

[0194]

[0215] Taken together, these data suggest that the size distribution of LNPs depends primarily on the surface-stabilizing PEG content rather than on the attributes of the lipid tail, and that this PEG dependence is particularly dominant in anionic PEG-lipid scaffolds.

[0195] Example 8 HTS for identification of ASO-LNP behavior trends

[0216] Our HTS approach allows for rapid preparation and characterization of diverse ASO-LNP formulations in a 96-well plate format. This high-throughput workflow can be seamlessly expanded to evaluate LNP delivery in target cell lines. This HTS approach leads to significant savings in materials and time. Furthermore, the direct comparison of ASO-LNP formulations in an identical environment generates a robust data set and minimizes processing variability.

[0196]

[0217] The HTS approach is also advantageous for data analysis and interpretation. First, characterization involving a large number of formulations can be performed in a short time (Figures 16A-16F). Second, comprehensive screening can identify correlations that may be masked with a narrow sample size. For example, our HTS data set shows that the hydrophilic PEG component of the PEG-lipid affects the particle size distribution of LNPs (Figures 16A-16F). Such behavioral trends can be quantitatively defined by predictive correlations using regression analysis. Linear regression models established that the charge dependence of PEG-lipid concentration and PEG size (p<0.05) on the size distribution of LNPs was significant compared to the C-tail attribute. The accuracy of these correlations can be further improved by iteratively screening a broader sample set in combination with advanced machine learning algorithms.

[0197] HTS predicts ASO-LNP performance in scale-up formulations

[0218] As with all screening assays, the value of the HTS approach lies in its ability to predict behavior in a scaled-up system. Therefore, we verified the convertibility of LNP attributes from an HTS approach to a scalable microfluidic method for manufacturing self-assembled nanoparticle formulations. Six hit ASO-LNPs formulated at specific PEG species and molar ratios (#13-1%, #16-3%, #1-5%, #10-1%, #8-3%, #9-5%) were selected from the HTS library. Representative formulations were selected based on containing a diverse PEG-lipid array of diglyceride (#13) PEG-lipid, ceramide (#16) PEG-lipid, and phosphoglyceride (#1) PEG-lipid with different lipid tail saturation levels (#10, #8), PEG structures (#9), and PEG-lipid contents (1, 3, 5 mol %), ensuring a robust verification of the predictability of HTS across a wide range of PEG contents in the LNP. The selected ASO-LNPs were scaled up 10-fold using a microfluidic mixer (NanoAssemblr TM Benchtop) under formulation conditions similar to the corresponding HTS.

[0198]

[0219] The DLS characteristics of six different LNPs prepared using microfluidics showed that the hydrodynamic diameter was similar to that of each LNP formulated using the HTS method. (Figure 18). The HTS approach reliably predicted the physicochemical properties and smoothly reflected these attributes in the microfluidics-based formulation. Currently, microfluidic technology has been widely adopted due to its scalability (from <mL to L) suitable for preclinical and clinical applications of LNP-based drug delivery vehicles. Thus, the predictive HTS approach can be utilized for formulation scale-up while significantly saving the resources typically required to optimize formulations on a scalable microfluidic engineering platform.

[0199]

[0220] In accordance with the present invention, a high-throughput screening approach is described to characterize LNP size distribution trends as a function of various PEG-lipid parameters such as PEG size, PEG-lipid content in the LNP, carbon-tail length, etc. The invention described herein can be further combined with machine learning algorithms to identify and define quantitative correlations across the vast datasets obtained in HTS.

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Claims

1. 1. A high-throughput method for producing a lipid nanoparticle (LNP) preparation, comprising: a. Obtaining a first solution comprising an aqueous phase; b. obtaining a second solution comprising an organic phase and a plurality of molecules capable of self-assembling, wherein the self-assembling molecules comprise at least one lipid component composed of at least one lipid molecule, wherein the at least one lipid molecule comprises an ionizable lipid species, and wherein the first solution and the second solution are miscible; c. dissolving payload molecules that are oligonucleotides in either the first solution or the second solution; d. Using a robotic liquid handler to prepare and dispense the phases having different compositions into multiple wells; e. mixing the first solution and the second solution to obtain lipid nanoparticles encapsulating the payload using the robotic liquid handler under conditions suitable for LNP formation, wherein at least one of the following conditions: type of self-assembling molecules, composition ratio of the self-assembling molecules, ratio and / or concentration of the self-assembling molecules to the payload, phase, buffer type and pH selection, injection order, injection rate, mixing rate, volume, phase ratio, injection duration, and mixing duration is varied between different wells; f. Measuring the encapsulation efficiency of the LNPs, and optionally measuring at least one of particle size distribution, purification and particle recovery, and formulation stability; g. Determining the optimal parameters for producing the LNP preparation; and h. Producing the LNP preparation based on the optimized parameters. Including, The encapsulation efficiency is optimized by measuring the charge ratio of ionizable lipid / oligonucleotide. method.

2. The method of claim 1 , wherein the oligonucleotide is an antisense molecule.

3. The method of claim 1 , wherein the oligonucleotide is an siRNA.

4. The method of claim 1 or 3, wherein the oligonucleotide is an shRNA.

5. 3. The method of claim 1 or 2, wherein the oligonucleotide is between about 10 and about 30 nucleotides in length.

6. The method described in claim 1, wherein the oligonucleotide is mRNA.

7. 7. The method of claim 6, wherein the size of the mRNA is from about 500 nucleotides to about 3000 nucleotides in length.

8. The method described in claim 6, wherein the size of the mRNA is from about 1,000 nucleotides to about 2,000 nucleotides in length.

9. The method of claim 1 or 2, wherein the payload is dissolved in the first solution.

10. The method of claim 1 or 2, wherein the payload is dissolved in a second solution.

11. 3. The method of claim 1, wherein the first solution is an aqueous buffer solution.

12. 3. The method of claim 1 or 2, wherein the first solution comprises a pH-adjusted buffer and an osmolality-adjusted buffer.

13. 3. The method of claim 1 or 2, wherein the organic phase of the second solution comprises methanol.

14. 3. The method of claim 1 or 2, wherein the organic phase of the second solution comprises ethanol.

15. 3. The method of claim 1 or 2, wherein the at least one lipid molecule comprises at least one additional lipid molecule selected from the group consisting of cationic lipid species, non-cationic lipid species, phospholipid species, and non-phospholipid species.

16. 3. The method of claim 1 or 2, wherein the total concentration of lipids is varied.

17. 17. The method of claim 16, wherein the total lipid concentration varies between about 0.4 mM and about 4 mM.

18. 3. The method of claim 1 or 2, wherein the percentage of lipid that is PEGylated is varied.

19. 20. The method of claim 18, wherein the percentage of lipid that is PEGylated varies between about 0.5% and about 5% of the total lipid composition.

20. 3. The method of claim 1 or 2, wherein the N:P ratio of the payload is varied.

21. 21. The method of claim 20, wherein the N:P ratio varies between about 0.5 and about 5.

22. 3. The method of claim 1 or 2, wherein the LNP is a polymeric lipid nanoparticle.

23. The method of claim 1 or 2, wherein the LNP is a liposome.

24. The method of claim 1 or 2, wherein the LNP is a lipoprotein nanoparticle.

25. 3. The method of claim 1, wherein the first solution is injected into the second solution.

26. 3. The method of claim 1, wherein the second solution is injected into the first solution.

27. ​​A method described in claim 1 or 2, wherein the payload encapsulation efficiency exceeds 80%.

28. The method of claim 1 or 2, wherein the LMP has an average diameter of 80 to 200 nm with a monomodal size distribution and a polydispersity of less than about 30%.

29. 3. The method of claim 1 or 2, wherein the LNPs maintain similar size distribution and payload encapsulation for at least one month under storage in solution at 4°C.

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