Methods and compositions for assessing immune response to lipid compositions

Abstract

The disclosure relates to methods and compositions for assessing an immune response to a lipid composition using iMonocytes.

Description

[0001] METHODS AND COMPOSITIONS FOR ASSESSING IMMUNE RESPONSE TO LIPID COMPOSITIONS

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No. 63 / 735,680, filed December 18, 2024, and U.S. Provisional Application No. 63 / 865,011, filed August 15, 2025, each of which is herein incorporated by reference in its entirety.

[0004] BACKGROUND

[0005] Lipid compositions, such as lipid nanoparticles (LNPs), have numerous applications in the medical field and are commonly used as therapeutic delivery systems, and in some instances, enhance the effectiveness of the therapeutic being delivered. Nonetheless, these nanoparticles are recognized by the body as foreign materials and stimulate an immune response. In vitro assays to assess an immune response to, or the immunogenicity of, lipid compositions are valuable for evaluating their safety and efficacy in drug delivery and gene therapy, for example.

[0006] SUMMARY

[0007] Current in vitro assays used to assess an immune response to a lipid composition typically rely on donor-derived human peripheral blood mononuclear cells (PBMCs), which introduce variability due to genetic and environmental differences. Provided herein are improved in vitro assays that utilize iMonocytes differentiated from induced pluripotent stem cells (iPSCs) (also referred to as “iPSC-derived monocytes”) or other progenitor cells to evaluate an immune response to, and thus the immunogenicity of, lipid compositions, such as lipid nanoparticles (LNPs). iMonocytes can be produced in large quantities under defined conditions, reducing batch-to-batch variability; and they offer a reproducible system for immunogenicity testing of lipid compositions.

[0008] Thus, aspects of the technology relate to a method of assessing an immune response to a lipid composition, the method comprising: combining monocytes differentiated from pluripotent cells, such as induced pluripotent stem cells, and a lipid composition; and assessing the monocytes for an immune response to the lipid composition.

[0009] 1

[0010] #14672028vl Other aspects of the technology relate to a method of assessing an immune response to a lipid composition, the method comprising: differentiating monocytes from pluripotent cells, such as induced pluripotent stem cells; combining a population of the monocytes and a lipid composition in a cell culture medium comprising serum; and assessing the monocytes for an immune response to the lipid composition.

[0011] In some embodiments, about 20% to about 40%, optionally about 30%, of the monocytes of a population express CD14. In some embodiments, about 30% to about 50%, optionally about 40%, of the monocytes of a population express CD 16. In some embodiments, monocytes of the population secrete TNF-a in response to exposure to a TLR agonist, optionally a TLR7 / 8 agonist.

[0012] In some embodiments, the monocytes and the lipid composition are combined in a cell culture medium. In some embodiments, the culture medium comprises serum. In some embodiments, the concentration of the serum in the cell culture medium is about 5% to about 15%, for example, about 10%. In some embodiments, the serum comprises fetal bovine serum.

[0013] In some embodiments, the cell culture medium comprises a Toll-like receptor (TLR) agonist. For example, the TLR agonist can be selected from imidazoquinoline compounds, adenine compounds, benzazepine compounds, flagellin, guanosine compounds, thiazoquinoline compounds, lipopolysaccharides, nucleic acid derivatives (e.g., CpG-ODNs, Poly I, ssRNA), nucleoside analogs, and synthetic small molecules. Other TLR agonists may be used.

[0014] In some embodiments, the TLR agonist is selected from imidazoquinoline compounds. For example, the imidazoquinoline compounds can be selected from resiquimod (R848), imiquimod, gardiquimod, dactolisib, and sumanirole. In some embodiments, the TLR agonist is resiquimod. In some embodiments, the concentration of resiquimod in the cell culture medium is about 0.05 pg / mL to 0.1 pg / mL.

[0015] In some embodiments, assessing the monocytes for an immune response comprises assaying for a marker of immune activation, assessing cell viability, assessing cell proliferation, assessing phagocytic activity, assessing transfection efficiency, and / or assessing influx of calcium of the monocytes. In some embodiments, assessing the monocytes for an immune response comprises assaying for a marker of immune activation (e.g., via increased or decreased gene or protein expression or activity). For example, the marker of immune activation can be selected from cytokines, chemokines, reactive oxygen species (ROS), nitric

[0016] 2

[0017] #14672028vl oxide (NO), pro-inflammatory lipid mediators, complement proteins, growth factors, and immune checkpoint proteins.

[0018] In some embodiments, a marker of immune activation is a cytokine or chemokine. In some embodiments, the cytokine or chemokine is selected from IL-1, IL-la, IL-ip, IL-2, IL- 4, IL-6, IL-8, IL-10, IL-11, IL-12, IL-13, IL-17, IL-18, CCL3, CCL5, IFN-y, MCP-1, TNF-a, CXCL10 / IP-10, and TGF-p.

[0019] In some embodiments, the monocytes are exposed to multiple doses (e.g., serial dilutions) of the lipid composition.

[0020] In some embodiments, the lipid composition comprises an LNP. In some embodiments, the lipid composition comprises a liposome.

[0021] In some embodiments, the lipid composition further comprises a (at least one) cargo molecule, such as a therapeutic molecule. In some embodiments, the cargo molecule is selected from nucleic acids and proteins. For example, the cargo molecule can be selected from messenger RNA (mRNA), short interfering RNA (siRNA), microRNA (miRNA), guide RNA (gRNA), circular RNA (circRNA), and self-amplifying messenger RNA (samRNA). In some embodiments, the therapeutic molecule is an mRNA. In some embodiments, the mRNA encodes an antibody or an antigen. In some embodiments, a cargo molecule is selected from gene editing molecules (e.g., a Cas nuclease, a guide RNA, and / or a ribonucleoprotein (RNP) complex including a Cas nuclease and a guide RNA). In some embodiments, a lipid composition comprises more than one (e.g., 2, 3, 4, or more) cargo molecule.

[0022] Other aspects of the technology relate to a composition comprising monocytes differentiated from pluripotent cells, such as iPSCs, and a lipid composition. In some embodiments, the composition further comprises cell culture medium. In some embodiments, the cell culture medium further comprises serum. In some embodiments, the concentration of the serum in the cell culture medium is about 5% to about 15%, for example, about 10%. In some embodiments, the serum comprises fetal bovine serum. In some embodiments, the serum comprises a TLR agonist, for example, selected from resiquimod (R848), imiquimod, gardiquimod, dactolisib, and sumanirole.

[0023] BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present disclosure, which can be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.

[0025] 3

[0026] #14672028vl FIGs. 1A-1C show that iMonocytes recapitulate the phenotype and function of primary monocytes. (FIG. 1A) Live / dead staining of iMonocytes at day 1, 3, and 7 postharvest. (FIG. IB) Flow cytometry analysis of iMonocyte phenotype, gated as CD14+ and CD16+ populations; (FIG. 1C) Function analysis of iMonocytes, assessed by their response to the TLR agonist, R848.

[0027] FIGs. 2A-2D show that serum improves in vitro mimicry of the in vivo environment in the iMonocyte assay for LNP studies. (FIGs. 2A-2B) Transfection efficiency of modified mScarlet mRNA-LNPs in media with and without serum. (FIGs. 2C-2D) Immune response of modified mScarlet mRNA-LNPs in media with and without serum.

[0028] FIGs. 3A-3D show that TLR agonist priming enhances the consistency and magnitude of immune response to LNPs. (FIGs. 3A-3B) Transfection efficiency of modified mScarlet mRNA-LNPs in media with and without R848. (FIGs. 3C-3D) Immune response of modified mScarlet mRNA-LNPs in media with and without R848.

[0029] FIGs. 4A-4D show the dose-dependent effects of R848. (FIG. 4 A) iMonocyte viability across R848 doses. (FIG. 4B) Transfection efficiency across R848 doses. (FIGs. 4C- 4D) Immune response across R848 doses.

[0030] FIG. 5 shows phagocytic activity of iMonocytes.

[0031] FIGs. 6A-6F show that long-lived iMonocytes enable kinetic studies of LNPs. (FIG. 6A) Transfection efficiency of mRNA-LNP up to 7 days post-LNP treatment. (FIG. 6B) Viability of iMonocytes on day 7 following LNP treatment. (FIGs. 6C-6F) Kinetics of the immune response in iMonocytes following treatment with LNPs up to 7 days post-LNP treatment.

[0032] FIGs. 7A-7C show that iMonocytes can also be used to evaluate the immune response triggered by the cargo. (FIGs. 7A-7C) Released cytokines from iMonocytes treated with non-immunogenic modified mScarlet mRNA-LNP and immunogenic OVA mRNA-LNP at day 3.

[0033] FIGs. 8A-8C show that repeated dosing of LNPs enhances the immune response of iMonocytes, compared with single dosing. (FIGs. 8A-8C) Released cytokines from LNP- treated iMonocytes at day 3, following single and repeated doses.

[0034] FIGs. 9A-9F show characterization of iPSCs and iPSC-Derived Monocytes. (FIGs. 9A-9B) Immunocytochemical analysis of (FIG. 9A) IP11 and (FIG. 9B) SCTi003 iPSCs, demonstrating expression of pluripotency markers Oct4, SSEA1, TRA-1-81, and Nanog. (FIGs. 9C-9D) Karyostat analysis of (FIG. 9C) IP11 and (FIG. 9D) SCTi003 iPSCs, confirming normal karyotypes with no detectable chromosomal aberrations. Whole genome

[0035] 4

[0036] #14672028vl views display copy number variations across all somatic and sex chromosomes. The smoothed signal plot (right y-axis) represents the log2 ratios of microarray probe intensities, with individual chromosome probe signals indicated by pink, green, and yellow, and normalized probe signals by blue. (FIGs. 9E-9F) Quantitative analysis of marker gene expression in iPSCs, HPSCs at day 7, and iMonocytes at day 18. Relative expression values are normalized to GAPDH. iPSC markers (gray): NANOG, OCT4; HPSC marker (pink): CD34; Monocyte markers (green): CD14, CD48, CD68, LYZ. Results are from n = 3 for each cell type.

[0037] FIGs. 10A-10E show that iPSC-derived monocytes recapitulate the phenotype and function of primary monocytes. (FIG. 10A) Schematic diagram of the differentiation procedure from iPSCs into functional monocytes. Cell morphology at each stage was also shown. (FIG. 10B) Live / dead cell viability assay of iMonocytes during the assay window at day 1, 3, and 7 post-harvest, showing consistent viability of -85% up to day 7. Statistic results were collected from 27 representative cell images at each time point. (FIG. IOC) Flow cytometry results showed -70% iPSC-derived monocytes were CD14 and CD16 double positive on day 7 post-harvest. (FIG. 10D) TNF-a release from iMonocytes following the R848 treatment (0.1 pg / mL for 16-18 hrs). Results were measured from n = 4, ***p = 0.0004. (FIG. 10E) Phagocytosis of iMonocytes stimulated by zymosan-conjugated pHrodo Green bioparticles. Co-treatment of the phagocytosis inhibitor cytochalasinD (CytoD) or the inflammation inducer LPS were also tested. Representative cell images showed phagocytosis at 24 hrs post-stimulation (left). Total integrated intensity within cell boundaries was measured hourly for 48 hrs (right). Results show mean ± SEM, n = 4. Scale bars of cell images = 200 pm.

[0038] FIGs. 11A-11B show LNP formulation characterizations. (FIG. 11 A) Particle size distribution and mRNA encapsulation efficiency of the tested LNPs. (FIG. 1 IB) cryo-TEM images of different LNP formulations. Scale bar in cryo-TEM images, 100 nm.

[0039] FIGs. 12A-12F show R848 priming enhances the consistency and magnitude of inflammatory responses to mRNA-LNPs in iMonocytes. (FIGs. 12A-12B) R848 dose titration in iMonocytes prior to mRNA-LNP treatment. Cytokine secretion was measured in conditioned media on day 3 after LNP treatment. (FIGs. 12C-12F) Dose-response analysis of mRNA-LNPs in iMonocytes. Cell viability (FIG. 12D) and cytokines (FIGs. 12D-12F) were evaluated on day 3 following mRNA-LNP treatment. Cells primed with 0.1 pg / mL R848 but without mRNA-LNP treatment served as control. Results represent mean ± SEM, n = 3.

[0040] 5

[0041] #14672028vl FIG. 13 shows mRNA translation efficiency delivered by different LNPs in iMonocytes. Fold changes of transfection efficiency of SM102 and Lipid 20 mRNA-LNPs in iMonocytes pre-treated with varying doses of R848 (0-8 pg / mL), followed by treatment with 2 pg / mL mScarlet mRNA-LNPs. Transfection efficiency was assessed on day 3 by Incucyte imaging of mScarlet fluorescence and normalized by individual LNP type. Results represent mean ± SEM, n = 3.

[0042] FIG. 14 shows kinetics of cytokine secretion from iMonocytes. IL-la and IL-ip levels in iMonocytes from day 0 to day 7 after treatment with SM102 and Lipid 20. All LNP- treated groups were pre-treated with 0.1 pg / mL R848. Data represent mean ± SEM, n = 3.

[0043] FIG. 15 shows R848 dose titration in primary cells. PBMCs and monocytes were pretreated with different doses of R848, followed by 2 pg / mL LNP treatment for 3 days, and measured for secretion of IL-1 cytokines. Results represent mean ± SEM, n = 3.

[0044] FIGs. 16A-16F show that the iMonocyte platform improved rank ordering of LNP - induced innate immune responses over primary PBMC and monocyte platforms. (FIG. 16A) Cell line preparation schemes for different assay platforms. (FIG. 16B) Heatmap of fold changes of LNP-induced cytokines in cell culture supernatants, relative to the R848-alone control. Primary cell lines were tested with two donors (PBMCs and monocytes are from the same donor), and iMonocyte was tested with two sources. Scale bar is adjusted according to different cytokine response range, with the R848 control group is always set as 1. (FIG. 16C) Visualization panel (FIG. 16B) data in radar plots. (FIGs. 16D-16F) Effect size analysis of cytokine responses for each LNP across different in vitro cell models and donors. For iMonocytes, donor 1 represents the IP 11 line and donor 2 represents the SCTi003 line.

[0045] FIG. 17 shows a heatmap of cytokine fold change values corresponding to the heatmap shown in FIG. 16B. Primary cells (PBMCs and monocytes) and iMonocytes were tested with two donors or sources. For iMonocytes, donor 1 represents the IP 11 line and donor 2 represents the SCTi003 line.

[0046] FIG. 18 shows mRNA expression kinetics and viability of iMonocytes. iMonocytes were primed with 0.1 pg / mL R848 followed by 2 pg / mL mRNA-LNP treatment. Kinetics of mRNA expression was monitored by mScarlet fluorescence intensity within 5 days post LNP treatment. Cell viability was measured at day 7 post LNP treatment. Data represent mean ± SEM, n = 3.

[0047] FIGs. 19A-19F show that the iMonocyte platform captures rank ordering of LNP- induced innate immune responses in vivo. (FIG. 19 A) Experimental workflow for measuring in vivo cytokine response to LNPs. C57BL / 6 mice (6-8 weeks old) were intramuscularly 6

[0048] #14672028vl injected with 0.15 mg / kg mRNA-LNPs, and blood plasma was collected at 6 hours postinjection for cytokine analysis by Luminex. (FIG. 19B) Heatmap of in vivo cytokine fold changes relative to the PBS control. (FIGs. 19C-19F) Correlations of effect sizes between in vivo and in vitro cytokine responses. iMonocyte results strongly correlated with in vivo results, whereas primary cells showed weak correlations.

[0049] FIG. 20 shows a heatmap of cytokine fold change values corresponding to the heatmap shown in FIG. 19B.

[0050] FIGs. 21A-21I show that RNA-seq of R848 / LNP -treated iMonocytes reveals common up-regulation and down-regulation pathways. (FIG. 21 A) Principal component analysis (PC A) of gene expression profiles of biological replicates from different LNP treatment groups. (FIG. 2 IB) Volcano plots of differential gene expression profiles from the three mRNA-LNPs. Red and blue represent differentially expressed genes (DEGs; |Log2FC| > 1 & FDR < 0.05) with increased or decreased expression, respectively. Total numbers of DEGs for each direction are also indicated. (FIG. 21C) Heatmap of the Z-scores of log2CPM gene expression values from the biological replicates for all of the DEGs. (FIG. 2 ID) UpSet plot of the intersections between the DEGs with increased (red) or decreased (blue) expression. (FIG. 2 IE) Gene set scores (mean log2CPM) of the DEGs with a shared direction of change across the three LNPs, split by direction. (FIG. 2 IF) Enriched Gene Ontology (GO) categories (based on biological process and molecular function) and Reactome pathway terms for the shared genes with increased expression. (FIGs. 21G-21I) Gene set scores of the top up-regulated Reactome pathways from different LNP treatments, where asterisks indicate a significant (FDR < 0.05) difference when compared to R848 alone control.

[0051] FIG. 22 shows a heatmap of the Z-scores of log2CPM gene expression values from the biological replicates for the detected genes from the Reactome interferon a / p signaling pathway.

[0052] FIGs. 23A-23C show that the iMonocyte platform differentiates lipid- and mRNA- induced cytokine responses. (FIG. 23 A) Transfection efficiency of NlpsU-modified versus unmodified mRNA delivered via LNPs containing different ionizable lipids (SM102, MC3, Lipid 20, CKK-E12). (FIGs. 23B-23C) Cytokine secretion profiles of IL-ip (FIG. 23B), and IL-6 (FIG. 23 C) following 72 hr-treatment of LNPs containing different ionizable lipids and loaded with either the modified or unmodified mRNA. Results represent mean ± SEM, n = 3. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, as analyzed by two-way ANOVA followed by a test for multiple comparisons.

[0053] 7

[0054] #14672028vl FIGs. 24A-24C show cytokine responses in iMonocytes treated with unmodified OVA mRNA-LNPs. Cytokine secretion profiles of IL-ip (FIG. 24A), IL-6 (FIG. 24B), and IP-10 / CXCL10 (FIG. 24C) following 72 hr-treatment of different mRNA-LNPs. Results are compared with those induced by the modified mScarlet mRNA-LNPs, and represent mean ± SEM, n = 3. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 as analyzed by two-way ANOVA for multiple comparisons.

[0055] FIGs. 25A-25B show that the iMonocyte platform enables evaluation of innate immune responses under different LNP-dosing regimens. (FIG. 25A) Experimental design for in vitro dosing regimen analysis. iMonocytes were treated with NlpsU-modified mScarlet mRNA-LNPs formulated with different ionizable lipids (SMI 02, MC3, Lipid 20, and CKK- E12) using three dosing strategies: single dosing (1 pg / mL on day 0), split dosing (0.5 pg / mL on day 0 and 0.5 pg / mL on day 1), and repeated dosing (1 pg / mL on day 0 and 1 pg / mL on day 1). (FIG. 25B) Cytokine levels (IL-6, IP-10 / CXCL10, and IL-ip) in conditioned media were measured on day 3 post-treatment using Luminex assay. Data represent mean ± SEM, n = 3 biological replicates. Statistical significance was determined by ordinary one-way ANOVA: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

[0056] DETAILED DESCRIPTION

[0057] Lipid compositions, such as lipid nanoparticles (LNPs), are used for various medical applications, and there is a need for robust, consistent methods to assess immune response to such lipid compositions. Conventional methods use peripheral blood mononuclear cells (PBMCs) to test the immune response to LNPs, for example; however, these methods are not scalable or translational. The iMonocytes provided herein are patient derived and clinically translational, can be scaled up, and are genetically modifiable. Thus, the technology of the disclosure relates to methods for using iMonocytes to assess immune responses to lipid compositions, such as LNPs and / or liposomes.

[0058] In some aspects, the present disclosure describes methods for assessing an immune response to (immunogenicity of) a lipid composition. For example, a method herein can include (a) combining monocytes derived from induced pluripotent stem cells or other progenitor cells (referred to herein as “iMonocytes”) and a lipid composition and (b) assessing the iMonocytes for an immune response to the lipid composition.

[0059] An “immune response” herein includes a cellular reaction to a lipid composition, which can include the production, expression, and / or secretion (e.g., by iMonocytes) of a marker of immune activation, for example, selected from cytokines, chemokines, reactive 8

[0060] #14672028vl oxygen species (ROS), nitric oxide (NO), pro-inflammatory lipid mediators, complement proteins, growth factors, and soluble immune checkpoint proteins.

[0061] Induced Pluripotent Stem Cells and iMonocytes

[0062] The methods herein, in some aspects, use induced pluripotent stem cells (iPSCs) to produce monocytes, which are then used to assess an immune response to a lipid composition. iPSCs can include non-naturally occurring pluripotent stem cells that can be generated directly from somatic cells. iPSCs are typically produced by introducing a specific set of pluripotency-associated genes, or “reprogramming factors,” into an adult cell type. Through the reprogramming process, somatic cells enter an embryonic-like pluripotent state that enables the development of other cell types. The original set of reprogramming factors (also called Yamanaka factors) are the genes Oct4 (Pou5fl), Sox2, cMyc, and Klf4. There are multiple methods to generate iPSCs, including retrovirus or lentivirus-mediated gene transduction and chemical induction. In some embodiments, iPSCs are generated in the cell culture platform / system.

[0063] In some embodiments, the somatic cells used to produce iPSCs can be obtained from a patient, for example, to tailor a treatment to the patient. In some embodiments, the somatic cells obtained from a patient include blood cells. In some embodiments, the somatic cells obtained from a patient include skin cells.

[0064] Directed Differentiation of human PSCs into iMonocyte

[0065] In some aspects of the disclosure, iPSCs are programmed to differentiate into iMonocytes. Monocyte includes a type of white blood cell that plays a role in the innate immune system. The term “iMonocytes” refers to a monocyte that has been artificially differentiated, for example, from iPSCs “iPSC-derived monocyte” or other progenitor cells, in vitro. iMonocytes are not primary monocytes — that is, iMonocytes are not monocytes produced in vivo by bone marrow. The process of generating iMonocytes, in some embodiments, includes first differentiating iPSCs into hematopoietic cells, and then further differentiating the hematopoietic cells into monocytes.

[0066] In some embodiments, iMonocytes are generated from iPSCs or other progenitor cells using a commercially available kit, such as the STEMdiff™ Monocyte Kit (StemCell Technologies, #05320), for example, with or without modifications to the manufacturer's instructions. In some embodiments, iPSCs or other progenitor cells are plated at about 50% to 90% confluency. For example, PSCs or other progenitor cells can be plated at about 50%, 9

[0067] #14672028vl about 60%, about 70%, about 80%, or about 90%confluency. In some embodiments, iPSCs or other progenitor cells are plated at about 80% confluency. When the cells reached the desired confluency, they can then be dissociated, for example, using a commercially available reagent, such as the Gentle Cell Dissociation Reagent (StemCell Technologies, #100-0485), and filtered (e.g., through a reversible filter, e.g., a 37 pm reversible filter) to remove single cells. The cell aggregates can then be plated, for example, on a Matrigel®-coated substrate, and incubated (e.g., overnight at ~37°C). The cells can then be maintained for several days in hematopoietic culture medium, for example, followed by maintenance in differentiation medium, with or without serum (e.g., 10% fetal bovine serum). The purity of the iMonocyte population can be assessed, for example, by flow cytometry and / or quantitative PCR. iMonocytes of the disclosure, in some embodiments, express CD14 and / or CD16, recapitulating the phenotype of primary monocytes. For example, in any given population of iMonocytes derived from iPSC, at least 10%, at least 20%, at least 25%, or at least 30% of the iMonocytes express CD14 (are CD14+), and / or at least 10%, at least 20%, at least 25%, at least 30%, at least 35%, or at least 40% of the iMonocytes express CD16 (are CD16+). iMonocytes of the disclosure, in some embodiments, secrete TNF-a, for example, in response to exposure to a TLR agonist (e.g., a TLR 7 / 8 agonist, such as R848), recapitulating the phenotype of primary monocytes. For example, iMonocytes treated with about 0.1 pg / mL of R484 and incubated for about 16-18 hours may secrete about 5,000 pg / mL to about 15,000 pg / mL, in some instances, about 10,000 pg / mL TNF-a.

[0068] Lipid Compositions

[0069] Methods of the disclosure, in some aspects, are used to assess an immune response to a lipid composition. A lipid composition can include any composition comprising a (one or more) lipid. Non-limiting examples of lipid compositions include micelles, nanostructured lipid carriers, lipid polymer hybrid nanoparticle, lipid nanoemulsions, lipid nanoparticles, and liposomes. In some embodiments, a lipid composition comprises a micelle, which can include a spherical structure that forms in water by the aggregation of surfactant molecules. In some embodiments, a lipid composition comprises a nanostructured lipid carrier, which can include a formulation that is composed of physiological and biocompatible lipids, surfactants, and cosurfactants. In some embodiments, a lipid composition comprises a lipid polymer hybrid nanoparticle, which can include a polymer core enveloped by a lipid bilayer. In some embodiments, a lipid composition comprises a lipid nanoemulsion, which can include an oil in water dispersion resulting in a nanodroplet. In some embodiments, a lipid composition

[0070] 10

[0071] #14672028vl comprises a liposome, which can include a small, spherical vesicle comprising a phospholipid bilayer that can encapsulate an aqueous phase.

[0072] Lipid Nanoparticles (LNPs)

[0073] In some aspects of the present disclosure, a lipid composition comprises a lipid nanoparticle. Lipid nanoparticles are often used as delivery systems for certain cargo, such as therapeutic agents, including mRNA vaccines. In vivo, LNPs generally protect the cargo from enzymatic degradation and destruction by the immune system before the cargo reaches its intended target (e.g., target cell), and in some instances, enhance the effectiveness of the cargo. Lipid nanoparticles typically include four lipid types, for example, ionizable lipids, phospholipids, cholesterol, and polyethylene glycol (PEG) lipids. The ionizable lipid includes a tertiary amine structure that enables the encapsulation of cargo, such as RNA, and facilitates the transport of RNA to the cytoplasm of a cell. Phospholipids and cholesterol play a role in stabilizing the LNPs and aiding endosomal escape. PEG lipids enhance the half-life of LNPs, thereby prolonging their circulation time in the body.

[0074] Cargo Molecules

[0075] The methods herein are used to assess an immune response to one or more lipid compositions, which, in some embodiments, comprises a cargo molecule, such as a therapeutic cargo molecule. A cargo molecule can include any chemical or biological molecule. A therapeutic cargo molecule can include a chemical or biological molecule that is delivered to a subject to yield a beneficial therapeutic result. Non-limiting examples of therapeutic cargo molecules include small molecule drugs, therapeutic proteins, therapeutic nucleic acids, or other biologically active compounds.

[0076] A small molecule drug can include a chemically synthesized, low molecular weight compounds, typically under 900 Daltons, which is used to treat or prevent disease in a subject. Small molecule drugs work by modulating the activity of biological targets such as receptors or enzymes. Non-limiting examples of small molecule drug classes include analgesics, antidepressants, antibiotics, antivirals, chemotherapeutics, immunosuppressants, antihypertensive drugs, anticoagulants, statins, antidiabetic drugs, respiratory drugs, and gastrointestinal drugs. In some embodiments the therapeutic cargo molecule is a small molecule.

[0077] Therapeutic proteins can include biologically synthesized protein molecules used to treat or prevent disease in a subject. Non-limiting examples of therapeutic proteins include antibodies, antibody fragments, recombinant proteins, fusion proteins, enzymes, hormones, cytokines, growth factors, and antivenoms. In some cases, therapeutic proteins include 11

[0078] #14672028vl synthetic peptides that are chemically synthesized amino acid polymers. Therapeutic proteins can have applications in various disease classes including cancer, autoimmune disease, genetic disorders, and infectious diseases. In some embodiments the therapeutic cargo molecule is a therapeutic protein.

[0079] A therapeutic nucleic acid can include a nucleic acid molecule (DNA or RNA) used to treat or prevent disease in a subject. Non-limiting examples of therapeutic nucleic acids include messenger RNA (mRNA), short interfering RNA (siRNA), microRNA (miRNA), guide RNA (gRNA), circular RNA (circRNA), and self-amplifying messenger RNA (samRNA). In some embodiments, a lipid composition comprises mRNA as the therapeutic cargo molecule. In some embodiments, an mRNA encodes an antibody. In some embodiments, an mRNA encodes an antigen (e.g., a vaccine antigen).

[0080] In some embodiments, a therapeutic cargo includes gene editing molecules and / or nucleic acids encoding gene editing molecules. Non-limiting examples of gene editing molecules include nucleases, base editors, or prime editors, and RNA-targeting systems, such as CRISPR-Cas systems (e.g., one or more gRNA and Cas enzyme).

[0081] Other types of therapeutic cargo molecules can include biologically active compounds comprising, for example, a combination of one or more small molecules, one or more proteins, and / or one or more nucleic acid molecules functionally linked together. Thus, in some embodiments a therapeutic cargo molecule includes an antibody drug conjugate (ADC).

[0082] Assay Conditions

[0083] Exemplary Assay

[0084] An exemplary, non-limiting, in vitro assay for assessing an immune response to (indicative of the immunogenicity of) a lipid composition follows.

[0085] In some embodiments, iMonocytes can be generated from iPSCs. In some embodiments, these iPSCs are seeded (e.g., in a 96-well plate) at a density of about 1 x 105to 2 x 105cells per well in culture medium (e.g., RPMI-1640 or DMEM) (e.g., at 37°C in a humidified incubator). In some embodiments, the culture medium comprises fetal bovine serum (FBS) (e.g., about 5% to about 15%, optionally about 10%). In some embodiments, the culture medium comprises antibiotics (e.g., penicillin, streptomycin, etc.).

[0086] In some embodiments, the cells are treated with (combined with) a lipid composition. In some embodiments, the cells are treated with LNPs, such as serial dilutions of LNPs. In some embodiments, the cells are treated with about 0.1-100 pg / mL of the lipid composition. For example, the cells can be treated with about 1-100 pg / mL, about 10-100 pg / mL, about 12

[0087] #14672028vl 25-100 pg / mL, about 50-100, about 1-50 pg / mL, about 10-50 pg / mL, or about 25-50 pg / mL of the lipid composition. In some embodiments, the cells are treated with about 0.1 pg / mL, 1 pg / mL. 10 pg / mL, 25 pg / mL, 50 pg / mL, 75 pg / mL, or 100 pg / mL. In some embodiments, the cells are treated with multiple doses (e.g., serial dilutions) of a lipid composition. In some embodiments, the cells are treated with 2, 3, 4, 5, 6, 7, 8, 9, 10 or more doses of a lipid composition.

[0088] Positive controls, such as lipopolysaccharide (LPS) or poly(I:C), can be included to benchmark immune activation, while untreated cells or vehicle-treated cells can serve as negative controls, for example.

[0089] In some embodiments, the iMonocytes are incubated with the lipid composition for about 24 to about 48 hours (e.g., about 24, 30, 36, 42, or 48 hours), after which the supernatant can be collected for cytokine quantification. Cytokine quantification can be performed using, for example, enzyme-linked immunosorbent assays (ELISA) or a multiplex bead-based system (e.g., Luminex or MSD). Non-limiting examples of cytokines measured to evaluate immune activation include IL-1 (e.g., IL-1 alpha, IL-1 beta), IL- la, IL-ip, IL-2, IL- 4, IL-6, IL-8, IL-10, IL-11, IL-12, IL-13, IL-17, IL-18, CCL3, CCL5, IFN-y, MCP-1, TNF-a, CXCL10 / IP-10, and TGF-p. In some embodiments, IL-1 alpha level is measured. In some embodiments, IL-1 beta level is measured. In some embodiments, IL-4 level is measured. In some embodiments, IL-6 level is measured. In some embodiments, CXCL10 / IP-10 level is measured. In some embodiments, TNF-a level is measured. In addition to cytokine release, immune cell activation can be assessed, for example, via flow cytometry (e.g., using fluorescently labeled antibodies) for markers such as CD80, CD86, and / or HLA-DR. Data from cytokine quantification (and optionally flow cytometry) can be analyzed to determine the level of immune activation induced by the lipid composition. This can include normalization of cytokine concentrations to untreated controls and evaluation of doseresponse relationships, for example.

[0090] Cell Culture Conditions

[0091] The methods of this disclosure, in some aspects, use induced pluripotent stem cell monocytes (iMonocytes) to assess an immune response to lipid compositions in cell culture medium. Cell culture medium can include a liquid, solid, or semi-solid containing the necessary ingredients to support cellular proliferation, differentiation, and / or maintenance. Non-limiting examples of the reagents that can be found in cell culture medium include water, salt, carbon sources, serums, and other plant, animal, or yeast extracts.

[0092] 13

[0093] #14672028vl Cell culture medium used for iMonocyte differentiation from iPSCs is distinct from cell culture medium used when assaying for an immune response to a lipid composition. In some embodiments, differentiation medium is serum-free, whereas culture medium used to assess lipid immunogenicity can include serum, such as fetal bovine serum. The data provided herein demonstrates that the inclusion of serum in the iMonocyte assay enhances in vitro mimicry of the in vivo environment for lipid studies.

[0094] Serums can include undefined and complex mixtures derived from animal sources that can include proteins, hormones, growth factors, amino acids, lipids, and other bioactive molecules. Serums can support growth and viability in mammalian cell lines, including primary cells, and the inclusion of serum in the cell culture medium of iMonocytes can create an environment in vitro that more closely mimics an in vivo environment. In some embodiments, the cell culture medium comprises serum. In some embodiments, the concentration of serum in cell culture medium is at least 5%, at least 10%, or at least 15%. In some embodiments, the concentration of serum in cell culture medium is about 5% to about 15%, about 5% to about 10%, or about 10% to about 15%. In some embodiments, the concentration of serum in cell culture medium is about 5%, about 10%, about 15 %, or about 20%. In some embodiments, the concentration of serum in cell culture medium is 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, or 20%. In some embodiments, the concentration of serum in cell culture medium is between 5-15%.

[0095] Non-limiting examples of serums include fetal bovine serum (FBS), newborn caff serum (NCS), horse serum, and human serum. FBS is commonly used for mammalian cell culturing and can include nutrient rich supplemental material obtained from fetuses of cows that can contain vitamins, minerals, albumin, globulins, fibronectin, transferrin, growth factors, hormones, antibodies, lipids, and other nutrients that support cell proliferation and cell viability. In some embodiments, the methods described herein use cell culture medium comprising FBS. Human serum can include nutrient rich supplemental material obtained from human blood that is used to support proliferation and viability of human cell cultures. Human serum can contain vitamins, minerals, glucose, albumin, fibronectin, transferrin, complement proteins, growth factors, hormones, antibodies, lipids, and other nutrients. In some embodiments, the methods described herein use cell culture medium comprising human serum.

[0096] In some embodiments, the cell culture medium used in the methods of this disclosure comprises a Toll-like receptor (TLR) agonist. TLRs include a class of pattern recognition receptor (PRR) proteins (often transmembrane proteins with leucine-rich repeats on the 14

[0097] #14672028vl surface of immune cells) that play a critical role in the innate immune system by recognizing TLR agonists. TLRs can be found on the surface of dendritic cells, macrophages, and monocytes, including iMonocytes. Non-limiting examples of TLRs include TLR1, TLR2, TLR3, TLR4, TLR5, TLR7, and TLR9, which each recognize specific TLR agonists. TLR agonists can include molecules that activate a particular TLR and thus trigger the receptor’s downstream signaling pathway and initiate an immune response. Non-limiting examples of TLR agonists include pathogen-associated molecular patterns (PAMPs) such as lipopolysaccharide (LPS), peptidoglycan, flagellin, viral RNA, unmethylated CpG DNA from bacteria and viruses; and damage-associated molecular patterns (DAMPs), which include intracellular (nuclear, mitochondrial, cytosolic) proteins that are released into extracellular space following tissue injury and molecules from the extracellular space and plasma membrane. TLR agonists also can include imidazoquinoline compounds, adenine compounds, benzazepine compounds, guanosine compounds, thiazoquinoline compounds, nucleic acid derivatives (e.g., CpG-ODNs, Poly I, ssRNA), nucleoside analogs, and synthetic small molecules. In some embodiments, the TLR agonist is selected from imidazoquinoline compounds, adenine compounds, benzazepine compounds, flagellin, guanosine compounds, thiazoquinoline compounds, lipopolysaccharides, nucleic acid derivatives (e.g., CpG-ODNs, Poly I, ssRNA), nucleoside analogs, and synthetic small molecules.

[0098] Imidazoquinoline compounds include a class of synthetic molecules known to target TLR7 or TLR8 and trigger an immune response involving pro-inflammatory cytokines such as interleukins, TNF-a, and IFN-a. Imidazoquinoline compounds can also be used in immunotherapies, vaccines, and treatments for viral infections due to their ability to induce an immune response. In some embodiments, the TLR agonist is selected from imidazoquinoline compounds. Non-limiting examples of imidazoquinoline compounds include resiquimod (R848), imiquimod, gardiquimod, dactolisib, and sumanirole. In some embodiments, the imidazoquinoline compounds are selected from resiquimod (R848), imiquimod, gardiquimod, dactolisib, and sumanirole. In some embodiments, the imidazoquinoline compound is resiquimod.

[0099] In some embodiments, the concentration of resiquimod is at least 0.01 pg / mL (e.g., 0.02 pg / mL, 0.03 pg / mL, 0.04 pg / mL, or 0.05 pg / mL). In some embodiments, the concentration of resiquimod is at least 0.05 pg / mL (e.g., 0.06 pg / mL, 0.07 pg / mL, 0.08 pg / mL, 0.09 pg / mL, or 0.1 pg / mL). In some embodiments, the concentration of resiquimod is at least 0.1 pg / mL (e.g., 0.2 pg / mL, 0.3 pg / mL, 0.4 pg / mL, or 0.5 pg / mL). In some embodiments, the concentration of resiquimod is at least 0.5 pg / mL (e.g., 0.6 pg / mL, 0.7 15

[0100] #14672028vl qg / mL, 0.8 qg / mL, 0.9 qg / mL, or 1.0 qg / mL). In some embodiments, the concentration of resiquimod is at least 1 qg / mL (e.g., 2 qg / mL, 3 qg / mL, 4 qg / mL, or 5 qg / mL). In some embodiments, the concentration of resiquimod is at least 5 qg / mL (e.g., 6 qg / mL, 7 qg / mL, 8 qg / mL, 9 qg / mL, or lOqg / mL). In some embodiments, the concentration of resiquimod in the cell culture medium is about 0.05 qg / mL to 0.1 qg / mL.

[0101] Assessing Immune Response

[0102] The methods herein for assessing an immune response to lipid compositions in iMonocytes, in some aspects, involves assessing the iMonocytes for an immune response. In some embodiments, assessing the iMonocytes for an immune response comprises assessing cell viability. Assessing cell viability can include using live / dead cell staining to quantify the percent of viable cells in a sample. This assessment can be done, for example, using commercially available cell viability kits, such as the LIVE / DEAD® Viability / Cytotoxicity Kit for mammalian cells (ThermoFisher #L37601). In some embodiments, a cell-permeant dye, such as calcein AM, is used to detect live cells, for example, via microscopy or flow cytometry. In some embodiments, a cell-impermeant dye, such as BOBO-3 iodide, is used to detect dead cells, for example, via microscopy or flow cytometry.

[0103] In some embodiments, assessing the iMonocytes for an immune response comprises assessing cell proliferation. Assessing cell proliferation can include measuring a change in the quantity of a cell population over time. In some embodiments, assessing the iMonocytes for an immune response comprises assessing influx of calcium of the iMonocytes. Assessing influx of calcium of the iMonocytes can include treating cells with fluorescent calcium indicators and measuring the change in fluorescence intensity via fluorescent microscopy.

[0104] In some embodiments, assessing the iMonocytes for an immune response comprises assaying for markers of immune activation. Assaying includes a using method of measuring the presence, amount, or activity of a substance in a sample. Thus, the methods herein use a measure the presence, amount, or activity of markers of immune activation in iMonocytes that have been combined with a lipid composition. In some aspects of the disclosure, an immune response is assessed by measuring immune marker secretion.

[0105] A marker of immune activation can include a molecule or biomarker that indicates the activation or response of the immune system to stimuli, such as infection, injury, or the presence of cancer cells. These markers can include proteins whose expression or concentration changes in response to immune system activation. Markers of immune activation can be used to assess the level of immune activity, the type of immune response (e.g., innate or adaptive), and the presence of inflammation or disease. Non-limiting

[0106] 16

[0107] #14672028vl examples of markers of immune activation include reactive oxygen species (ROS), nitric oxide (NO), pro-inflammatory lipid mediators, complement proteins, growth factors, soluble immune checkpoint proteins, cytokines, and chemokines.

[0108] In some embodiments, a marker of immune activation is a reactive oxygen species (ROS). ROS include highly reactive molecules that contain oxygen produced as a natural bioproduct of cellular metabolism and can play a role in immune defenses or oxidative stress. In some embodiments, a marker of immune activation is a nitric oxide (NO). NO includes a gaseous signaling molecule involved in immune responses and inflammation as a defense against pathogens. In some embodiments, a marker of immune activation is a pro- inflammatory lipid mediator. A pro-inflammatory lipid mediator includes a bioactive molecule derived from lipids that promote inflammation in response to injury, infection, or disease. In some embodiments, a marker of immune activation is a complement protein. Complement proteins include proteins involved in the complement cascade pathway of the immune system. In some embodiments, a marker of immune activation is a growth factor. A growth factor includes a signaling protein or peptide that stimulates growth, development, and differentiation of cells and call also regulate cellular processes including cell division, tissue repair, and immune responses. In some embodiments, a marker of immune activation is a soluble immune checkpoint protein. A soluble immune checkpoint protein includes a type of immune regulatory protein that circulates in the body in a soluble (non-membrane bound) form and regulate immune cell activity.

[0109] In some embodiments, a marker of immune activation is a cytokine. A cytokine includes a small, secreted protein or peptide that acts as a signaling molecule to regulate immune responses, inflammation, and other cellular activities. In some embodiments, a marker of immune activation is a chemokine. A chemokine includes a small, secreted protein or peptide that acts as a signaling molecule to regulate immune cell migration and activation. Non-limiting examples of cytokines and chemokines include IL-1, IL- la, IL-ip, IL-2, IL-4, IL-6, IL-8, IL-10, IL-11, IL-12, IL-13, IL-17, IL-18, CCL3, CCL5, IFN-y, MCP-1, TNF-a, CXCL10 / IP-10, and TGF-p.

[0110] All references, patents and patent applications disclosed herein are incorporated by reference with respect to the subject matter for which each is cited, which in some cases may encompass the entirety of the document.

[0111] The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”

[0112] 17

[0113] #14672028vl It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

[0114] In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of’ and “consisting essentially of’ shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03.

[0115] The terms “about” and “substantially” preceding a numerical value mean ±10% of the recited numerical value.

[0116] Where a range of values is provided, each value between and including the upper and lower ends of the range are specifically contemplated and described herein.

[0117] EXAMPLES

[0118] The following Examples are provided to illustrate certain embodiments of the technology and to facilitate an understanding of the disclosed compositions and methods. These Examples are not intended to be limiting, and the data, results, and interpretations described herein represent specific implementations that merely exemplify the broader concepts of the technology. Variations in materials, experimental conditions, analytical methods, and biological systems may be made. The Examples are offered solely to demonstrate the workability and representative performance of select embodiments.

[0119] Example 1: iMonocytes recapitulate the phenotype and function of primary monocytes

[0120] Live / dead staining was of iMonocytes was done at days 1, 3, and 7 post-harvest using the LIVE / DEAD® Viability / Cytotoxicity Kit for mammalian cells (ThermoFisher #L37601) according to the manufacturer’s protocol. Calcein AM, a cell-permeant dye, stains live cells green. BOBO-3 iodide, a cell-impermeant dye, stains dead cells with compromised membranes red. iPSC-derived monocytes (iMonocytes) were incubated with 2X dye solution for 15 minutes at 20-25°C and imaged via Incucyte. Over 7 days, no significant cell death was observed despite cell accumulation (FIG. 1A). This confirms the suitability of these cells for long-term LNP treatment and screening.

[0121] 18

[0122] #14672028vl CD14 and CD16 are markers of monocytes. iPSC-derived monocytes (iMonocytes) at differentiation day 28 were stained with BB700 anti-human CD14 antibody and PE antihuman CD16 antibody and analyzed via flow cytometry. Approximately 30% of cells were CD14+. Approximately 40% of cells were CD16+ (FIGs. 1B-1C). The expression of CD14 and CD 16 indicates that iMonocytes recapitulate the phenotype and function of primary monocytes.

[0123] The iMonocytes were further evaluated based on their response to the TLR agonist R848. IMonocytes were treated with 0.1 pg / mL R848 and incubated for 16-18 hours. Supernatants were collected and an ELISA assay was used to measure the concentration of secreted TNF-a (FIG. ID). iMonocytes to the TLR7 / 8 agonist R848 by secreting TNF-a, thus recapitulating another functional characteristic of primary monocytes.

[0124] Together, these data confirm that iMonocytes are suitable as a model for immune response studies.

[0125] Example 2: iMonocyte assay development. iMonocytes were treated with modified mScarlet mRNA-LNPs either with or without 10% fetal bovine serum (FBS) albumin. Two LNPs, LNP1 and LNP2, were tested, and PBS treatment was used as a control. 3 days after treatment with the LNPs, the transfection efficiency of the mRNA was evaluated (which indicates LNP delivery efficiency) using the fluorescence intensity of mScarlet measured via Incucyte imaging (Ex / Em 569 nm / 594 nm) (FIG. 2A). Fluorescence images were used to quantify transfection efficiency, which was determined as the fluorescence intensity divided by the total number of cells (FIG. 2B). These results illustrate that use of the serum improves transfection efficiency. The concentration of secreted cytokines (IL-ip or IL-4) was measured in the supernatant to determine the immune response of the iMonocytes in response to the LNPs with or without serum (FIGs. 2C-2D) Inclusion of serum in the iMonocyte assay creates an in vitro condition that more closely mimics the in vivo environment. Including serum results in a stronger immune response elicited by the mRNA-LNPs, thus these results highlight the importance of developing assay conditions for evaluating lipid nanoparticle performance in a more biologically relevant context. iMonocytes were tested in cell culture medium containing serum either with or without 0.1 pg / mL R848 (a TLR7 / 8 agonist) plus a modified mScarlet mRNA-LNP (either LNP1 or LNP2). Two LNPs were tested, and PBS treatment was used as a control. 3 days after treatment with the LNPs, the transfection efficiency of the mRNA was evaluated using 19

[0126] #14672028vl the fluorescence intensity of mScarlet measured via Incucyte imaging (Ex / Em 569 nm / 594 nm) (FIG. 3A). Fluorescence images were used to quantify transfection efficiency, which was determined as the fluorescence intensity divided by the total number of cells (FIG. 3B). These results illustrate that priming with R848 slightly reduces transfection efficiency. The concentration of secreted cytokines (IL-ip or IL-6) was measured in the supernatant to determine the immune response of the iMonocytes in response to the LNPs with or without R848 (FIGs. 3C-3D). R848 priming results in a stronger immune response elicited by the mRNA-LNPs. TLR agonist priming is crucial for the iMonocyte-based in vitro assay to evaluate LNP-induced immune responses, as it significantly improves the consistency and magnitude of the observed responses.

[0127] Several concentrations of R848, ranging from 0-5 pg / mL, were tested to determine the concentration for assessing LNP immunogenicity with the iMonocyte assay. Two modified mScarlet mRNA-LNPs (LNP2 or LNP3) were tested, and R848 without an LNP was used as a control. Cell viability at day 7, measured relative to the 0 pg / mL R848 condition, was consistent at all concentrations of R848 (FIG. 4A). Lower transfection efficiency was associated with higher concentrations of R848 (FIG. 4B). The concentration of secreted cytokines (IL- la or IL- 1 P) was measured in the supernatant to determine the elicited immune response of the LNPs at various R848 concentrations (FIGs. 4C-4D). Higher cytokine concentrations were associated with higher concentrations of R848. These results indicate that R848 has a dose-dependent effect on LNP-mediated activation of iMonocytes, and the dose of R848 for sensitizing iMonocytes is -0.05-0.1 pg / mL. This range of concentrations does not affect cell viability (FIG. 4A), minimally impacts transfection efficiency (FIG. 4B), and significantly enhances cytokine secretion compared to untreated groups (FIGs. 4C-4D)

[0128] A phagocytosis assay was performed to confirm the function of iMonocytes. iMonocytes were treated with pHrodo Green conjugated beads under several conditions (media only, beads only, beads+serum, beads+LPS, beads+R848 0.05 pg / mL, beads+R848 1 pg / mL, beads+CytoD). Cytochalasin D (CytoD) at 10 pM, which blocks phagocytic function in iMonocytes, was used as a negative control. Results are shown in FIG. 5. Treatment with 10% FBS (serum) significantly increases phagocytosis by iMonocytes. Treatment with R848 decreases phagocytic activity in a dose-dependent manner. These data correlate with the findings of increased transfection efficiency and decreased transfection efficiency associated with FBS and R848, respectively.

[0129] 20

[0130] #14672028vl Table 1: Summary of tested LNPs.

[0131] Sample ID Theoretical Immunogenicity

[0132] LNP 1 low immunogenic LNPs

[0133] LNP 2 low immunogenic LNPs

[0134] LNP 3 medium immunogenic LNPs

[0135] LNP 5 high immunogenic LNPs

[0136] LNP 6 high immunogenic LNPs

[0137] Example 3: Comparison of current standard assays (primary cell-based assays) and iMonocyte assay.

[0138] Primary cells are currently used in the standard assays for testing the immune responses of LNPs. Primary peripheral blood mononuclear cells (PBMCs), which are derived from donor blood and include macrophages, dendritic cells, and monocytes, can be used. Alternatively, just primary monocytes can be used for these assays. In this example, PBMCs or primary monocytes were treated with an LNP + R848 (or PBS or R848 alone as controls). The concentration of secreted cytokines (IL-ip, IL-6, or IP-10 / CXCL10) was measured in response to treatment.

[0139] The results, summarized in Table 2 and Table 3, demonstrate that the standard primary cell-based assays have significant donor-to-donor variability, and the results do not consistently align with the theoretical immunogenicity of the tested LNPs.

[0140] Table 2: Fold change of released cytokines in PBMC assay.

[0141] *Presents the fold change of released cytokines, normalized to PBS control

[0142] 21

[0143] #14672028vl Table 3. Fold change of released cytokines in primary monocyte assay.

[0144] *Presents the fold change of released cytokines, normalized to PBS control

[0145] Alternatively, iMonocytes were treated under the same conditions (LNP+R848, PBS, or R848 alone). The concentration of secreted cytokines (IL- 1 P, IL-6, or IP-10 / CXCL10) was measured in response to treatment.

[0146] The results, summarized in Table 4, indicate that iMonocytes offer improved predictability compared to primary cell-based assays and that iMonocytes allow an immune response to multiple LNPs to be ranked relative to one another. In the iMonocyte assay, background signal is reduced and there is greater consistency across cytokines.

[0147] Table 4: Fold change of released cytokines in iMonocyte assay.

[0148] *Presents the fold change of released cytokines, normalized to PBS control

[0149] #14672028vl Example 4: iMonocytes enable kinetic studies of LNPs. iMonocytes were treated with multiple mRNA-LNPs, LNP1, LNP2, or LNP3. The LNPs encapsulate mRNAthat encodes modified mScarlet. The transfection efficiency of the mRNA in LNP1 and LNP2 treated cells was measured over a 7-day period and quantified as the fluorescence intensity divided by the total number of cells (FIG. 6A). The viability of the iMonocytes was measured on day 7 and is normalized to the control (FIG. 6B). The concentration of secreted cytokines (IL-la, IL-ip, IL-6, or IP-10 / CXC10) was measured in the supernatant over the 7-day period to determine the kinetics of the immune response in the iMonocytes in response to treatment with LNP2 or LNP3 (FIGs. 6C-6F). The results show that iMonocytes are viable over long (7-day) time periods, enable kinetic studies of LNPs, and show the dynamic changes in cytokine secretin and immune activation. These characteristics of iMonocytes overcome the limitations of short-lived primary monocytebased in vitro assays.

[0150] Example 5: iMonocytes assess an immune response to cargo carried by LNPs. iMonocytes were grown in cell culture medium containing serum and R848 and treated with a non-immunogenic modified mScarlet mRNA-LNP or with an immunogenic OVA mRNA-LNP. The LNP was either LNP2 or LNP3. Ovalbumin (OVA) is a member of the serpin superfamily and the predominant glycoprotein found in egg whites. It is a commonly used antigen for immunization and biochemical studies and is an established model allergen for airway hyper-responsiveness. Three days after treatment, the concentration of secreted cytokines (IL-ip, IL-6, or IP- 10 / CXC 10G) was measured in the supernatant to determine the kinetics of the immune response in the iMonocytes in response to the LNPs (FIGs. 7A-7C). This data demonstrates that iMonocytes can be utilized to evaluate the immune response triggered by the cargo of an LNP while simultaneously evaluating the immune response elicited by the LNP.

[0151] Example 6: iMonocytes can be tested with repeat dosing of LNPs. iMonocytes were grown in cell culture medium containing serum and R848 and treated with either a single dose or repeated dose of an LNP. The LNPs were chosen from LNP1, LNP2, LNP3, or LNP5. Under the single dose condition, iMonocytes were treated with 1 pg / mL of the LNP on day 0. Under the repeat dose condition, iMonocytes were treated with 0.5 pg / mL of the LNP on day 0 and 0.5 pg / mL of the LNP on day 1. PBS treatment (no R848) or R848 treatment without an LNP were used as controls. On day 3 relative to the first 23

[0152] #14672028vl or only LNP treatment (day 0) the concentration of secreted cytokines (IL- 1 P, IL-6, or IP- 10 / CXC 10) was measured in the supernatant to determine the kinetics of the immune response in the iMonocytes in response to LNP treatment (FIGs. 8A-8C). This data shows that iMonocytes provide a robust platform to investigate the effects of repeated LNP dosing, aligning closely with internal in vivo data. This also highlights the utility of iMonocytes for evaluating multi-dose strategies during the preclinical development of LNP -based therapeutics.

[0153] Materials and Methods

[0154] Materials

[0155] Lipids, including l,2-distearoyl-sn-glycero-3-phosphoethanolamine (DOPE), 1,2- dimyristoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (14:0 PEG2000 PE), and the cationic lipid l,2-di-O-octadecenyl-3-trimethylammonium propane (DOTMA), were purchased from Avanti Polar Lipids (Alabaster, AL, USA). The ionizable lipids dilinoleylmethyl-4-dimethylaminobutyrate; heptadecan-9-yl 8-((2- hydroxyethyl)(6-oxo-6-(undecyloxy)hexyl)amino)octanoate; and 3,6-bis(4-(bis(2- hydroxydodecyl)amino)butyl)piperazine-2, 5-dione were from MedChemExpress (MCE, NJ, USA), and cholesterol was sourced from Sigma-Aldrich (St. Louis, MO, USA). Lipid 20, described in US patent US 10, 221,127, was synthesized in-house. NlpsU-modified mScarlet mRNA was also synthesized in-house, while Cleancap OVA mRNA was purchased from TriLink BioTechnologies (San Diego, CA, USA). All other reagents were prepared using DNase- and RNase-free solutions. mRNA-LNP Preparation mRNA was dissolved in citrate buffer (50 mM, pH 3.0) at a concentration of 83.3 pg / mL and dispensed into a 96-well plate (Greiner Bio-One, 655101, NC, USA) at 168.75 pL per well using a robotic liquid handler (TECAN Freedom EVO, NC, USA). The organic phase consisted of ionizable or cationic lipids, DOPE, cholesterol, and C14-PEG2000 in ethanol, with a molar ratio of 50: 10:38.5: 1.5 and a total lipid concentration of 12.5 mM.

[0156] To assemble the lipid nanoparticles (LNPs), 56.5 pL of the organic lipid solution was rapidly dispensed into the mRNA-containing wells at a flow rate of 0.5 mL / s and an aqueous- to-organic phase ratio of 3: 1. The phases were thoroughly mixed using 10 cycles of aspiration and dispensing (100 pL per cycle) with the TECAN robot, facilitating the self-assembly of mRNA-loaded LNPs. The resulting mRNA-LNPs were dialyzed against phosphate-buffered 24

[0157] #14672028vl saline (PBS, pH 7.4) using a dialysis plate with a 10 kDa molecular weight cutoff (MWCO). Dialysis was performed for 2 hours at room temperature, followed by buffer change and overnight dialysis at 4°C. LNPs were also prepared using the microfluidic mixing method with the NanoAssemblr Ignite Instrument (Precision Nanosystems, BC, Canada) at standard bench scales, as previously described by Gao, et al. (Anal Bioanal Chem 416, 5281-5293 (2024)).

[0158] Physicochemical Characterization of mRNA-LNPs

[0159] Dynamic light scattering (DLS) was performed to assess particle size distributions of mRNA-loaded LNPs. Samples were diluted 10-fold in phosphate-buffered saline (PBS, pH 7.4) and analyzed in a 384-well microplate (Corning 3821BC, NY, USA) using a DynaPro Plate Reader III (Wyatt Technology, CA, USA). The mean particle diameters and particle size distributions, represented as percent poly dispersity (%PD), were determined. The concentrations of soluble and total mRNA (after extraction using 0.2% Triton X-100 in 1 x TE buffer) were measured with the Quant-iT™ RiboGreen reagent. The mRNA encapsulation efficiency (%EE) was calculated using the following formula: iP SC -monocyte (iMonocytes) differentiation

[0160] Directed Differentiation of human PSCs into iMonocyte

[0161] Hematopoietic progenitors and iMonocytes were generated from iPSCs using the STEMdiff™ Monocyte Kit (StemCell Technologies, #05320, stemcell. com / media / files / pis / 10000005536-PIS_02. pdf) according to the manufacturer's instructions, with minor modifications. Briefly, iPSCs at approximately 80% confluency were dissociated using Gentle Cell Dissociation Reagent (StemCell Technologies, #100-0485) and filtered through a 37 pm reversible filter to remove single cells. The cell aggregates were then plated in Matrigel®-coated cultureware and incubated overnight at 37°C. From Day 0 to Day 2, the cells were maintained in Hematopoietic Medium A, followed by Hematopoietic Medium B from Day 5 to Day 7. A portion of the cells was collected at this stage to characterize the hematopoietic stem cells. Subsequently, Monocyte Differentiation Medium was introduced, with medium changes every 2-3 days until Day 18-20, when monocytes were harvested as needed and the medium was supplemented with or without 10% FBS. The purity

[0162] 25

[0163] #14672028vl of the CD14+ / CD16+ monocyte population was assessed by flow cytometry, and further characterized by quantitative PCR.

[0164] Characterization of iMonocytes

[0165] Cell viability assay

[0166] Live / Dead assay was performed using the LIVE / DEAD® Viability / Cytotoxicity Kit for mammalian cells (ThermoFisher #L37601) according to the manufacturer's protocol. Calcein AM, a cell-permeant dye, stains live cells green. BOBO-3 iodide, a cell-impermeant dye, stains dead cells with compromised membranes red (Ex / Em 570 nm / 602 nm). Cells were incubated with 2X dye solution for 15 minutes at 20-25°C and imaged using Incucyte over time.

[0167] Phagocytosis assay

[0168] The uptake of pH-sensitive pHrodo dyes conjugated to zymosan A particles (P35365) by iMonocytes was assessed using high-content Incucyte imaging. Harvested iMonocytes were seeded into poly-D-lysine (PDL)-coated 96-well PhenoPlates (Perkin Elmer) at a density of 30,000 cells per well, one day prior to the phagocytosis assay. On the day of the assay, half of the cell culture medium was replaced with fresh medium containing 2x pHrodo particles, resulting in a final concentration of 10 pg / mL.

[0169] Kinetic measurements were performed using the Incucyte system at 37°C and 5% CO2. Four images per well were captured at one-hour intervals using a 20* objective. In some wells, cytochalasin D (100 ng / mL) was added as a negative control to inhibit phagocytosis. After 48 hours of imaging, the integrated intensity (GCU x pm2 / image) was calculated using Incucyte software.

[0170] Flow Cytometry

[0171] Supernatants were removed, and cells were washed twice with PBS before staining.

[0172] Viability staining was performed using Ghost Dye UV 450 (Cytek, USA) and Human TruStain FcX block (BioLegend, CA, USA) for 30 minutes at 4°C. After staining, cells were washed and resuspended in 30 pL of antibody cocktail per well. Surface marker staining was conducted for 30 minutes at 4°C using the following antibodies: BB700 anti-CD14 (M5E2) and PE anti-CD16 (3G8). All antibodies were obtained from either BD Biosciences (CA, USA) or BioLegend (CA, USA). Cells were acquired on a CytoFLEX LX 6-laser flow cytometer equipped with CytExpert Software (Beckman Coulter, CA, USA). Data analysis 26

[0173] #14672028vl was performed using FlowJo software (v.10.8.2). Dead cells were excluded based on viability dye staining, and single cells were gated using forward scatter area and height (FSC-A / FSC- H) parameters.

[0174] PBMC Isolation and Primary Monocyte Purification

[0175] Whole blood was obtained from three to six healthy human donors who voluntarily consented to participate in Genentech's Samples for Science blood donation program. The collected blood was diluted 1 : 1 with phosphate-buffered saline (PBS) and processed for peripheral blood mononuclear cell (PBMC) isolation using density gradient centrifugation (1200 x g for 15 minutes) in SepMate™ tubes (StemCell Technologies, Vancouver, Canada). Mononuclear cells were carefully collected from the plasma / Ficoll interface using a serological pipette.

[0176] The isolated PBMCs were washed with 1 x PBS and passed through a 70 pm cell strainer to remove debris. Primary monocytes were subsequently purified from the PBMCs using the Monocyte Isolation Kit (StemCell Technologies) following the manufacturer's protocol. Live cell counts were determined using a Vi-CELL BLU Cell Viability Analyzer (Beckman Coulter, Brea, CA, USA). PBMCs or monocytes were then seeded in a 96-well round-bottom plate at a density of 4 x io5cells per well or 2 x 105cells per well and cultured in RPML1640 medium supplemented with 10% fetal bovine serum (FBS), lx GlutaMAX™, 55 pM P-mercaptoethanol, 10 mM HEPES, lx non-essential amino acids, and lx sodium pyruvate.

[0177] TLR Agonist and mRNA-LNP Treatments

[0178] The TLR7 / 8 agonist R848 was used to prime induced monocytes (iMonocytes) and PBMCs. A dose titration of R848, ranging from 0.01 pg / mL to 5 pg / mL, was conducted separately on iMonocytes, PBMCs, and primary monocytes to determine the concentration. Based on these experiments, 0.1 pg / mL was selected for subsequent studies. Cells were treated with 0.1 pg / mL R848 and incubated for 2 hours at 37°C. Following incubation, cells were either washed or left unwashed before mRNA-LNP treatment. mRNA-loaded LNPs (mScarlet and / or OVA mRNA) were diluted 1 : 10 or 1 :20 in cell culture medium and added to cells at final mRNA concentrations of 1 or 2 pg / mL in a total volume of 200 pL per well. After overnight incubation and a subsequent 3-day culture, the plates were centrifuged, supernatants were collected, and cells were resuspended in FACS staining buffer (l x PBS with 2% BSA) for flow cytometry analysis. Additionally, cells were seeded 27

[0179] #14672028vl into 96-well black / clear flat-bottom plates for imaging mScarlet fluorescence (Ex / Em 569 nm / 594 nm) as a measure of mRNA transfection efficiency.

[0180] Luminex and ELISA Assays

[0181] Supernatants from LNP -treated PBMC and iMonocyte cultures were collected and stored at -80°C until cytokine measurements were performed. Treatments with 0.1 pg / mL R848 (InvivoGen, CA, USA) were used as a control. Cytokine levels were quantified using a magnetic bead-based multiplex assay for the Luminex® platform, following the manufacturer’s protocol. The Milliplex Human Cytokine Panel (Millipore, MA, USA) was used to measure a panel of cytokines, including IL-4, IL-6, IL-ip / IL-lF2, IL-la / IL-lFl, and CXCL10. Cytokine concentrations below the assay's lower limit of detection were recorded as zero.

[0182] Example 7: Predictive in vitro profiling of LNP-induced innate immune response using an iPSC-derived monocyte model.

[0183] Lipid nanoparticles (LNPs) are a powerful drug delivery platform advancing vaccines and gene therapies. While their efficacy and safety has been found to be closely linked to innate immune activation, current in vitro models are unable to predict immune responses reliably. Conventional models, such as PBMCs, are limited by donor variability and inconsistent sensitivity. To address this, we developed a cytokine profiling platform using induced pluripotent stem cell (iPSC)-derived monocytes (iMonocytes), a physiologically relevant innate immune cell type that plays a key role in immune surveillance and inflammation. iPSCs provide a renewable, uniform monocyte source for consistent, high- sensitivity LNP screening. When tested with LNPs of graded immunostimulatory potency, iMonocytes showed improved reproducibility and strong correlation with in vivo cytokine responses. This platform enables evaluation of cargo- and dose-dependent effects, providing a robust and scalable tool for preclinical assessment and rational design of LNP therapeutics.

[0184] Introduction

[0185] Lipid nanoparticles (LNPs) have revolutionized the landscape of modern medicine. This versatile drug delivery platform has enabled breakthroughs in vaccines, cancer immunotherapies, and gene therapies due to its rapid design, scalable manufacturing, and ability to encapsulate diverse therapeutic cargos, particularly nucleic acids, which are traditionally challenging to be safe and effectively delivered. A critical determinant of the 28

[0186] #14672028vl success of LNP platforms lies in their interaction with the innate immune system, a doubleedged sword that presents both opportunities and challenges. For sustained efficacy of protein replacement or gene editing therapies targeting genetic disorders like cystic fibrosis, minimizing innate immune recognition is crucial to prevent unnecessary inflammation and neutralizing antibody formation. Conversely, vaccine development requires precisely tuned innate immune activation to elicit robust adaptive responses; while not triggering excessive inflammation to compromise safety and / or effectiveness. Therefore, as the LNP field rapidly advances, it becomes increasingly important to understand and control potential innate immune responses triggered by LNPs to ensure both efficacy and safety across this expanding medical landscape.

[0187] The innate immunostimulatory potential of LNPs exhibits substantial variability depending on LNP composition, including the ionizable lipids, structural lipids, PEGylation, steroid lipids, and overall physicochemical properties at the nanoparticle scale. Among these components, the synthetic, non-natural ionizable lipid serves as the primary determinant of immune modulation. Previous research demonstrated the role of ionizable lipids in mediating LNPs' adjuvant effects, demonstrating their capacity to stimulate interleukin 6 (IL-6) production from innate immune cells and subsequently drive potent germinal center B-cell and T follicular helper cell responses. This mechanistic insight was expanded by a group that demonstrated that lipid formulated nanoparticles, including LNPs, can induce cytokines such as IL-6 via inflammasome-mediated activation of interleukin 1 (IL-1). LNP -induced innate immune responses were previous studied by conducting a systematic comparison of six clinically relevant ionizable lipids (MC3, SM-102, ALC-0315, MTX Lipid 5, Compound 9, and CKK-E12). This previous work revealed differences in innate immune activation, with CKK-E12 emerging as the most potent inducer of monocyte chemoattractant protein- 1 (MCP-1), eliciting significantly higher cytokine levels at six hours post-administration compared to other lipids.

[0188] Standardized regulatory frameworks for assessing the immunostimulatory properties of LNP -based therapies remain lacking, necessitating the development of robust in vitro models for preclinical development. Primary human immune cells, such as peripheral blood mononuclear cells (PBMCs), including monocytes, are widely used to study LNP-induced innate immune responses due to their physiological relevance. However, inability to culture primary cells for prolonged time for kinetic studies and potential donor-to-donor variability compromises reproducibility; while immortalized cell lines (e.g., THP-1), though scalable, exhibit altered morphology and limited stimulus responses. To overcome these limitations, 29

[0189] #14672028vl induced pluripotent stem cell (iPSC)-derived monocytes (iMonocytes) have emerged as a promising alternative. Human iPSCs offer an unlimited self-renewal and differentiation potential, enabling the generation of genetically uniform, functionally consistent myeloid cells for disease modeling, therapeutic development, and immunostimulatory response screening.

[0190] Here, we present the development of an in vitro iMonocyte model to evaluate the innate immune responses of LNPs. We first evaluated the model performance for rank ordering several model LNPs formulated with ionizable lipids with potentially graded immunostimulatory potential: SM-102, MC3 and Lipid 20, eliciting low-to-intermediate innate immune responses; and CKK-E12, eliciting high innate immune responses. Using comprehensive cytokine profiling, a well-validated biomarker of innate immune activation, we demonstrated that iMonocytes show superior predictive value when benchmarked against conventional PBMC and primary monocyte assays. Importantly, our in vitro findings correlate strongly with in vivo cytokine data, validating the translational relevance of this platform. Beyond characterizing LNP vehicle associated cytokine release, we further showed the utility of iMonocytes for assessing cargo-dependent innate immunostimulatory properties and optimizing dosing regimens. iPSC-derived monocytes show great promise as a robust, scalable, and translational platform for screening and optimizing LNP-based therapeutics during preclinical development.

[0191] Results iMonocytes recapitulate the phenotype and function of primary monocytes

[0192] We first assessed the phenotypic feature of iMonocytes. Characterization of two human iPSC lines, IP11 and SCTi003, revealed robust expression of pluripotency markers (NANOG, OCT4, SSEA4, and TRA-1-81) as confirmed by immunofluorescence staining (FIGs. 9A-9B). Genomic integrity was further assessed via KaryoStat™ analysis, which demonstrated normal karyotypes and an absence of chromosomal aberrations in both lines (FIGs. 9C-9D). Monocytes were derived from both human iPSC lines using an adapted differentiation protocol from STEMCELL Technologies. A schematic diagram illustrates the differentiation steps from iPSCs to functional monocytes, with representative cell morphologies at each stage (FIG. 10A). During the initial 7 days, hematopoietic stem cells (HSCs) were induced, characterized by the expression of CD34 (FIGs. 9E-9F). From day 8 onwards, cells were maintained in monocyte-specific media and harvested for downstream assays between days 18 and 20. The harvested iMonocytes can be used within a week, with 30

[0193] #14672028vl consistent cell viability of -85% in this assay period (FIG. 10B). Surface markers CD14 and CD16 were analyzed in the harvested cells, with -70% being CD14+CD16+(FIG. 10C). In our optimized T175 flask differentiation format, we generated 25-30 million CD14+and CD16+iMonocytes and produced 0.3-1.2 million cells per well in a 6-well plate, demonstrating both the scalability of iMonocyte production and the flexibility of our protocol to accommodate different production scales based on experimental needs. This protocol was validated using two independent human iPSC lines.

[0194] Upon the treatment of R848, which is a Toll Like Receptor (TLR) 7 / 8 agonist, iMonocyte secreted significant levels of TNF (FIG. 10D). Further, iMonocyte also exhibited robust phagocytosis capability, as measured by the cellular uptake of pHrodo green- conjugated zymosan A particles (FIG. 10E). The phagocytosis peaked at -24 hrs, completely inhibited by cytochalasin D (phagocytosis inhibitor by blocking the actin polymerization), while not significantly affected by the acute inflammation inducer, lipopolysaccharide (LPS). Overall, these results demonstrate iMonocytes recapitulate monocyte functionality, in terms of innate cytokine secretion and phagocytosis.

[0195] R848 priming enhances the consistency and magnitude of mRNA-LNP induced immune response in iMonocytes

[0196] To evaluate the iMonocytes as an in vitro platform for assessing the immune- stimulatory responses of LNPs, a panel of representative mRNA-LNP formulations was designed to span a spectrum of innate immune activation. Specifically, Nl- m ethylpseudouridine (m l ) modified mRNA-LNPs were prepared using typical composition ratios of the ionizable lipid, cholesterol, DOPE, and DMPE-PEG2k. Four different ionizable lipids, MC3, SM102, Lipid 20, and CKK-E12, were selected to potentially provide distinct immunogenic profiles, ranging from SM102, MC3, Lipid 20 (low to moderate), to CKK-E12 (high) stimulation. SM102, MC3, and Lipid 20 mRNA-LNPs showed mean diameter -120 nm and encapsulation efficiency >95%; CKK-E12 mRNA-LNP showed slightly larger particle size (mean diameter of 138 nm) and slightly lower mRNA encapsulation (-84%) (FIG. 11 A). All four types of mRNA-LNPs showed similar morphology and the structure feature of condensed cores, as measured by cryo-TEM (FIG. 1 IB).

[0197] IL-1 plays a critical role in regulating the innate immune response of monocytes to LNP-mRNA and may modulate the secretion of additional cytokines relevant to downstream analysis. Building on our previous observation that detection of nanoparticle-induced inflammasome activation and interleukin 1 (IL-1) release is enhanced in vitro in the presence

[0198] 31

[0199] #14672028vl of signal 1 (TLR agonist such as R848, we sought to enhance the sensitivity of our iMonocyte assay by pre-treating the cells with low-dose R848. iMonocytes were pre-treated with or without R848 for 2 hours, followed by washing out and LNP treatment for 3 days, and measured for IL-1 secretion (FIGs. 12A-12B) and mRNA translation (FIG. 13). In the absence of R848, cytokine levels showed little difference between SMI 02 and Lipid 20, or between the LNPs and controls. Treatment with R848 alone led to a moderate, doseindependent IL- la and IL-ip responses. The R848 dose titration results indicated that pretreatment with a narrow dose window around 0.1 pg / mL allowed clear differentiation in IL-1 cytokine responses induced by different LNPs (FIGs. 12A-12B). Further increasing the R848 dose led to excessive immune stimulation (FIGs. 12A-12B) and significant decrease in mRNA expression (FIG. 13). After R848 priming, addition of LNPs further potentiated cytokine release in a manner dependent on both LNP type and dose, as measured by representative cytokines including IL-ip (FIG. 12D), IL-6 (FIG. 12E), and IP-10 (FIG. 12F). The LNP treatment dose was capped ~2 pg / mL of total mRNA to maintain cell viability (FIG. 12C), as well as allowing the most distinctive rank ordering of cytokine responses among different LNP types (FIGs. 12D-12F). The IL-1 cytokine responses were generally stable within day 2 to 7 after LNP treatment (FIG. 14), so that cytokine analysis at day 3 post LNP treatment represented robust rank ordering results. To establish optimal R848 concentrations across different in vitro models, we performed parallel dose titrations in primary cells, including PBMCs and monocytes (FIG. 15). These comprehensive titrations across all cellular models confirmed that an R848 dose of 0.1 pg / mL is optimal for differentiating mRNA-LNP-induced cytokine release from background noise. Based on these results, pre-treatment of 0.1 pg / mL R848 for 2 hrs, followed by 2 pg / mL LNP treatment for 3 days, was employed for the following iMonocyte assays. iMonocytes improve rank ordering of LNP-Induced innate immune responses compared to primary cell-based assays

[0200] Next, we compared different in vitro models, including primary human PBMCs and monocytes, to iMonocytes, for their performance in cytokine profiling and rank ordering of different LNPs in terms of innate immune responses (FIG. 16 A). As expected, donor-to- donor variability was observed in the primary immune cell models (FIG. 16B). Following LNP treatment, several key cytokines, including IL-6 and CCL5 (RANTES), exhibited inverse secretion patterns between donors. For instance, in PBMCs, IL-6 fold change in response to CKK-E12 was 0.9 in Donor 1 versus 1.4 in Donor 2, complicating data 32

[0201] #14672028vl interpretation (FIG. 16B and FIG. 17). CCL5 showed even greater inconsistency: for SM102, Lipid 20, and CKK-E12 LNPs, CCL5 levels increased in Donor 1 but decreased in Donor 2. Given that IL-6 and CCL5 are key mediators of innate immunity and dysregulated inflammation, accurately quantifying their induction is critical. These differences likely reflect inherent physiological variation between individuals, an expected aspect of primary cell assays. As a result, ranking LNP’s innate immune responses using primary cells across different donors can present challenges. In contrast, iMonocytes demonstrated markedly more consistent cytokine responses across donor-derived lines. While SCTi003 produced higher overall cytokine levels than IP11, both preserved the same relative response pattern across LNPs. This suggests that iMonocytes retain the immunostimulatory rank ordering of LNPs despite differences in donor background, offering a key advantage for comparative analysis.

[0202] Moreover, primary immune cells lacked sufficient sensitivity to distinguish between LNPs with weak or moderate proinflammatory responses. In radar plots, although highly stimulatory LNPs like CKK-E12 triggered robust responses detectable by PBMCs or primary monocytes, responses to “weaker” LNPs overlapped substantially. In contrast, radar plots generated from iMonocytes provided enhanced resolution, enabling clearer differentiation across the full spectrum of LNP innate immune responses (FIG. 16C). To evaluate model sensitivity quantitatively, we calculated the effect size of cytokine induction for the 3 assay platforms: PMBC (FIG. 16D), primary monocyte (FIG. 16E), and iMonocyte (FIG. 16F). This metric captures both the magnitude and consistency of cytokine responses. In primary cells, effect sizes clustered around 2.0, even for the highly immunostimulatory CKK-E12 LNP, indicating limited discriminatory power. By contrast, iMonocytes exhibited a clear, graded increase in effect size, effectively distinguishing low (SM102), intermediate (MC3, Lipid 20), and high (CKK-E12) immune-stimulatory LNPs. Notably, while SCTi003 and IP11 displayed differences in overall cytokine levels, which is a natural variation when comparing distinct iPSC lines, trends of their effect sizes were remarkably comparable. This consistency further underscores the reproducibility of the iMonocyte platform. This robust stratification highlights the strength of iMonocytes in sensitively and reliably assessing the immunostimulatory potential of LNPs across both donors and formulations.

[0203] Furthermore, PBMCs are primary immune cells with a limited lifespan ex vivo, which poses challenges for conducting longitudinal studies, such as investigating the immune response kinetics to LNPs over time or evaluating the effect of repeated dosing. By 48 hours post-isolation, PBMC populations failed to maintain normal functional parameters. In contrast, iMonocytes exhibited extended viability, with no significant cell death observed at

[0204] 33

[0205] #14672028vl day 7 post-harvest (FIG. 10B). Additionally, within the assay time window, mRNA expression reached and remained plateau from day 2 to at least day 5, while iMonocyte viability was also maintained at day 7 (FIG. 18). Furthermore, mRNA expression kinetics correlated with cytokine response kinetics as measured by IL-1 (FIG. 14). Taken together, these findings highlight the suitability of iMonocytes for kinetic studies and dosing regimens of LNPs, thereby overcoming the limitations associated with short-lived, primary cell-based in vitro assays. iMonocyte-based cytokine profiles correlate with in vivo immune responses to LNPs

[0206] To further investigate the translational value of the iMonocyte assay platform, we evaluated in vivo cytokine responses of the panel of LNPs in a murine model (FIG. 19A). Serum cytokine responses were analyzed at 6 hr after a single intramuscular (IM) injection at 0.15 mg / kg of different LNPs.

[0207] Among the tested formulations, CKK-E12 LNP elicited the most pronounced cytokine response, while SMI 02 led to only modest elevations. Cytokine levels triggered by CKK-E12 exceeded those of SM102 by approximately 3- to 20-fold across several key inflammatory mediators, including IL-6, MCP-1, G-CSF, CXCL1, IL- la, and IP- 10 (FIG. 19B and FIG. 20). Importantly, the moderately stimulatory LNPs, MC3 and Lipid 20, as classified by the iMonocyte assay, also induced stronger in vivo cytokine responses compared to SM102. This trend closely mirrored the relative immune activation profiles observed in vitro, supporting the translational relevance of iMonocytes in modeling in vivo responses.

[0208] To quantitatively assess concordance between models, we again calculated and compared the effect sizes of cytokine secretion between in vivo (normalized to the PBS control) and in vitro (normalized to the R848 control) (FIGs. 19C-19F). iMonocytes demonstrated a strong correlation with in vivo responses (R2= 0.96 for IP 11 iMonocytes and R2= 0.93 for SCTi003 iMonocytes), accurately capturing both the magnitude and rank order of LNP immunogenicity. Conversely, primary cell-based assays exhibited poor correlation (R2= 0.20 for PBMCs and R2= 0.42 for primary monocytes), highlighting their limited predictive utility.

[0209] Collectively, these findings establish the translational relevance of iMonocyte-based cytokine assays for LNPs. Within the panel of LNPs tested, the iMonocyte assay not only distinguishes their varying immunostimulatory potency in vitro but also reliably reflects in vivo cytokine response patterns, positioning it as a robust tool for preclinical innate immune response screening.

[0210] 34

[0211] #14672028vl iMonocyte transcriptomes exhibit distinct immune profiles following mRNA-LNP treatment

[0212] To mechanistically understand LNP-induced cytokine response, we further performed RNA-seq in the treated iMonocytes to examine their gene expression profiles in response to mRNA-LNPs with graded innate immune responses (SMI 02 < Lipid 20 < CKK-E12). Principal component analysis (PCA) revealed that treatment with mRNA-LNPs had a strong effect on the overall gene expression profiles, as indicated by the segregated grouping by different LNPs along the first principal component (PCI), which corresponded to the known rank ordering of immune response intensities (FIG. 21 A). Differential expression analysis showed that each mRNA-LNP formulation, in combination with R848, elicited robust profiles of differentially expressed genes (DEGs; |Log2FC| > 1 & FDR < 0.05) when compared with the R848-only control. The magnitude of transcriptional changes increased with the immune potency of the LNPs, in alignment with prior observations (FIG. 2 IB). Notably, DEGs included key cytokines such as CCL5 CXCL10 / IP10 IL IB., and I IA., which showed elevated expression levels, with high reproducibility among biological replicates within each treatment group (FIG. 21C). Analysis of shared DEGs across conditions revealed substantial overlap, with 101 genes upregulated and 60 downregulated across the SMI 02, Lipid 20 and CKK-E12 LNP formulations (FIG. 2 ID). Average gene set expression scores confirmed this trend associated with the LNP immune potency ranking, as genes with increased expression revealed progressively higher scores, while the genes with decreased expression showed a lower score (FIG. 2 IE). Gene ontology (GO) and Reactome pathway enrichment analysis of the upregulated shared DEGs highlighted functional associations with key monocyte processes, such as interferon a / p signaling and cytokine / chemokine activity, which are central to mRNA-LNP induced innate responses (FIG. 2 IF). In addition to the gene set, Reactome pathway enrichment analyses of the individual contrast ranked interferon a / p signaling, chemokine receptors bind chemokines, and interleukin- 10 signaling amongst the top significant (FDR < 0.05) pathways (data not shown). These pathways were up-regulated in all three LNP formulations and their gene set scores increased following control < SMI 02 < Lipid 20 < CKK-E12 LNPs, consistent with their rank ordering in innate immune responses assessed by the iMonocyte platform (FIGs. 21G-21I). Interestingly, enrichment of the interferon a / p signaling pathway was represented mostly by interferon-stimulated genes (ISGs), such as ISG15, IFIT1, OAS1, whereas transcripts for Type I IFN ligands (IFNA1, IFNA2, IFNB1, IFNB2) were not represented (FIG. 22).

[0213] 35

[0214] #14672028vl Overall, the transcriptomic findings align well with the cytokine data from iMonocytes, recapitulating the immune activation rank ordering of SMI 02 < Lipid 20 < CKK-E12 LNPs. Collectively, these observations reinforce iMonocytes as a robust, sensitive, and mechanistically clean platform for probing LNP-induced innate immune response.

[0215] The iMonocyte platform differentiates both lipid and mRNA cargo-induced innate immune responses

[0216] The development of mRNA-based therapeutics necessitates careful consideration of both lipid excipients and mRNA structural modifications, as these components collectively influence protein expression, innate immune activation, and therapeutic efficacy. RNA engages multiple pattern recognition receptors (PRRs), including endosomal Toll-like receptors (TLR3, TLR7, and TLR8) and cytoplasmic sensors (RIG-I and MDA-5), through their characteristic sequence motifs and secondary structures. Nucleoside modifications like m l offer an established approach to reducing PRR activation while maintaining translational efficiency.

[0217] To address this interplay, we formulated ml'P modified or unmodified mScarlet mRNA into SM102, MC3, Lipid20, and CKK-E12 LNPs, and assessed their effects on protein expression and cytokine secretion using the iMonocyte platform. Enhanced expression efficiency was observed for all modified mRNA-LNPs, except for Lipid 20, compared to their counterparts loaded with the unmodified mRNA (FIG. 23 A). This enhancement was accompanied by significantly reduced secretion of proinflammatory cytokines including IL-ip (FIG. 23B) and IL-6 (FIG. 23C), following SM102, MC3, or Lipid 20 LNP treatment. These results were consistent with the established role of ml'P in damping innate immune activation. These effects were further validated using an unmodified Ovalbumin (OVA) mRNA-LNP, which elicited markedly higher cytokine levels compared to ml'P-modified mScarlet mRNA LNPs, confirming our platform's ability to discriminate not only LNP -triggered but also innate immune responses induced by the cargo itself (FIGs. 24A- 24C).

[0218] The interplay between cargo and lipid types can produce distinct innate immune stimulation profiles. Analysis of cytokine responses elicited by modified versus unmodified mRNA revealed substantial variation across different LNPs. Notably, MC3 LNPs delivering unmodified mRNA induced significantly elevated levels, 2.5-fold higher IL-6, compared to the CKK-E12 LNP loaded with the unmodified mRNA (FIG. 23C). Furthermore, the magnitude of cytokine level changes between modified and unmodified mRNA was greater

[0219] 36

[0220] #14672028vl with MC3 than with the other two LNPs tested (SMI 02 and Lipid 20). For CKK-E12, which is already identified as a strong innate immune stimulatory lipid, switching the cargo from modified to unmodified mRNA did not further increase the cytokine responses, probably suggesting the lipid-driven responses. These differential cytokine signatures likely reflect the engagement of different levels of innate immune signaling pathways, potentially driven by the interaction between lipid species and cargo type, which may influence how cells recognize them via TLRs and other innate immune pathways.

[0221] The iMonocyte-based platform enables concurrent assessment of transfection efficiency and innate immune activation across diverse LNPs and mRNA cargos, offering a powerful tool for the rational design of next-generation mRNA therapeutics. Future applications integrating iMonocyte screening with in vivo immunization data could guide the development of mRNA-LNP formulations with optimized immune signatures, leading to the next generation therapeutic strategies.

[0222] The iMonocyte platform enables evaluation of mRNA-LNP dosing regimens.

[0223] Dosing regimens play a crucial role in the development of mRNA-LNP therapeutics, balancing therapeutic efficacy with safety and tolerability. While multiple approaches have been explored to understand the impact of dosing regimens on innate immune response, there remains an unmet need for translational in vitro models to systematically evaluate these dynamics. To address this gap, we leveraged the iMonocytes which offer a prolonged testing window, to assess cytokine responses to mRNA-LNPs under different dosing schedules and total doses. Specifically, iMonocytes were treated with ml'P-modified mScarlet mRNA- LNPs formulated with different ionizable lipids (SMI 02, MC3, Lipid 20, and CKK-E12) and three dosing strategies: single dosing (1 pg / mL on day 0), split dosing (0.5 pg / mL on day 0 and 0.5 pg / mL on day 1), and repeated dosing (1 pg / mL on day 0 and 1 pg / mL on day 1), followed by cytokine analysis on day 3 (FIG. 25A). Overall, split dosing at a total dose of 1 pg / mL led to elevated cytokine levels compared to single dosing across all LNP formulations tested (FIG. 25B). This finding aligns with published studies that split dosing elicited stronger immune responses across various vaccine platforms when delivered to multiple tissue compartments, such as skin and muscle. These results underscore the importance of the dosing schedule in stimulating an innate immune response, which potentially shapes the overall therapeutic efficacy. We further evaluated repeated dosing, a common clinical approach exemplified by COVID-19 mRNA vaccine regimens. Results showed significantly stronger cytokine responses compared to single dosing (FIG. 25B), consistent with literature 37

[0224] #14672028vl demonstrating that repeat administration enhances both innate and adaptive immune responses. Interestingly, when comparing split dosing at a total dose of 1 pg / mL to repeated dosing at a total dose of 2 pg / mL, we observed that the latter dose strategy further elevated cytokine release rather than reaching a plateau. These findings suggest that iMonocytes maintain sensitivity to dosing variations, providing a robust platform for detecting cytokine secretion patterns induced by varying dosing schedules as well as total doses.

[0225] Collectively, this study highlights the utility of the iMonocyte-based in vitro assay in screening mRNA-LNP immunostimulation from both ionizable lipids and payloads while enabling systematic evaluation of dosing regiments. This platform offers critical insights that support the rational design of preclinical studies and could potentially inform clinical strategies to optimize mRNA-LNP-based therapies for improved safety and efficacy.

[0226] Discussion

[0227] LNPs have revolutionized the landscape of mRNA-based therapeutics, establishing them as essential tools for delivering nucleic acids in vivo. However, their clinical potential hinges on the ability to precisely modulate innate immune activation. Traditional platforms employing primary cells, such as PBMCs, often suffer from variability in output and limited sensitivity, hindering reliable assessment of LNP immunostimulatory properties. In this study, we present iMonocytes as a scalable, reproducible, and physiologically relevant platform that bridges these limitations and offers a robust framework for evaluating LNP- induced innate immune responses.

[0228] The use of iPSCs to derive monocytes offers substantial benefits in LNP profiling. iPSCs offer an unlimited, renewable cell source, laying the foundation for personalized models to study immune responses across diverse genetic populations. Standardized differentiation protocols further enhance reproducibility and experimental consistency, addressing key challenges inherent to primary cell assays. While the differentiation of iPSCs into mature monocytes involves technical complexities, recent advancements in differentiation methodologies have substantially improved reliability, positioning iMonocytes as an increasingly accessible system for immunological studies. Though initial setup costs may pose a barrier, their scalability, coupled with continuous progress in functional characterization, underscores the assay’s value as the next-generation tools in immunology.

[0229] In direct comparison with PBMCs and primary monocytes, iMonocytes outperformed cellular platforms by exhibiting consistent and sensitive responses to LNP formulations. Across all tested ionizable lipids and donors, iMonocytes accurately ranked

[0230] 38

[0231] #14672028vl immunostimulatory profiles, correlating closely with in vivo cytokine signatures. This predictive capability is crucial for preclinical screening, as it facilitates the early identification of overstimulatory formulations while supporting the optimization of LNP designs. Notably, mRNA modifications, such as the ml T, reduced cytokine release in an ionizable lipid-dependent manner, unveiling complex interdependencies between the carrier vehicle and payload. These findings reinforce the necessity for integrated analysis of LNP composition and payload structure during screening approaches. Our results further demonstrated that iMonocytes enable systematic evaluation of dosing regimens, a critical component of preclinical development. Split and repeated dosing strategies enhanced cytokine responses compared to single dosing, aligning with in vivo and clinical observations from mRNA vaccines. This capability highlights the translational relevance of iMonocytes in dose optimization, reducing reliance on animal studies while accelerating the refinement of therapeutic dosing protocols. iMonocyte offers a promising platform for investigating nextgeneration LNP based therapeutics, including vaccine development for infectious disease, cancer, and genetic disorders.

[0232] Beyond monocyte engagement, LNPs activate the complement system - a process governed by their physicochemical properties (surface charge, PEGylation density, and lipid composition) that generates anaphylatoxins (C3a, C5a) and opsonins (C3b). These complement products potentiate monocyte responses through CR3-mediated phagocytosis and proinflammatory cytokine production (IL-ip, IL-6), establishing a functional bridge between cellular innate defense mechanisms. The resulting innate immune activation propagates to adaptive immunity via enhanced dendritic cell maturation and antigen presentation, culminating in robust CD8+ cytotoxic T cell responses and CD4+ T helper cell polarization. Therefore, comprehensive profiling of these LNP-complement interactions via iMonocytes could further guide rational design of vaccine platforms for finely tuned immune activation profiles. Moreover, future high-throughput screening of LNP libraries may reveal LNP physicochemical structure-activity relationships that enable precise control over immunostimulatory and efficacy outcomes.

[0233] To validate the translatability of our in vitro findings, in vivo studies using murine models were conducted. While murine models offer valuable preclinical insights, and mice and humans share many conserved immune pathways, evolutionary divergence has led to key functional differences in immune recognition and response mechanisms. Therefore, the results should be interpreted in parallel with human data to ensure translational relevance and a comprehensive understanding of immune responses to mRNA vaccines.

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[0235] #14672028vl The treatment of iMonocytes with mRNA-LNPs resulted in the up-regulation of gene expression related to some of the immune pathways that we have previously observed when administering ASO-LNPs to mice via intracerebroventricular injection, specifically the interferon and related oligoadenylate synthetase (OAS) pathways. This observation suggests that part of the observed immune response may be related to cellular sensing of non-host RNA and that this response differs by LNP. Overall, the relationship between gene expression profiles and immune responses suggests that transcriptomic profiles of iMonocytes can be further developed to contribute to high-throughput screening of LNPs by providing a gene set scoring system. Comparative analysis revealed that iMonocytes capture immunostimulatory responses overlooked by primary cells, particularly for LNPs with low- to-medium immunostimulatory potency. This in vitro behavior closely mirrors in vivo observations and underscores the translational relevance of the iMonocyte assay platform. Delineating the mechanistic basis for these divergent responses will be essential for refining predictive models and advancing our understanding of LNP -triggered immune activation.

[0236] In summary, iMonocytes provide a translational and robust platform for assessing LNP innate immune response, accelerating the design of safer, more effective LNP formulations and fostering innovation across the fields of nucleic acid delivery, immunotherapy, and vaccine development.

[0237] Methods iPSC culture and characterization iPSC line iPl 1 and SCTi003-A were purchased from ALSTEM and Stem Cell Technology, respectively. iPl 1 line was generated from the foreskin fibroblasts of a male donor, and SCTi003 was generated from healthy female donor peripheral blood mononuclear cells (PBMCs) by each vendor. After thawing cryopreserved iPSCs, the cells were plated on Matrigel®-coated cultureware, cultured, and passaged at least three times before initiating iMonocyte differentiation. All iPSCs were maintained in mTeSR™l media and were passaged as small chunks every 3-5 days, depending on confluence, using Gentle Cell Dissociation Reagent. All iPSC lines were routinely characterized for the expression of pluripotency markers, and mycoplasma tests were performed regularly. For characterization, cells were plated in a 96-well PhenoPlate and subjected to immunofluorescence staining for NANOG, OCT4, SSEA4, and TRA1-81. Total RNA was purified from cells using RNeasy Micro Kit and transcribed to cDNA using the theSuperScript™ IV VILO™ Master Mix with ezDNase™ Enzyme. Quantitative RT-PCR was performed using the QuantStudio 7 Pro

[0238] 40

[0239] #14672028vl system, with taqMan™ Fast Advanced Master Mix. The following pre-designed primer sets were used (Table 5): 0.1 mL custom TaqMan Array plates (18s rRNA, OCT4, NANOG, CD68, and LYZ) and PrimeTime™ Std qPCR Assay (KLF4, CD14, CD34 and CD48).

[0240] Table 5. Primers and probes used for RT PCR

[0241] Directed differentiation of human iPSCs into iMonocyte

[0242] Hematopoietic progenitors and iMonocytes were generated sequentially from iPSCs using the STEMdiff™ Monocyte Kit according to the manufacturer's instructions, with minor modifications. Briefly, iPSCs at approximately 80% confluency were dissociated using Gentle Cell Dissociation Reagent and filtered through a 37 pm reversible filter to remove single cells. The cell aggregates were then plated in Matrigel®-coated cultureware and incubated overnight at 37°C. From day 0 to day 2, the cells were maintained in Hematopoietic Medium A, followed by Hematopoietic Medium B from day 5 to day 7. A portion of the cells was collected at this stage to characterize the hematopoietic stem cells. Subsequently, Monocyte Differentiation Medium was introduced, with medium changes every 2-3 days until day 18-20, when monocytes were harvested as needed. The purity of the CD14+ / CD16+ monocyte population was assessed by flow cytometry and further characterized by quantitative PCR.

[0243] #14672028vl Phagocytosis assay

[0244] The uptake of pH-sensitive pHrodo dyes conjugated to zymosan A particles (P35365) by iMonocytes was assessed using high-content Incucyte imaging. Harvested iMonocytes were seeded into poly-D-lysine (PDL)-coated 96-well PhenoPlates at a density of 30,000 cells per well, one day prior to the phagocytosis assay. On the day of the assay, half of the cell culture medium was replaced with fresh medium containing 2x pHrodo particles, resulting in a final concentration of 10 pg / mL. Kinetic measurements were performed using the Incucyte system at 37°C with 5% CO2. Four images per well were captured at one-hour intervals using a 20* objective. In some wells, cytochalasin D (100 ng / mL) or LPS (200 ng / mL)was added to inhibit phagocytosis. After 48 hours of imaging, the integrated intensity (GCU x pm2 / image) was calculated using the Incucyte software. mRNA payload synthesis

[0245] OVA mRNA and modRNA were used in the studies. OVA mRNA was purchased from TriLink BioTechnologies. modRNA was synthesized in house, using 1-methyl- pseudouridine, capping was performed cotranscriptionally using a trinucleotide cap 1 analog (CleanCap AG (3' OMe) m7(3'OMeG)(5’)ppp(5')(2'OMeA)pG, Trilink). Co-transcriptionally capped RNA reactions were performed using a Capl analog, CleanCap® Reagent AG (3’0Me) (TriLink, N-7413), and the T7-FlashScribe™ Transcription Kit. The linearized DNA template was mixed with ATP, CTP, GTP, ml YTP, DTT, 10x reaction buffer, RNase inhibitor, and T7 RNA polymerase. The reaction included N1 -methyl pseudouridine 50- triphosphate (ml YTP) (TriLink) for nucleoside-modified mRNA, in which 100% of uridine was substituted with mlY. For each sample, 1 pg of linearized DNA template was mixed with 2 pL of 10X T7 Transcription Buffer, 1.8 pL of each NTP (ATP, CTP, GTP, ml YTP), 1.8 pL of the CleanCap AG, 2 pL of DTT, 0.5 pL of RNase inhibitor, 2 pL of T7 FlashScribe Enzyme, and RNase-free water to reach 20 pL total. The reaction was incubated for 2 h at 37°C at 300 rpm (Thermo Scientific™ Sorvall™ Legend™ Micro 17R Microcentrifuge). DNase was then added and incubated for 15 min at 37°C. The RNA reaction was stopped by ammonium acetate precipitation. Briefly, the sample was incubated for 15 min on ice and then centrifuged at 13,300 rpm for 15 min at 4°C. The supernatants were removed, and the pellets were gently rinsed with 70% ambient ethanol. The centrifugation step was repeated under the same conditions. The ethanol supernatant was pipetted out, and the pellet was briefly air-dried prior to suspension in RNase-free water. A final column purification using the MEGAclear™ Kit (Invitrogen) was performed according to the manufacturer’s

[0246] 42

[0247] #14672028vl instructions. RNA concentration was measured using a NanoDrop spectrophotometer (Thermo Fisher Scientific) at 260 nm. RNA samples were stored at -80°C. mRNA-LNP preparation

[0248] Lipids, including l,2-distearoyl-sn-glycero-3-phosphoethanolamine (DOPE), 1,2- dimyristoyl-sn- glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (14:0 PEG2000 PE) were purchased from Avanti Polar Lipids. The ionizable lipids dilinoleylmethyl-4- dimethylaminobutyrate (DLin-MC3-DMA) (MC3); heptadecan-9-yl 8-((2 -hydroxyethyl) (6- oxo-6-(undecyloxy)hexyl)amino)octanoate ester (SM102); and 3,6-bis(4-(bis(2- hydroxydodecyl)amino)butyl) piperazine-2, 5-dione (CKK-E12) were from MedChemExpress, and cholesterol was sourced from Sigma-Aldrich. Lipid 20, described in US patent US 10, 221,127, was synthesized in-house. mRNA was diluted in citrate buffer (50 mM, pH 3.0). The organic phase consisted of ionizable, DOPE, cholesterol, and C14-PEG2000 in ethanol, with a molar ratio of 50: 10:38.5: 1.5 and a total lipid concentration of 12.5 mM. mRNA-LNPs were formulated by the microfluidic method, as previously described. Specifically, NanoAssemblr Ignite (Precision Nanosystems, BC, Canada) was used to prepare bench-scale LNPs, with a total flow rate of 12 mL / min and an aqueous to organic ratios of 3 : 1. The resulting mRNA-LNPs were dialyzed against phosphate-buffered saline (PBS, pH 7.4) using the Pierce microdialysis plate (Thermofisher) with a 10 kDa molecular weight cutoff (MWCO). Dialysis was performed for 2 hrs at room temperature, followed by buffer change and then overnight dialysis at 4°C.

[0249] Physicochemical Characterization of mRNA-LNPs

[0250] Particle size distributions of mRNA-loaded LNPs were analyzed by dynamic light scattering (DLS). Samples were diluted 10-fold in phosphate-buffered saline (PBS, pH 7.4) and analyzed in a 384-well microplate using a DynaPro Plate Reader III. The mean particle diameters and particle size distributions, represented as percent poly dispersity (%PD), were determined. The concentrations of soluble and total mRNA (after extraction using 0.2% Triton X-100 in 1 * TE buffer) were quantified using the Quant-iT™ RiboGreen reagent. The percent encapsulation efficiency (%EE) of mRNA was calculated using the following equation:

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[0252] #14672028vl

[0253] Cryogenic transmission electron microscopy (Cryo-TEM)

[0254] Cryo-EM samples were prepared by applying 3 pL of undiluted mRNA-LNP onto glow-discharged carbon grids (Quantifoil Cu 300 mesh Rl.2 / 1.3) treated for 7-9 s at 20 mA, followed by vitrification using a Vitrobot Mark IV system maintained at 4°C and 95% humidity with the following blotting parameters: -12 to -25 blot force, 45 s wait time, and 0.5 s drain time. Images were taken on a Talos Arctica 200 keV TEM equipped with a Falcon III detector, collecting data at 0.78-0.96 A / pixel with defocus values ranging from -1.5 to -3 pm and a total electron dose of 60-64 Q-lk2.

[0255] PBMC isolation and primary monocyte purification

[0256] Whole blood was obtained from three to six healthy human donors who voluntarily consented to participate in ablood donation program. The collected blood was diluted 1 : 1 with phosphate-buff ered saline (PBS) and processed for peripheral blood mononuclear cell (PBMC) isolation using density gradient centrifugation (1200 * g for 15 minutes) in SepMate™ tubes. Mononuclear cells were carefully collected from the plasma / Ficoll interface using a serological pipette.

[0257] The isolated PBMCs were washed with 1 x PBS and passed through a 70 pm cell strainer to remove debris. Primary monocytes were subsequently purified from the PBMCs using the Monocyte Isolation Kit (StemCell Technologies) following the manufacturer's protocol. Live cell counts were determined using a Vi-CELL BLU Cell Viability Analyzer. PBMCs or monocytes were then seeded in a 96-well round-bottom plate at a density of 2-4 x 105cells per well and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS), l x GlutaMAX™, 55 pM P-mercaptoethanol, 10 mM HEPES, l x non-essential amino acids, and 1 x sodium pyruvate.

[0258] Flow cytometry

[0259] Media were removed, and cells were washed twice with PBS before staining. Viability staining was performed using Ghost Dye UV 450 and Human TruStain FcX block for 30 minutes at 4 °C. After staining, cells were washed and resuspended in 30 pL of antibody cocktail per well. Cells were stained for surface markers for 30 minutes at 4 °C using the following antibodies: BB700 anti-CD14 (M5E2) and PE anti-CD16 (3G8). All

[0260] 44

[0261] #14672028vl antibodies were obtained from either BD Biosciences or BioLegend. Cells were acquired on a CytoFLEX LX 6-laser flow cytometer equipped with CytExpert Software. Data analysis was performed using FlowJo software (v.10.8.2). Dead cells were excluded based on viability dye staining, and single cells were gated using forward scatter area and height (FSC-A / FSC-H) parameters.

[0262] TLR agonist and mRNA-LNP treatments

[0263] The TLR7 / 8 agonist R848 was used to prime iMonocytes and PBMCs. A dose titration of R848, ranging from 0.01 pg / mL to 5 pg / mL, was conducted separately on iMonocytes, PBMCs, and primary monocytes to determine the optimal concentration. Cells were treated with R848 and incubated for 2 hrs at 37 °C. Cells were washed out before mRNA-LNP treatment. mRNA-loaded LNPs were diluted 1 :10 or 1 :20 in Monocyte Differentiation Medium and added to cells at the final mRNA concentration of 1 or 2 pg / mL in a total volume of 200 pL per well. After overnight incubation and a subsequent 3-day culture, the plates were centrifuged, conditioned media were collected, and cells were resuspended in FACS staining buffer (1 x PBS with 2% BSA) for flow cytometry analysis. Alternatively, cells were seeded into 96-well black / clear flat-bottom plates to measure mRNA expression kinetics by imaging mScarlet fluorescence intensity (Ex / Em 569 nm / 594 nm) using the Incucyte.

[0264] In Vivo

[0265] To measure the cytokine level in vivo, 6-8-week-old C57BL / 6 mice were intramuscular injections of ml'P-modified mRNA-LNPs at a dose of 0.15 mg / kg. At 6 h post-injection, whole blood was collected into tubes containing 3.8% sodium citrate as an anticoagulant. Samples were centrifuged at 1,500 x g for 10 min at 4 °C to obtain plasma, which was immediately stored at -80 °C until subsequent Luminex cytokine analysis.

[0266] Luminex assay

[0267] To measure cytokines, conditioned media from cell culture were collected and frozen until the assay. Samples were thawed and analyzed using Milliplex MAP reagents according to the manufacturer’s recommended protocol. The reconstituted standards were diluted by 2.73 folds to increase the number of data points from six to nine while maintaining the original dynamic range. Fluorescence intensity was measured by xPONENT software v 4.2 on FlexMap 3D instruments. Standards were prepared with two replicates and measured for 45

[0268] #14672028vl median fluorescence intensity using the Bio-Plex Manager v 6.2. Four- or five-point standard curves were obtained for each cytokine analyte and each plate. Sample measurements were performed with three replicates. Any values below the quantification limit were recorded as zero.

[0269] RNA-seq

[0270] Total RNA was purified from cells using RNeasy Micro Kit and quantified with the Quant-iT RiboGreen RNA Kit on a Victor X2 Multilabel Microplate Reader. RNA quality was determined using the High Sensitivity RNA ScreenTape Assay on a TapeStation 4200. Sequencing libraries were prepared using the SMART-Seq Total RNA PicoInput kit with 1- 10 nanograms of total RNA as input. Libraries quantification was performed using the Quant- iT PicoGreen dsDNA Assay Kit on the Victor X2 Multilabel Microplate Reader. Average library size was analyzed using D5000 ScreenTape Assay on a TapeStation 4200. Libraries were pooled and sequenced on NovaSeq X Plus to generate 30 million single-end, 50 base pair reads for each sample. RNA-seq data was analyzed through fastp (PMID: 30423086, 38868435), GSNAP (PMID: 27008021), HTSeqGenie, and voom-limma (PMID: 24485249). Enrichr was utilized for the GO and Reactome analysis of the shared DEGs (PMID: 23586463, 27141961 and 33780170). CAMERA (PMID: 22638577) was utilized for enrichment analysis of Reactome pathways for the individual contrasts (PMIDs: 31691815, 37941124).

[0271] Statistical analysis

[0272] All quantitative data are expressed as mean ± standard error of the mean (SEM), with exact sample sizes (n) detailed in respective figure legends. Parametric analyses were performed using unpaired Student's t-tests for pairwise comparisons or one- / two-way ANOVA for multi-group evaluations, followed by Tukey's or Dunnett' s post hoc tests where appropriate. A significance threshold of p < 0.05 was applied for all analyses, which were analyzed using GraphPad Prism 10. To normalize the distribution of cytokine levels and stabilize variance, all cytokine raw data were log 10 transformed. We then employed linear mixed-effect models to determine the effect of various treatments on cytokine responses. A separate model was fitted for each cytokine dataset obtained from each assay platform (in vivo, iPSC, and primary cells). For the in vivo data, cytokine results were modeled as a function of the treatment. A random intercept for each replicate was included to account for baseline differences between experimental repeats. For the iPSC data, the model was 46

[0273] #14672028vl extended to include an additional random effect for the experimental batch. For the primary cell data, cytokine results were modeled with treatment and donor as fixed effects and replicate as a random effect. Estimated coefficients for the treatment effects were extracted from each model. These coefficients were then aggregated across all common cytokines to estimate a composite effect size, allowing for the direct comparison and ranking of treatment- induced effects.

[0274] 47

[0275] #14672028vl

Claims

What is claimed is:CLAIMS1. A method of assessing an immune response to a lipid composition, the method comprising: combining monocytes differentiated from induced pluripotent stem cells and a lipid composition; and assessing the monocytes for an immune response to the lipid composition.

2. The method of claim 1 further comprising differentiating the monocytes from induced pluripotent stem cells, optionally wherein the monocytes are CD14+ / CD16+.

3. The method of claim 1, wherein combining the monocytes and the lipid composition is in a cell culture medium.

4. The method of claim 3, wherein the culture medium comprises serum.

5. The method of claim 4, wherein the concentration of the serum in the cell culture medium is about 5% to about 15%, optionally about 10%.

6. The method of claim 5, wherein the serum comprises fetal bovine serum.

7. The method of any of claims 3-5, wherein the cell culture medium comprises a Tolllike receptor (TLR) agonist.

8. The method of claim 7, wherein the TLR agonist is selected from imidazoquinoline compounds, adenine compounds, benzazepine compounds, flagellin, guanosine compounds, thiazoquinoline compounds, lipopolysaccharides, nucleic acid derivatives (e.g., CpG-ODNs, Poly I, ssRNA), nucleoside analogs, and synthetic small molecules.

9. The method of claim 8, wherein the TLR agonist is an imidazoquinoline compound.

10. The method of claim 9, wherein the imidazoquinoline compound is selected from resiquimod (R848), imiquimod, gardiquimod, dactolisib, and sumanirole.

11. The method of claim 10, wherein the TLR agonist is resiquimod.

12. The method of claim 10 or 11, wherein the concentration of the imidazoquinoline compound in the cell culture medium is about 0.05 pg / mL to 0.1 pg / mL.

13. The method of any preceding claim, wherein assessing the monocytes for an immune response comprises assaying for a marker of immune activation, assessing cell viability, assessing cell proliferation, assessing phagocytic activity, assessing transfection efficiency, and / or assessing influx of calcium of the monocytes.

14. The method of claim 13, wherein assessing the monocytes for an immune response comprises assaying for a marker of immune activation.48#14672028vl15. The method of claim 14, wherein the marker of immune activation is selected from cytokines, chemokines, reactive oxygen species (ROS), nitric oxide (NO), pro-inflammatory lipid mediators, complement proteins, growth factors, and soluble immune checkpoint proteins.

16. The method of claim 15, wherein the marker is a cytokine or chemokine.

17. The method of claim 16, wherein the cytokine or chemokine is selected from IL-1, IL- la, IL-1 , IL-2, IL-4, IL-6, IL-8, IL-10, IL-11, IL-12, IL-13, IL-17, IL-18, CCL3, CCL5, IFN-y, MCP-1, TNF-a, CXCL10 / IP-10, and TGF-0.

18. The method of any preceding claim, wherein combining the monocytes and the lipid composition comprises exposing the monocytes to multiple doses of the lipid composition.

19. The method of any preceding claim, wherein the lipid composition is selected from micelles, nanostructured lipid carriers, lipid polymer hybrid nanoparticle, lipid nanoemulsions, lipid nanoparticles (LNPs), and liposomes.

20. The method of claim 19, wherein the lipid composition is a lipid nanoparticle (LNP).

21. The method of any preceding claim, wherein the lipid composition further comprises at least one therapeutic molecule.

22. The method of claim 21, wherein the therapeutic molecule is selected from therapeutic nucleic acids and therapeutic proteins.

23. The method of claim 22, wherein the therapeutic molecule is an RNA molecule.

24. The method of claim 23, wherein the RNA molecule is selected from messenger RNA (mRNA), short interfering RNA (siRNA), microRNA (miRNA), guide RNA (gRNA), circular RNA (circRNA), and self-amplifying messenger RNA (samRNA).

25. The method of claim 24, wherein the therapeutic molecule is an mRNA.

26. The method of claim 25, wherein the mRNA encodes an antibody or an antigen.

27. The method of any one of claims 21-26 further comprising assessing the monocytes to differentiate between an immune response induced by the lipid composition and an immune response induced by the therapeutic molecule.

28. The method of claim 27, wherein assessing the monocytes comprises producing a differential cytokine signature that reflects the cytokines produced as part of the immune response induced by the lipid composition and the cytokines produced as part of the immune response induced by the therapeutic molecule.

29. A method of assessing an immune response to a lipid composition, the method comprising: optionally differentiating monocytes from induced pluripotent stem cells;49#14672028vlcombining a population of the monocytes with a lipid composition in a cell culture medium comprising serum; and assessing the monocytes for an immune response to the lipid composition.

30. The method of claim 29, wherein about 20% to about 40%, optionally about 30%, of the monocytes of the population express CD14.

31. The method of claim 29 or 30, wherein about 30% to about 50%, optionally about 40%, of the monocytes of the population express CD 16.

32. The method of any one of claims 29-31, wherein the monocytes secrete TNF-a in response to exposure to a TLR agonist, optionally a TLR7 / 8 agonist.

33. The method of any one of claims 29-32, wherein the serum is fetal bovine serum.

34. The method of any one of claims 29-33, wherein the concentration of serum in the culture medium is about 5% to 15%, optionally about 10%.

35. The method of any one of claims 29-34, wherein assessing the monocytes for an immune response to the lipid composition comprises (a) adding a TLR agonist to the cell culture medium and (b) assaying for a marker of immune activation.

36. The method of claim 35, wherein the marker of immune activation is selected from cytokines, chemokines, reactive oxygen species (ROS), nitric oxide (NO), pro-inflammatory lipid mediators, complement proteins, growth factors, and soluble immune checkpoint proteins.

37. The method of claim 36, wherein the marker is a cytokine or chemokine.

38. The method of claim 37, wherein the cytokine or chemokine is selected from IL-1, IL- la, IL-ip, IL-2, IL-4, IL-6, IL-8, IL-10, IL-11, IL-12, IL-13, IL-17, IL-18, CCL3, CCL5, IFN-y, MCP-1, TNF-a, CXCL10 / IP-10, and TGF-p.

39. The method of any one of claims 35-38, wherein the TLR agonist is a TLR7 / 8 agonist.

40. The method of any one of claims 35-39, wherein the TLR agonist is selected from imidazoquinoline compounds, adenine compounds, benzazepine compounds, flagellin, guanosine compounds, thiazoquinoline compounds, lipopolysaccharides, nucleic acid derivatives (e.g., CpG-ODNs, Poly I, ssRNA), nucleoside analogs, and synthetic small molecules.

41. The method of claim 40, wherein the TLR agonist is an imidazoquinoline compound.

42. The method of claim 41, wherein the imidazoquinoline compound is selected from resiquimod (R848), imiquimod, gardiquimod, dactolisib, and sumanirole.

43. The method of claim 42, wherein the TLR agonist is resiquimod.50#14672028vl44. The method of claim 42 or 43, wherein the concentration of the imidazoquinoline compound in the cell culture medium is about 0.05 pg / mL to 0.1 pg / mL.

45. The method of any one of claims 29-44, wherein the lipid composition is selected from micelles, nanostructured lipid carriers, lipid polymer hybrid nanoparticle, lipid nanoemulsions, lipid nanoparticles (LNPs), and liposomes.

46. The method of claim 45, wherein the lipid composition is a lipid nanoparticle (LNP).

47. The method of any one of claims 29-46, wherein the lipid composition further comprises at least one therapeutic molecule.

48. The method of claim 47, wherein the therapeutic molecule is selected from therapeutic nucleic acids and therapeutic proteins.

49. The method of claim 48, wherein the therapeutic molecule is an RNA molecule.

50. The method of claim 49, wherein the RNA molecule is selected from messenger RNA (mRNA), short interfering RNA (siRNA), microRNA (miRNA), guide RNA (gRNA), circular RNA (circRNA), and self-amplifying messenger RNA (samRNA).

51. The method of claim 50, wherein the therapeutic molecule is an mRNA.

52. The method of claim 51 , wherein the mRNA encodes an antibody or an antigen.

53. The method of any one of claims 47-52 further comprising assessing the monocytes to differentiate between an immune response induced by the lipid composition and an immune response induced by the therapeutic molecule.

54. The method of claim 53, wherein assessing the monocytes comprises producing a differential cytokine signature that reflects the cytokines produced as part of the immune response induced by the lipid composition and the cytokines produced as part of the immune response induced by the therapeutic molecule.

55. A composition comprising monocytes differentiated from induced pluripotent stem cells and a lipid composition.

56. The composition of claim 55 further comprising cell culture medium.

57. The composition of claim 56 further comprising serum.

58. The composition of claim 57, wherein the concentration of the serum in the cell culture medium is about 5% to 15%.

59. The composition of claim 58, wherein the serum comprises fetal bovine serum.

60. The composition of any of claims 56-59, wherein the cell culture medium comprises a Toll-like receptor (TLR) agonist.

61. The composition of claim 60, wherein the TLR agonist is selected from imidazoquinoline compounds, adenine compounds, benzazepine compounds, flagellin,51#14672028vlguanosine compounds, thiazoquinoline compounds, lipopolysaccharides, nucleic acid derivatives (e.g., CpG-ODNs, Poly I, ssRNA), nucleoside analogs, and synthetic small molecules.

62. The composition of claim 61, wherein the TLR agonist is an imidazoquinoline compound.

63. The composition of claim 62, wherein the imidazoquinoline compound is selected from resiquimod (R848), imiquimod, and gardiquimod.

64. The composition of claim 63, wherein the TLR agonist is resiquimod.

65. The composition of claim 63 or 64, wherein the concentration of the imidazoquinoline compound in the cell culture medium is about 0.05 pg / mL to 0.1 pg / mL.

66. The composition of any preceding claim, further comprising a marker of immune activation secreted by the monocytes.

67. The composition of claim 66, wherein the marker of immune activation is selected from cytokines, chemokines, reactive oxygen species (ROS), nitric oxide (NO), pro- inflammatory lipid mediators, complement proteins, growth factors, and soluble immune checkpoint proteins.

68. The composition of claim 67, wherein the marker of immune activation is a cytokine or chemokine.

69. The composition of claim 68, wherein the cytokine or chemokine is selected from IL- 1, IL- la, IL-ip, IL-2, IL-4, IL-6, IL-8, IL- 10, IL-11, IL- 12, IL- 13, IL- 17, IL- 18, CCL3, CCL5, IFN-y, MCP-1, TNF-a, CXCL10 / IP-10, and TGF-p.

70. The composition of any one of claims 55-69, wherein the lipid composition is selected from micelles, nanostructured lipid carriers, lipid polymer hybrid nanoparticle, lipid nanoemulsions, lipid nanoparticles (LNPs), and liposomes.

71. The composition of claim 70, wherein the lipid composition is a lipid nanoparticle (LNP).

72. The composition of any one of claims 55-71, wherein the lipid composition further comprises at least one therapeutic molecule.

73. The composition of claim 72, wherein the therapeutic molecule is selected from therapeutic nucleic acids and therapeutic proteins.

74. The composition of claim 73, wherein the therapeutic molecule is an RNA molecule.

75. The composition of claim 74, wherein the RNA molecule is selected from messenger RNA (mRNA), short interfering RNA (siRNA), microRNA (miRNA), guide RNA (gRNA), circular RNA (circRNA), and self-amplifying messenger RNA (samRNA).52#14672028vl76. The composition of claim 75, wherein the therapeutic molecule is an mRNA.

77. The composition of claim 76, wherein the mRNA encodes an antibody or an antigen.53#14672028vl

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