Lymphoid cell compositions, systems, and assays

Abstract

The present disclosure relates to in vitro mammalian, e.g., human, lymphoid cell cultures and systems, and the utility of these culture and systems for determining the immunogenicity of candidate therapeutic molecules. The present disclosure also relates to in vitro methods of antibody production utilizing the disclosed lymphoid cell cultures.

Description

LYMPHOID CELL COMPOSITIONS, SYSTEMS, AND ASSAYS

[0001] The benefit under 35 U.S.C. §119(e) of U.S. Provisional Application No. 63 / 679,578, filed August 5, 2024, is hereby claimed. FIELD

[0002] The field of this disclosure relates to in vitro human lymphoid cell cultures and systems, and the utility of these culture and systems for determining the immunogenicity of candidate therapeutic molecules. The present disclosure also relates to in vitro methods of antibody production utilizing the disclosed lymphoid cell cultures. INCORPORATION BY REFERENCE OF MATERIAL SUBMITTED ELECTRONICALLY

[0003] Incorporated by reference in its entirety is a computer-readable nucleotide / amino acid sequence listing submitted concurrently herewith and identified as follows: 11.5 KB (XML) file named "10966-WO01-SEC_Seqlisting.xml"; created on August 4, 2025. BACKGROUND OF VARIOUS EMBODIMENTS

[0004] Biologic-based therapeutics, e.g., monoclonal antibodies (mAbs), bispecific antibodies, recombinant peptides, fusion proteins, and antibody-peptide conjugates, are revolutionizing personalized medicine by providing highly specific targeted treatment options across an array of diseases and disorders. However, as the diversity and complexity of these biologic-based therapies expands, so does the risk of immunogenicity. In fact, repeated administration of even a simple biologic, such as monoclonal antibody, can be highly immunogenic. Drug immunogenicity results in the generation of anti-drug antibodies (ADAs), which can alter a drug's pharmacokinetic and pharmacodynamic properties, reducing drug efficacy. In severe cases, ADAs can neutralize the drug's therapeutic effects or cause severe adverse events to the patient. Accordingly, there is a need to identify the potential immunogenicity associated with any biologic molecule early in its development.

[0005] Current methods and assays for predicting immunogenicity of biologics include computational prediction of T cell epitopes, DC:T cell in vitro assays, and in vivo assays (e.g., cynomolgus macaque toxicology studies). However, each of these have limited utility (e.g., only predict T cell epitopes) or limited sensitivity which leads to poor translatability to the clinic. Thefailure of these current methods and assays arises from their failure to recapitulate the cellular and structural complexity of the human immune system. Accordingly, there is a need in the art for an in vitro platform that accurately recapitulate critical aspects of human immune response to more accurately predict the immunogenicity of biologic-based therapeutic early in the development pipeline. SUMMARY OF VARIOUS EMBODIMENTS

[0006] A first aspect of the present disclosure is directed to an in vitro system, where the system comprises: a plurality of mammalian lymphoid cell cultures. Each of the plurality of mammalian lymphoid cell cultures comprise mammalian lymphoid tissue-derived B cells and T cells in a cell culture well comprising culture media, and a candidate therapeutic molecule in the culture media. The plurality of mammalian lymphoid cell cultures comprise a plurality of different major histocompatibility complex (MHC) proteins.

[0007] Another aspect of the present disclosure is directed to an in vitro method of predicting in vivo immunogenicity of a candidate therapeutic molecule. This method comprises providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising mammalian lymphoid tissue derived B cells and T cells in culture media, where the plurality of mammalian lymphoid cell cultures comprise a plurality of different MHC proteins. The method further involves administering a first and second dose of the candidate therapeutic molecule to each of the plurality of cell cultures, where the second dose is administered between 3–7 days after administering the first dose. The cells, the culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures are harvested after administering the second dose of the candidate therapeutic molecule, and one or more markers of a de novo immune response is assessed in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In vivo immunogenicity of the candidate therapeutic molecule is determined based on assessment of the one or more markers of the de novo immune response.

[0008] Another aspect of the present disclosure is directed to an in vitro method of predicting in vivo immunogenicity of a candidate therapeutic molecule. This method involves providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4. The plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles. The methodfurther involves administering the candidate therapeutic molecule to each of the plurality of cell cultures, and harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5-8 days after administering the candidate therapeutic molecule. One or more markers of immune cell activation is measured in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures, and in vivo immunogenicity of the candidate therapeutic molecule is predicted based on measurement of the one or more markers of B cell and / or T cell activation.

[0009] Another aspect of the present disclosure is directed to a method of producing an in vitro immune responsive mammalian lymphoid cell culture. This method comprises subjecting isolated mammalian lymphoid tissue to mechanical and enzymatic dissociation to produce a suspension of lymphoid tissue derived B cells, T cells, follicular dendritic cells, dendritic cells and endothelial cells. The method further comprises, introducing the suspension of lymphoid tissue derived cells, after the subjecting, into a cell culture well comprising cell culture media, where the cell culture media comprises a candidate therapeutic molecule and does not contain a B cell survival factor. The B cell survival factor is added to the cell culture media at 3-5 days after the introducing step to produce the immune responsive human lymphoid cell culture. The present disclosure is further directed to an in vitro mammalian lymphoid cell culture produced by this method.

[0010] Another aspect of the present disclosure is directed to an in vitro mammalian lymphoid cell culture. This cell culture comprises mammalian lymphoid tissue derived B cells and T cells in a cell culture well comprising culture media; and a candidate therapeutic molecule in the culture media. In some aspects the cell culture is devoid of CD25+ cells. In some aspects the cell culture further comprises plasmablasts and / or plasma cells, wherein the plasmablasts and / or plasma cells secrete anti- candidate therapeutic molecule antibodies.

[0011] Another aspect of the present disclosure is directed to an in vitro mammalian lymphoid cell culture. This cell culture comprises mammalian lymphoid tissue-derived B cells and T cells in a cell culture well comprising culture media, an antigen, and an antigen delivery system.

[0012] Another aspect of the present disclosure is directed to an in vitro method of generating antibodies against a target antigen. This method comprises providing a cell culture comprising mammalian lymphoid tissue derived B cells and T cells and introducing, to the cell culture, an antigen delivery system comprising the target antigen. This method further comprises incubating the cell culture, after said introducing, under conditions suitable for B cells of the culture to produce antibodiesagainst the antigen. In one embodiment, the antigen delivery system comprises an artificial antigen presentation scaffold as described herein.

[0013] Another aspect of the present disclosure is directed to an antigen delivery system This antigen delivery system comprises a substrate and a lipid layer surrounding the substrate. In one embodiment, the antigen is immobilized directly to the surface of the lipid layer surrounding the substrate. In another embodiment, the antigen is immobilized to the surface of the lipid layer indirectly via an immune-complex. In this embodiment, the artificial antigen presentation scaffold further comprises an immune-complex receptor protein and an immune-complex receptor ligand. The immune-complex receptor protein is immobilized to a surface on the lipid layer, and the immune- complex receptor ligand is coupled to an antigen and is bound to the immobilized immune-complex receptor proteins on the surface of the lipid layer.

[0014] The in vitro lymphoid cell cultures and systems described herein accurately mimic the cellular and structural complexity of the in vivo human immune system. As demonstrated herein, these cultures are capable of recapitulating B cell maturation and de novo antibody response to antigenic stimuli. Importantly, as demonstrated herein the lymphoid cell cultures and systems of the present disclosure also recapitulate de novo immune responses to clinical therapeutic molecules, with the lymphoid culture immune responses correlating tightly with clinical ADA rates of these therapeutic molecules. The lymphoid cell cultures also generate de novo immune responses to clinical therapeutic molecules, which were not identified as comprising immunogenic liabilities in standard in vitro immunogenicity assays. Accordingly, the lymphoid cell cultures and systems described herein provide a novel and highly sensitive in vitro immunogenicity platform for predicting candidate therapeutic molecule immunogenicity early in pre-clinical therapeutic molecule development. BRIEF DESCRIPTION OF THE FIGURES

[0015] FIGs.1A–1C show that tonsil cells form aggregates in culture. As shown in FIG. 1A, tonsil cells seeded as single-cell suspensions into Transwell inserts form aggregates after 2-3 days in culture. Representative images of tonsil cell re-aggregation in a Transwell insert (FIG. 1B) and 96- flat bottom plate (FIG.1C) captured on the Opera Phenix High-content Screening System (10X, non- confocal brightfield).

[0016] FIGs.2A–2B are images of live cell immunofluorescent staining of tonsil cell cultures showing high B cell and T cell content in the tonsil cultures. Day 3 tonsil cultures were stained forCD3 (T cells, red), CD20 (B cells, green), and Hoechst (nuclei, blue) (FIG.2A) and the cell field was imaged using the Opera Phenix High-content Screening System (20X, confocal). FIG.2B is a higher magnification of the inset shown in FIG. 2A.

[0017] FIGs.3A–3C show 3-dimensional imaging of tonsil aggregates after 14 days in culture. Tonsil aggregates were stained for CD20 (B cells, green) and CD3 (T cells, red) (FIG.3A) or CXCR4 (germinal center dark zone, red) and CD20 (B cells) (FIGs. 3B and 3C) and imaged using the Opera Phenix High-content Screening System (20X, confocal). White solid arrows indicate the periphery while white, non-solid arrows indicate the inner core of tonsil aggregates.

[0018] FIGs.4A–4B show tonsil aggregates display B cell rich areas with light and dark zones. Tonsil aggregates were stained for CD20 (B cells; green), CXCR4 (germinal center dark zone; red) and Hoechst (nuclei; blue) (FIG.4A) or CXCR4 (germinal center dark zone; red) and CD35 (follicular dendritic cell marker; blue) (FIG. 4B) and the cell field was imaged using the Opera Phenix High- content Screening System (20X, confocal). The far right panel of each FIG. is an enlarged view of the white dotted boxed area of the middle panel.

[0019] FIGs. 5A–5B show the proportion of B cell phenotypes present in the tonsil cultures. FIG. 5A shows representative flow plots demonstrating discrimination of the following B cell phenotypes: (i) naïve B cells identified by CD27- / CD38- expression profile, (ii) memory B cells identified by CD27+ / CD38- expression profile, (iii) pre-GC B cells identified by CD27- / CD38+expression profile, (iv) Germinal Cell (GC) B cells identified by CD27+ / CD38+expression profile, and (v) plasmablasts identified by CD27+ / CD38hiexpression profile. Composition of B cell compartment (as % of total CD19+B cells) in cultures at D0 (FIG. 5B, top graph) and D14 without stimulation (FIG. 5B bottom left graph) or after stimulation with the Afluria Tetra Flu vaccine (FIG. 5B, bottom right graph).

[0020] FIGs. 6A–6B show the proportion of T cell phenotypes in tonsil cultures. FIG. 6A shows representative flow plots demonstrating discrimination of T cell phenotypes defined by CD3, CD4, CD8 and CXCR5 expression. Composition of T cell compartment (as % of total CD3+T cells) in cultures at D0 (FIG.6B, top graph) and D14 without stimulation (FIG.6B, bottom left graph) or at D 14 after stimulation with the Afluria Tetra Flu vaccine (FIG.6B, bottom right graph).

[0021] FIGs. 7A–7B show the proportion of macrophages in tonsil cultures. FIG. 7A shows representative flow plots demonstrating discrimination of macrophage phenotypes defined by CD11b and CD14 expression. Proportion of macrophages in unstimulated D14 cultures (FIG.7B, left graph)and cultures stimulated with Afluria Tetra Flu vaccine at D0 and cultured until D14 (FIG. 7B, right graph).

[0022] FIGs.8A–8B show the proportion of dendritic cells in tonsil cultures. FIG.8A shows representative flow plots demonstrating discrimination of dendritic cell phenotypes defined by CD11c and Clec9 expression. Proportion of total CD11c+ dendritic cells (FIG.8B, top three graphs) or cDC1 (Clec9+) cells (FIG. 8B, bottom three graphs) in cultures at D0 (FIG. 8B, top and bottom far left graphs), at D14 without stimulation (FIG. 8B, top and bottom middle graphs), and at D14 after stimulation with the Afluria Tetra Flu vaccine (D0) (FIG.8B, top and bottom far right graphs).

[0023] FIGs. 9A–9B show the proportion of follicular dendritic cells in tonsil cultures. FIG. 9A shows representative flow plots demonstrating discrimination of follicular dendritic cells defined as CD45- / CD90+ / PDPN+ / CD35+ / CD31- cells. FIG.9B is a graph showing the proportion of follicular dendritic cells in unstimulated cultures after 7 days, represented as % of total living cells

[0024] FIGs.10A–10B show the stimulation schedule is different for recall and novel antigens. FIG. 10A shows representative flow plots demonstrating the change in plasmablast (CD27+ / CD38++) proportion (gated on CD19+cells) in D14 cultures that were stimulated with the Afluria Tetra Flu vaccine one time (at D0) (FIG. 10A, top right, plasmablast population labeled “plasma”) or 3 times (at D0, D7, and D10) (FIG. 10A, bottom right). Flow plots of unstimulated control cultures are provided in FIG. 10A, top left and bottom left. FIG. 10B shows representative flow plots demonstrating the change in plasmablast proportion (gated on CD19+ cells) in D14 cultures that were stimulated with a novel antigen one time (at D0) (FIG. 10B, top right) or 3 times (at D0, D7, D10) (FIG. 10B, bottom right). Flow plots of unstimulated control cultures are provided in FIG. 10B, top left and bottom left.

[0025] FIGs. 11A–11B show that the timing of cytokine addition to the tonsil culture alters the culture’s responsiveness to stimulation. FIG.11A is an ELISpot showing total IgM secretion from cultures maintained for 14 days after stimulation with Rabies vaccine on D0 and D7; left column indicates timing of BAFF (1μg / mL) addition (D0, D3, D5, or D7), top row indicates donor ID. FIG. 11B shows the response rate (fold change IgM secretion in stimulated vs. unstimulated culture) as determined by antigen specific ELISpot to Afluria Tetra vaccine stimulation (2.5 μg administered on D0) (FIG. 11B, left graph) or Keyhole Limpet Hemocyanin (KLH) (1 μg administered on D0, D7, D10 (FIG.11B, right). BAFF was added at the timepoint indicated on the x-axis legend, cultures were maintained for 14 days prior to harvest and analysis by ELISpot

[0026] FIGs. 12A–12C show the recall response to Afluria Tetra Vaccine generated in the tonsil cultures from various donors. Cultures were simulated at D0 with 1 μg or 5 μg of Afluria Tetra Influenza vaccine. Change in plasmablast proportion (CD27+CD38hi) was quantified at D7 by flow cytometry (FIG.12A). FIG.12B is a graph plotting change in plasmablast proportion in unstimulated and stimulated (1 and 5 μg vaccine) donor cultures. The graph of FIG. 12C shows anti-HA IgM in culture supernatants on D14 in each of the treatment groups as quantified by ELISA.

[0027] FIGs. 13A–13C show the de novo response to Keyhole Limpet Hemocyanin (KLH) generated in tonsil cultures from various donors. Cultures were simulated at D0 and D10 with 0.1 or 1μg of KLH (megathura crenata). Changes in plasmablast proportion (CD27+CD38hi) cells were quantified at D7 by flow cytometry as shown in the plots for the unstimulated culture (FIG.13A, left) and the 0.1 μg and 1 μg KLH stimulated cultures (FIG. 13A, middle and right plots, respectively). FIG. 13B is a graph plotting change in plasmablast proportion in unstimulated and stimulated (1 μg KLH) donor cultures. The graph of FIG. 13C shows anti-KLH IgM in culture supernatants on D14 (left) and anti-KLH IgG in culture supernatants on D17 (right) as quantified by ELISA.

[0028] FIGs. 14A–14C show the de novo response of the tonsil cultures to clinical molecules. FIG. 14A provides a schematic overview of the experimental design (top) and a table listing the clinical molecules that were tested and their reported clinical ADA rate (bottom). Response rate as measured by fold-change in plasmablast frequency (as a percentage of B cells) in treated vs. untreated cultures after 14 days is shown the graph of FIG.14B. The graph of FIG.14C (left) shows the response rate as determined by change in frequency of antigen-specific antibody secreting cells as determined by ELISpot. A correlation plot of reported clinical ADA rate vs. responder rate in tonsil cultures as determined by antigen-specific antibody ELISpot is provided in FIG.14C, right graph.

[0029] FIGs.15A–15C demonstrate the tonsil model’s capacity to detect non-sequence-based immunogenicity in a fusion protein. FIG. 15A provides a schematic overview of the experimental design (top) and a table listing the clinical molecule tested and its known clinical ADA rate (bottom). The response rate of the tonsil cultures as measured by a change in plasmablast proportion (as a percentage of total B cells) in treated vs. untreated cultures after 14 days as determined by flow cytometry is shown in FIG.15B, left graph. The response rate as determined by change in frequency of antigen-specific antibody secreting cells in treated vs. untreated cultures after 14 days as determined by ELISpot is shown in FIG. 15B, right graph. FIG. 15C is a graph showing the change in T cellsexpressing a Tfh (CD4+CXCR5+) phenotype in untreated and treated cultures after 14 days as determined by flow cytometry

[0030] FIGs.16A–16B demonstrate the tonsil model’s capacity to detect non-sequence-based immunogenicity in a bispecific antibody modality. FIG. 16A provides a schematic overview of the experimental design (top) and a table listing the molecule tested and its clinical ADA rate (bottom). FIG. 16B, left graph, shows the response rate of the tonsil cultures as measured by fold-change in plasmablast proportion (as a percentage of total B cells) in cultures treated for 14 days with the parent bispecific antibody vs. cultures treated with either Fab arm of the parent bispecific alone as determined by flow cytometry. FIG. 16B, right graph, shows the response rate as measured by fold-change in frequency of antigen-specific antibody secreting cells in cultures treated for 14 days with the parent bispecific antibody vs. cultures treated with either Fab arm of the parent bispecific antibody alone as determined by ELISpot (FIG.16B, right).

[0031] FIG.17 shows an exemplary panel of ELISpot detected IgM and IgG secreting cells in non-stimulated tonsil cell cultures after 14 days (IgM) or 17 days (IgG). The high level of IgM and IgG secreting cells in the “normal” panel indicates a high level of non-specific, background immune cell activation in non-stimulated donor derived tonsil cells. As described in Example 9 herein and shown in the bottom panel of ELISpot plates of FIG.17, this high background immune cell activation is reduced by culturing cells in IL-4 / GM-CSF supplemented media.

[0032] FIG.18 shows that the addition of low levels of IL-4 and GM-CSF to the culture media reduces background proliferation to enhance detection of a de novo antigen-specific immune response. The graph of FIG.18 shows the fold increase in ovalbumin-specific antibody production in ovalbumin treated donor cells (vs. untreated cells) grown in the absence (- cytokines) or presence (+ cytokines) of IL-4 and GM-CSF. In the absence of IL-4 and GM-CSF media supplementation, a significant ovalbumin-specific antibody response was not detected in the tonsil cell cultures from donors 2 and 4. In contrast, once background proliferation was reduced using IL-4 / GM-CSF media supplementation, the expected ovalbumin-specific antibody response could be detected in donor 2 and donor 4 derived tonsil cultures.

[0033] FIG.19 shows that depletion of CD25+immune cells prior to culture of the tonsil-tissue derived cells increases the magnitude of the antigen-specific immune response. The graph of FIG.19 shows the fold increase in antigen-specific antibody secreting cells in CD25+and CD25-depleted tonsil cell cultures treated with ovalbumin.

[0034] FIGs. 20A-20B show the utility of the tonsil cell culture model in assessing CD4+T cell proliferation as an early surrogate marker of immunogenicity. FIG.20A shows detection of CD4+T cell proliferation (stimulation index) after 7 days of treatment with 300 nM ovalbumin. FIG. 20B shows that CD4+T cell proliferation in response to treatment with (i) 300 nM of an antibody molecule having low-to-no clinical immunogenicity and (ii) 300 nM of an antibody having high clinical immunogenicity. CD4+T cell proliferation tracks the known clinical immunogenicity profile of each compound.

[0035] FIG. 21A-21E is a panel of images showing artificial antigen presentation scaffolds of an antigen delivery system of the present disclosure. Biotin-liposome coated mesoporous silica micro- rods (MSRs) were customized to immobilize various immune-complex receptor proteins. Each image represents a progression of the MSR coated with each subsequent protein. Representative microscopy of uncoated MSRs 30-200um in size (FIG.21A). Biotin-liposome coated MSRs stained with AF647- Streptavidin (FIG. 21B). B-human CD64 coated MSRs stained with PE anti-CD64 antibody (FIG. 21C). Human anti-his / HA-his coated MSRs stained with AF647 Rabbit anti-HA antibody (FIG.21D) and B-CD320 coated MSRs stained with AF647 Goat anti-Human CD320 (FIG.21E).

[0036] FIG. 22 shows the production of influenza specific IgG antibodies using the artificial antigen presentation scaffolds as an antigen delivery system (ADS) as described herein. Tonsil cultures from two donors were stimulated on Day 0 with artificial antigen presentation scaffolds loaded with hemagglutinin (HA) influenza protein or soluble influenza protein alone (soluble HA). On Day 14, cultures were harvested and culture supernatants were screened for secreted influenza specific antibodies.

[0037] FIG.23 is a schematic diagram of an illustrative computing device with which aspects described herein may be implemented. DETAILED DESCRIPTION OF THE VARIOUS EMBODIMENTS

[0038] The present disclosure relates to in vitro mammalian lymphoid cell cultures and systems that accurately mimic the cellular and structural complexity of the in vivo mammalian immune system. As demonstrated herein, these cultures are capable of recapitulating B cell maturation and de novo antibody response to antigenic stimuli as well as candidate therapeutic molecules comprising immunogenic liabilities.

[0039] A first aspect of the present disclosure is directed to an in vitro system, where the system comprises: a plurality of mammalian lymphoid cell cultures. Each of the plurality of mammalian lymphoid cell cultures comprise lymphoid tissue-derived B cells and T cells in a cell culture well comprising culture media, and a candidate therapeutic molecule in the culture media. The plurality of lymphoid cell cultures collectively express a plurality of different major histocompatibility complex (MHC) proteins. In one embodiment, the plurality of lymphoid cell cultures collectively express a plurality of different MHC class II proteins.

[0040] In accordance with this and all aspects of the disclosure, each of the plurality of lymphoid cell cultures comprise lymphoid tissue derived B cells and T cells obtained from an individual mammalian donor, e.g., a human donor. In other words, each culture is a lymphoid tissue model of an individual mammalian donor. The lymphoid tissue derived B cells and T cells of a cell culture can be obtained from the tissue of any secondary lymphoid organ. Secondary lymphoid organs include, without limitation, lymph nodes, spleen, and tonsils. The lymphoid tissue derived B cells and T cells can alternatively be derived from secondary lymphoid tissue that is found within various mucous membrane layers of the body, e.g., the mucous membrane lining the intestinal tract, the respiratory tract, the urinary tract, etc. In one embodiment, the lymphoid tissue derived B cells and T cells are derived from tonsil tissue.

[0041] In accordance with this and all aspects of the disclosure, the plurality of lymphoid cell cultures are a plurality of mammalian lymphoid cell cultures, i.e., each culture comprising lymphoid tissue derived B cells and T cells obtain from a mammalian donor. In one embodiment, the mammalian donor is a human donor. In one embodiment, the mammalian donor is a non-human primate, e.g., a cynomolgus monkey (Macaca fascicularis) (referred to herein as “cyno”). Other suitable mammalian donors include, without limitation, rodents (e.g., mice and rats), dogs, cats, pigs, sheep, rabbits, and others. Accordingly, in any embodiment, the mammalian lymphoid cell cultures of the present disclosure include without limitation, human lymphoid cell cultures, non-human primate lymphoid cell cultures, rodent lymphoid cell cultures, canine lymphoid cell cultures, feline lymphoid cell cultures, Suidae lymphoid cell cultures, bovine lymphoid cell cultures, or Leporidae lymphoid cell cultures. In one embodiment, the mammalian lymphoid cell cultures of the present disclosure are human lymphoid cell cultures. In one embodiment, the mammalian lymphoid cell cultures of the present disclosure are non-human primate lymphoid cell cultures.

[0042] The lymphoid-tissue derived cells of the cell culture include B cells and T cells. B cells are a critical component of the immune system, responsible for the short-term and long-term generation of humoral antibody responses. B cells also are critical for antigen-presentation, modulation of T cell differentiation and survival, and the production of regulatory and pro- inflammatory cytokines. Lymphoid tissue-derived B cells include a heterogenous population of peripheral B cells, representing the different stages of B cell maturation. The B cell composition of the lymphoid cell cultures is not static, especially when utilized in the various methods described herein. The B cell composition of a lymphoid cell culture also varies based on the donor tissue from which it was derived. Accordingly, the lymphoid tissue-derived B cells of the cell cultures described herein include, without limitation, any combination of transitional B cells, naïve B cells, pre-germinal center B cells, germinal center B cells, marginal zone B cells, follicular B cells, plasma B cells, and memory B cells. Most B cells can be identified by their cell surface expression of the pan-B cell markers CD19 and CD20, and the lack of expression of certain non-B cell exclusion markers, such as CD3 (T cell marker) and CD14 (monocyte and macrophage marker). The identification of particular sub-populations of B cells can be determined by their phenotypic cell surface marker expression profile. For example, transitional B cells, which are bone-marrow derived, immature B cells that have emigrated to the periphery) can be identified by assessing the expression of one or more surface markers selected from CD10, CD19, CD20, CD24, CD28, CD38, BCL-1, and CD27, where the expression profile of these markers on transitional B cells comprises CD10+, CD19+, CD20+, CD24high, CD28high, CD38high, BCL-2low, and CD27–.

[0043] Naïve B cells are B cells that have not been exposed to an antigen. The presence of naive B cells in the lymphoid cell cultures described herein can be identified by assessing the expression of one or more surface markers selected from CD19, CD20, CD23, CD40, IgM, IgD, CD38, CD24, Cd27 and CD150, where the expression profile of these markers on naïve B cells comprises CD19+, CD20+, CD23+, CD40+, IgM+, IgD+, CD38+ / –, CD24+ / –, CD27–,CD150+. In one embodiment, naïve B cells can reliably be identified and distinguished from other B cell phenotypes by their CD27- / CD38- expression profile.

[0044] Marginal zone B cells, which are non-circulating mature B cells, can be identified by assessing the expression of one or more surface markers selected from CD1c, CD19, CD20, and CD27, where the expression profile of these markers on marginal zone B cells comprises CD1c+, CD19+, CD20+, and CD27+.

[0045] Follicular B cells are a mature B cell found in the follicles of secondary lymphoid organs that participate in T cell-dependent immune responses. The presence of follicular B cells in the lymphoid cell cultures described herein can be identified by assessing the expression of one or more surface markers selected from CD5, CD19, CD1d, CD23, CD43, IgM, and IgD, where the expression profile of these markers on follicular B cells comprises CD5–, CD19+, CD1d+, CD23+, CD43–, IgMlow, IgDhi.

[0046] Germinal center (GC) B cells are the B cells that produce high-affinity, class switched antibodies required for protective immunity. The presence of GC B cells in the lymphoid cell cultures described herein can be identified by assessing the expression of one or more surface markers selected from IgG, Fas, PNA, CD19, CD20, CD27 and CD38, where the expression profile of these markers on GC B cell comprises IgDlo, Fas+, PNA+, CD20+, CD19+, CD27+, CD38+. In one embodiment, GC B cells can reliably be identified and distinguished from other B cell phenotypes by their CD27+ / CD38+ expression profile. Pre-GC B cells can reliably be identified and distinguished from other B cell phenotypes by their CD27- / CD38+ expression profile.

[0047] Memory B cells are a differentiated population of B cells that emerge from germinal center and circulate in the periphery. The presence of memory B cells in the lymphoid cell cultures described herein can be identified by assessing the expression of one or more surface markers selected from CD19, CD20, CD27, CD40, IgA, IgG, CD23, CD150, and CD138, where the expression profile of these markers on memory B cells comprises CD19+, CD20+, CD27+, CD40+, IgA+, IgG+, CD23low, CD150–and CD138–. In one embodiment, memory B cells can reliably be identified and distinguished from other B cell phenotypes by their CD27+ / CD38- expression profile.

[0048] B cells of the cell cultures described herein also include plasmablasts and plasma B cells. Plasmablasts are proliferating, short-lived activated B cells that secrete antibodies while dividing. Plasmablasts, which mediate the early antibody response, arise from marginal zone B cells, follicular B cells, or memory B cells and may further mature into plasma cells. Plasma cells are non- dividing, terminally differentiated B cells that have emerged from matured, activated germinal center B cells. Plasmablasts and plasma cells can be identified in the lymphoid cell cultures described herein by a similar surface marker phenotype comprising CD19+ / –, IgD–, CD27high, CD38high, CD24–as well as by the expression of transcription factors BLIMP1, XBP1, and IRF4. Plasma cells also express high levels of CD138 (SDC1). In one embodiment, plasmablasts can reliably be identified and distinguished from other B cell phenotypes by their CD27+ / CD38highexpression profile.

[0049] As noted above, the B cell composition of the cell cultures of the system is not static. In one embodiment, the cell cultures of the system comprise plasmablasts (1-5% of total B cells), naïve B cells (~10-70% of total B cells), memory B cells (~1-20% of total B cells), GC B cells (~10-20% of all B cells), and pre-GC ( ~20-50% of total B cells). This cell culture system represents a culture without antigenic stimulation.

[0050] The B cell compositional profile of the cell culture may change after exposure to antigenic stimuli (e.g., at day 14 of culture with antigenic stimuli). In particular, there may be an increase in the proportion of plasmablasts in the culture and a decrease in the proportion of naïve and / or memory B cells. For example, the proportion of plasmablasts may increase from 1-5% of total B cells to 1-20% of the total B cells in the culture. Naïve and memory B cells may decrease to constitute <20% of the total B cells in the culture.

[0051] The mammalian (e.g., human) lymphoid cell cultures of the in vitro system described herein further comprise T cells, which are critical for the humoral immune response. Like B cells, T cells of the cell cultures described herein are a heterogenous population of various T cell types. The T cell composition of a culture is not static, especially when utilized in the methods described herein, and also varies depending on the donor tissue from which it is derived. T cells can generally be identified by the expression of the T cell receptor (TCR) and CD3, a component of the TCR complex. Particular T cell sub-populations of the lymphoid cell cultures described herein include, without limitation, CD4+ helper T cells and CD8+ T cells. Subsets of the CD4+ T cell population that can further be identified within the lymphoid cell cultures described herein include, follicular helper T cells, which can be characterized by the phenotypic expression profile comprising CD4+CXCR5+, or the expression profile comprising CD4+PD1+CXCR5+BCL6high. Non-follicular helper T cells can be characterized by the phenotypic expression profile comprising CD4+ / CXCR5-, or the expressionprofile comprising CD4+PD1 CXCR5 BCL6low. Pre-follicular helper T cells can be characterized bythe phenotypic expression profile comprising CD4+PD1+CXCR5 BCL6mid. T cells of the lymphoidcultures may be naïve cells, but transition to activated cells while in culture. In one embodiment, the T cell composition of the mammalian (e.g., human) lymphoid cell culture comprises a combination of CD8+ T cells, CD4+ T cells, and follicular helper T cells. In one embodiment, the T cell composition of the mammalian lymphoid cell culture comprises a CD4+ T cell population that is greater than (e.g., 2-fold greater) the CD8+ T cell population. In one embodiment, the T cell composition of the mammalian lymphoid cell culture comprises a follicular helper T cell population that is greater thanthe CD4+ T cell population. This T cell compositional profile is typical of early, unstimulated culture (e.g., D0 culture). In another embodiment, the T cell composition of the mammalian lymphoid cell culture comprises a CD4+ T cell population that is greater than (~2-fold greater) the follicular helper T cell population. This T cell compositional profile is typical of a culture stimulated with antigen.

[0052] In one embodiment, the mammalian (e.g., human) lymphoid cell culture is depleted of CD25+cells. In other words, the mammalian lymphoid cell culture comprises CD25–T cells, CD25–B cells, and CD25–myeloid cells (e.g., CD25–dendritic cells). CD25 (cluster of differentiation 25) is a part of the interleukin-2 (IL-2) receptor, i.e., IL-2 receptor subunit alpha (IL2-RA), that serves as cell surface marker of activated lymphocytes. CD25+ cell depletion of the mammalian lymphoid cell cultures can be achieved using commercially available antibodies and standard fluorescence-activated cell sorting (FACs) or magnetic-activated cell sorting (MACs) protocols.

[0053] In one embodiment, each of the plurality of mammalian (e.g., human) lymphoid cell cultures of the present disclosure further comprise additional lymphoid tissue-derived cells, including, without limitation follicular dendritic cells, dendritic cells, macrophages, endothelial cells, or any combination thereof. The presence of each of these cell populations can be identified by their characteristic cell surface marker phenotypes as described herein or known in the art.

[0054] In one embodiment, the mammalian (e.g., human) lymphoid cell cultures of the present disclosure further comprise follicular dendritic cells (FDCs). FDCs, which have a dendritic morphology but are not related to dendritic cells, are abundant in secondary lymphoid organs where they play an important role in presenting antigen to B cells. The presence of follicular dendritic cells in the lymphoid cell cultures described herein can be identified by the cell surface expression of one or more markers selected from CD45, CD5, CD21, CD23, CD90, PDPN, CD35, and CD31, where the expression profile of these markers on follicular dendritic cells comprises CD21+, CD23+, CD45-, CD90+, PDPN+, CD35+, CD5- and CD31-. Follicular dendritic cells are also CD3- and CD19-. Alternatively, the presence of follicular dendritic cells in lymphoid cell culture can be identified by the cell surface expression of one or more markers selected from CD21, CD23, CD35, and the absence of expression of cytokeratin and CD5.

[0055] In one embodiment, the mammalian (e.g., human) lymphoid cell cultures of the present disclosure further comprise dendritic cells. Dendritic cells play an essential role in antigen presentation in the generation of a primary immune response. Dendritic cells are identified by the cell surface marker phenotype of CD45+ MHC-II and CD11c and lack of CD3 and CD19 expression. Prominentmarkers of type-2 dendritic cells, the dominant dendritic subset in lymphoid tissue, include, without limitation, CD14, CD163, Clec10A, Clec9, CD11c, NOTCH2, ITGAM, SIRPA, CXCR1, CD1C, and CD2. In one embodiment, the presence of dendritic cells in the human lymphoid cell cultures are identified and distinguished by cell surface expression of CD11c and / or cell surface expression of CD45 and Clec9.

[0056] In one embodiment, the mammalian (e.g., human) lymphoid cell cultures of the present disclosure further comprise macrophages. Macrophages are identified by the cell surface marker expression of one or more markers selected from CD14, CD11b, CCR2, MHC-II, CD163, CD169, CD206, CX3CR1, Lyve1, CD9, and TREM2. In one embodiment, the presence of macrophages in the human lymphoid cell cultures are identified and distinguished by cell surface expression of CD14 and / or CD11b.

[0057] In one embodiment, the mammalian (e.g., human) lymphoid cell cultures of the present disclosure further comprise endothelial cells. Endothelial cells are identified by the cell surface expression of one or more markers selected from CD36, CD31, VEGFR, ICAM1 (CD54), CD34, CD45, Lyve-1, VCAM1 (CD106), VE cadherin, and von Willebrand factor.

[0058] In one embodiment, the lymphoid cell cultures of the system form germinal centercores within cell culture aggregates. The germinal center is a specialized microstructure that forms within SLTs in response to antigenic stimulation to produce antibody secreting plasma cells and memory B cells. Germinal centers are organized into two major zones, i.e., a dark zone and a light zone. In the dark zone, maturing B cells undergo gene mutations that modify their antigen receptors for binding to foreign antigen. The dark zone is characterized by a population of B cells expressing high levels of the chemokine receptor, CXCR4. The light zone of the germinal center is where B cells having high affinity antigen receptors are selected. The light zone is characterized by a B cell population that does not express CXCR4, and by the presence of CD35+follicular dendritic cells.

[0059] The presence of germinal center cores within the lymphoid cell cultures of the systemdescribed herein can be identified using markers of B cells (CD20), T cells (CD3), and a marker of germinal-center dark zones (CXCR4) and assessing the three-dimensional orientation of these cells in culture. As demonstrated in the Example herein, within the spontaneously forming tonsil cell aggregates, the lymphocytes arrange themselves such that the B cells exist primarily within the core of the aggregate while the T cells cluster around the periphery (see FIG. 3A). Importantly, CXCR4-positive cells are found only within the center of the aggregate and are surrounded by B cells which mimics a germinal center-like dark zone found within lymph nodes (see FIGs.3B and 3C).

[0060] Germinal center-like structure formation in the tonsil cultures can also be assessed bythe presence of spatially distinct populations of CD20+CXCR4+B cells (marker of germinal center dark zones) and CXCR4- B cells and CD35+follicular dendritic cells (marker of germinal center lightzone).

[0061] The in vitro system of the present disclosure comprises a plurality of human lymphoid tissue derived cell cultures, where each of the lymphoid tissue derived cell cultures (in the plurality of cultures) is derived from a different human donor. In one embodiment, the plurality of lymphoid cell cultures comprises at least two cell cultures wherein each culture is derived from a different human donor, at least three cell cultures wherein each culture is derived from a different human donor, at least four cell cultures wherein each culture is derived from a different human donor, at least five cell cultures wherein each culture is derived from a different human donor, at least six cell cultures wherein each culture is derived from a different human donor, at least seven cell cultures wherein each culture is derived from a different human donor, at least eight cell cultures wherein each culture is derived from a different human donor, at least nine cell cultures wherein each culture is derived from a different human donor, at least ten cell cultures wherein each culture is derived from a different human donor, at least fifteen cell cultures wherein each culture is derived from a different human donor, at least twenty cell cultures wherein each culture is derived from a different human donor, at least twenty- five cell cultures wherein each culture is derived from a different human donor, at least thirty cell cultures wherein each culture is derived from a different human donor, at least thirty-five cell cultures wherein each culture is derived from a different human donor, at least forty cell cultures wherein each culture is derived from a different human donor, at least forty-five cell cultures wherein each culture is derived from a different human donor, at least fifty cell cultures wherein each culture is derived from a different human donor. In one embodiment, the plurality of lymphoid cell culture comprises at least ten cell cultures wherein each culture is derived from a different human donor.

[0062] Each of the plurality of lymphoid cell cultures that make up the in vitro system described herein is derived from a different mammalian (e.g., human) donor. Individual donor-derived lymphoid cell cultures are selected to collectively express a plurality of different major histocompatibility complex (MHC) alleles to represent a diverse MHC population. The major histocompatibility complex of genes consists of a linked set of genetic loci encoding the proteins whichrecognize endogenous and exogenous proteins and present these proteins to T-cell receptors on T cells. MHC class II molecules are found in antigen presenting cells, including B cells, macrophages, and dendritic cells and are responsible for presenting exogenous proteins and pathogens to T cells. Presentation to T cells stimulates proliferation of CD4+ T-helper cells, which in turn stimulates B cell proliferation and differentiation into antibody producing plasmablasts and plasma cells. Thus, in one embodiment, each of the plurality of lymphoid cell cultures is derived from a different mammalian donor such that, collectively, the plurality of lymphoid cell cultures of an in vitro system express a plurality of different MHC class II alleles (i.e., each culture expresses the MHC class II allele of its donor). In humans, the MHC class II proteins are encoded by the human leukocyte antigen gene complex (HLA). HLAs corresponding to MHC class II include HLA-DR (HLA-DRA / HLA-DRB), HLA-DQ (HLA-DQA / HLA-DQB), HLA-DM, HLA-DO (HLA-DOA / HLA-DOB), and HLA-DP (HLA-DPA / HLA-DPB) loci. Thus, in one embodiment, the plurality of lymphoid cell cultures are a plurality of human lymphoid cell cultures, where each culture is derived from a different human donor such that, collectively, the plurality of human lymphoid cell cultures express a plurality of different HLA class II alleles. In one embodiment, each of the plurality of human lymphoid cell cultures are derived from a different human donor such that, collectively, the plurality of human lymphoid cell cultures express two or more different high frequency alleles of an HLA class II molecule selected from HLA-DR, HLA-DQ, HLA-DM, HLA-DO, and HLA-DP. A high frequency HLA allele is an allele that occurs commonly within a defined population, e.g., an allele present at a frequency of within a population. In one embodiment, the plurality of lymphoid cell cultures are a plurality of human lymphoid cell cultures, each culture derived from a different human donor, where the plurality of cultures collectively express at least two different high frequency HLA-DRB alleles, at least three different high frequency HLA-DRB alleles, at least four different high frequency HLA-DRB alleles, at least five different high frequency HLA-DRB alleles, at least six different high frequency HLA- DRB alleles, at least seven different high frequency HLA-DRB alleles, at least eight different high frequency HLA-DRB alleles, at least nine different high frequency HLA-DRB alleles, at least 10 different high frequency HLA-DRB alleles, at least eleven different high frequency HLA-DRB alleles, or at least twelve different high frequency HLA-DRB alleles. In one embodiment, the plurality of lymphoid cell cultures are a plurality of human lymphoid cell cultures collectively expressing at least ten different high frequency HLA-DRB alleles.

[0063] As described in more detail herein, a primary utility of the in vitro system of the present disclosure is to predict or determine the potential in vivo immunogenicity of a candidate therapeutic molecule in a human population. Since HLA type, particularly HLA II type, of an individual plays a key role in determining an immune response to any exogenous protein or molecule, the immunogenicity of a candidate therapeutic molecule is tested across a plurality of human lymphoid cultures derived from different human donors that represent the population diversity of HLA class II protein alleles. Such diversity across the cultures of the in vitro system enables an accurate determination of potential in vivo immunogenicity of a candidate molecule across one or more populations. Accordingly, in one embodiment, the in vitro system comprises a plurality of mammalian (e.g., human or cyno) lymphoid cultures, each culture derived from a different donor, wherein the plurality of cultures collectively express at least two different high frequency MHC class II alleles (e.g., at least two different high frequency HLA class II alleles), at least three different high frequency MHC class II alleles (e.g., at least three different high frequency HLA class II alleles), at least four different high frequency MHC class II alleles (e.g., at least four different high frequency HLA class II alleles), at least five different high frequency MHC class II alleles (e.g., at least five different high frequency HLA class II alleles), at least six different high frequency MHC class II alleles (e.g., at least six different high frequency HLA class II alleles), at least seven different high frequency MHC class II alleles (e.g., at least seven different high frequency HLA class II alleles), at least eight different high frequency MHC class II alleles (e.g., at least eight different high frequency HLA class II alleles), at least nine different high frequency MHC class II alleles (e.g., at least nine different high frequency HLA class II alleles), at least 10 different high frequency MHC class II alleles (e.g., at least 10 different high frequency HLA class II alleles), at least 15 different high frequency MHC class II alleles (e.g., at least 15 different high frequency HLA class II alleles. In one embodiment, the in vitro system comprises a plurality of human lymphoid cultures, each culture derived from a different human donor, where the plurality of cultures collectively express at least ten different high frequency HLA class II alleles.

[0064] The MHC class II protein composition (e.g., HLA class II-type) of a cell culture is a donor tissue dependent feature, and typically the MHC class II composition of the tissue is determined at the time donor tissue is collected. The MHC class II composition-type of an individual is determined using standard MHC-typing methodologies, including the detection of MHC (i.e., HLA) antibodies in serological samples using flow cytometry or solid phase separation techniques. Alternatively, theMHC allelic composition of an individual can be determined using standard genetic sequencing techniques, e.g., PCR or next generation sequencing.

[0065] In accordance with this and all aspects of the present disclosure, the lymphoid tissue- derived B cell and T cells are cultured in a cell culture well comprising culture media. The lymphoid tissue derived cells are preferably cultured in a standard flat, uncoated, polycarbonate cell culture well. The cells of the culture do not attach, adhere, or embed within the surface of the culture dish. Any culture media comprising a basal medium (e.g., IMDM, MEM, DMEM, RPMI 1640, Alpha Medium or McCoy's Medium, or an equivalent) supplemented with appropriate growth factors and cytokines to support growth of primary cells in culture is suitable for culturing the lymphoid tissue-derived cells of the present disclosure.

[0066] In some embodiments, the culture media of the lymphoid cell cultures comprises a serum component, as it is an important source of growth and adhesion factors, hormones, lipids and minerals. However, as demonstrated herein, the use of fetal bovine serum (FBS), which is a typical serum type for cell culture, can induce an immune response from the human lymphoid tissue-derived cells of the culture because it is a foreign protein. Therefore, in one embodiment, the cell culture media comprises a concentration of FBS that does not induce an immune response from the human lymphoid-tissue derived cells of the culture. This concentration minimizes or avoids a false positive readout of immunogenicity of the candidate therapeutic molecule also present in the culture media. In one embodiment, the cell culture media comprises a concentration of FBS that is less than 10%. In one embodiment, the concentration of FBS in the media is <9.5%, <8.5%, <8%, <7.5%, <7.0%, <6.5%. <6%, <5.5%, or <5%. In one embodiment, the culture media comprises a concentration of 7.5% FBS. As demonstrated herein, this concentration is sufficient to maintain cell culture health and reduce false detection of immune responsiveness of the culture.

[0067] In an alternative embodiment, the culture media of the lymphoid cell cultures comprises human serum to avoid or further minimize non-warranted (non-antigen specific) immune cell responsiveness in the human lymphoid-tissue derived cell culture. In one embodiment, the concentration of human serum in the media is less than 10%. In one embodiment, the concentration of human serum in the media is <9.5%, <8.5%, <8%, <7.5%, <7.0%, <6.5%. <6%, <5.5%, or <5%. In one embodiment, the culture media comprises a concentration of 7.5% human serum.

[0068] In one embodiment, the culture media of the lymphoid cell cultures further comprises a B cell survival factor. A B cell survival factor plays a critical role in controlling B cell proliferation,maturation, and survival within the cell cultures of the present disclosure. In one embodiment, the B cell survival factor is a B cell-activating receptor factor receptor (BAFFR) agonist. The BAFFR is encoded by the TNFRSF13C gene and is a primary pro-survival receptor on B cells. In one embodiment, the BAFFR agonist is the natural ligand for the BAFF receptor, i.e., B cell-activating factor (BAFF). In one embodiment, the BAFFR agonist is a human BAFFR agonist. Human BAFF is a 285 amino acid protein (UniProt. Accession No. Q9Y275) that binds as a trimer to BAFFR. In one embodiment, the BAFFR agonist is a recombinant or synthetically produced mammalian (e.g., human or cyno) BAFF protein, fusion protein, or active fragment thereof. In one embodiment, the BAFFR agonist is a recombinant or synthetically produced human BAFF protein, fusion protein, or active fragment thereof. In one embodiment, the BAFFR agonist is a small molecule mammalian BAFFR agonist. In one embodiment, the BAFFR agonist is a mammalian BAFFR agonist antibody

[0069] In one embodiment, the culture media of the lymphoid cell cultures further comprises interleukin 4 (IL-4). Human IL-4 is a 153 amino acid cytokine (UniProt. Accession No. P05112) typically secreted by mast cells, T cells, eosinophils and basophils to regulate antibody production, hematopoiesis and inflammation, and the development of effector T cell responses. IL-4 is also known to induce the expression of MHC class II molecules on B cells. In one embodiment, IL-4 is a recombinant or synthetically produced mammalian (e.g., human or cyno) IL-4 protein, fusion protein, or active fragment thereof. IL-4 supplementation of the culture media aids in maintaining the naïve B cell population, thereby reducing background, non-specific cell activation and / or proliferation.

[0070] In one embodiment, the culture media of the lymphoid cell cultures further comprises granulocyte-macrophage colony-stimulating factor (GM-CSF). Human GM-CSF is a 144 amino acid cytokine (UniProt. Accession No. P04141) that stimulates growth and differentiation of hematopoietic precursor cells from various lineages. In one embodiment, GM-CSF is a recombinant or synthetically produced mammalian (e.g., human or cyno) GM-CSF protein, fusion protein, or active fragment thereof. GM-CSF supplementation of the culture media aids in the reduction of background, non- specific cell activation and / or proliferation

[0071] In one embodiment, the culture media of the lymphoid cell cultures is supplemented during culture with one or more cytokines that help drive B cell differentiation into antibody secreting plasmablasts. In accordance with this embodiment, the culture media of the lymphoid cell cultures can be supplemented with one or more cytokines selected from interleukin 10 (IL-10), interleukin-6 (IL-6), interleukin-2 (IL-2), interleukin-21 (IL-21), and interleukin-15 (IL-15). Preferably, the cellculture media is supplemented with one or any combination of these cytokines at about day 4, day 5 or day 6 in culture. In one embodiment, the lymphoid cell culture comprising CD25- immune cells (e.g., CD25–B cells and T cells) is cultured from day 0 in a cell culture media comprising IL-4 and the culture media is supplemented between day 4–5 with IL-10, IL-6, IL-2, IL-21, IL-15 or a combination thereof. Cytokine concentration within the cell culture media ranges from about 25 ng / mL to about 200 ng / mL.

[0072] In accordance with this and all aspects of the present disclosure, the lymphoid tissue- derived B cell and T cells are cultured in a cell culture well comprising culture media containing a candidate therapeutic molecule. As referred to herein a “candidate therapeutic molecule” is a molecule at any stage of research or development for the treatment or modulation of a disease or disorder. A candidate therapeutic molecule is not intended to induce an immune response in a human subject. For purposes of the present disclosure, vaccines and other molecules specifically designed to induce, enhance, or stimulate an immune response are excluded from the definition of “candidate therapeutic molecule.”

[0073] In one embodiment, the candidate therapeutic molecule is a candidate therapeutic molecule composed of biological components, e.g., amino acids, nucleic acids, carbohydrates, and lipids. In one embodiment, the candidate therapeutic molecule is not a small molecule therapeutic. In one embodiment, the candidate therapeutic molecule is a candidate protein therapeutic. Protein therapeutics include proteins and peptides, e.g., enzymes and regulatory proteins, that are administered to replace a particular protein that is deficient or abnormal in the subject, to augment an existing protein function, or to provide a novel function or activity. Suitable proteins can be recombinantly produced or isolated from their native source. The protein therapeutic can be a full-length protein or comprise an active fragment thereof. In one embodiment, the protein is a fusion protein, where the therapeutic protein is coupled to another protein portion or non-protein portion, e.g., pegylated portion. The protein therapeutic is typically a human protein, but can also be a non-human protein that has been engineered to be non-immunogenic when administered to a human.

[0074] Other candidate protein therapeutics suitable for testing in the in vitro system and methods described herein include targeted proteins therapeutics, e.g., antibodies (mono-, bi-, and tri- specific antibodies, antibody fragments (Fv, Fc, Fab, F(ab)2, VHH), antibody derivatives (e.g., scFvs), receptor ligand proteins, and immunoadhesions. In one embodiment, the targeted protein therapeutic is a human or humanized targeted protein therapeutic.

[0075] In one embodiment, the candidate therapeutic molecule is nucleic acid molecule, e.g., a molecule composed of deoxyribonucleic acid residues, ribonucleic acids, peptide nucleic acid residues, or any combination thereof. Suitable candidate therapeutic nucleic acid molecules are nucleic acid molecules, e.g., siRNA, shRNA,, microRNA, antisense oligonucleotides, aptamers, all designed, from a sequence perspective, to avoid immunogenic or antigenic motifs. Suitable candidate nucleic acid therapeutic molecules include nucleic acid molecules housed or coupled to a delivery vehicle, e.g., viral or non-viral vector based delivery vehicles, and encapsulating vehicles made of polymers, lipids and lipid nanoparticles or the like.

[0076] In one embodiment, the candidate therapeutic molecule is a protein or nucleic acid therapeutic as described above, that has been screened by one or more in silico or in vitro assays of immunogenicity and identified as having low to no immunogenicity risk. These assays include, without limitation, in silico screening algorithms that detect sequence based liabilities (i.e., antigenic or potentially immunogenic sequence motifs), and in vitro cell-based assays that measure dendritic cell internalization, dendritic cell activation or antigen presentation, and T cell activation. In one embodiment, the candidate therapeutic molecule is a molecule that has been identified as having low to no immunogenicity risk as measured by a standard in vitro T cell activation assay or dendritic cell (DC) activation assay, such as a dendritic cell (DC)-T cell assay. The DC:T cell assay involves culturing dendritic cells, derived from various donor peripheral blood mononuclear cell (PBMC) samples, with the candidate therapeutic molecule, and further inducing a mature phenotype by culture in a defined media. PBMCs from the same donors are labeled with a T cell marker and co-cultured with the corresponding antigen-primed DC for several days. Any change in the proliferation or activation state of the labeled T cells, i.e., an increase in CD4+ T cell proliferation, is detected via flow cytometry and used to assess the potential immunogenicity of the candidate therapeutic molecule. In one embodiment, the candidate therapeutic molecule is a molecule that was tested in the DC:T cell assay and did not cause a significant increase in CD4+ T cell proliferation, and therefore, was considered non-immunogenic by this assay.

[0077] In one embodiment, the candidate therapeutic molecule is a molecule that has been identified as having low to no immunogenicity risk as measured by a standard in vitro PBMC activation assay. This cell assay involves culturing peripheral blood mononuclear cell (PBMC) samples derived from various donors, with the candidate therapeutic molecule, and detecting CD3+CD4+T cell proliferation. Any change in the proliferation or activation state of the labeled Tcells, i.e., an increase in CD3+CD4+T cell proliferation, is detected via flow cytometry and used to assess the potential immunogenicity of the candidate therapeutic molecule. In one embodiment, the candidate therapeutic molecule is a molecule that was tested in the PBMC cell assay and did not cause a significant increase in CD3+CD4+T cell proliferation, and therefore, was considered non- immunogenic by this assay.

[0078] In one embodiment, the candidate therapeutic molecule is a molecule that has been identified as having low to no immunogenicity risk as measured by a standard in vitro pre-anti-drug antibody assay. This assay involves culturing B cell containing cell samples from various donors with the candidate therapeutic molecule and detecting the production of anti-drug antibodies by the cell samples. In one embodiment, the candidate therapeutic molecule is a molecule that was tested in the pre-ADA cell assay and did not cause a pre-ADA response, and therefore, was considered non- immunogenic by this assay

[0079] In one embodiment, the candidate therapeutic molecule is present in the culture media of the lymphoid tissue-derived cell cultures at a concentration of about 100 nM to about 1 mM. In one embodiment, the candidate therapeutic molecule is present in the culture media at a concentration of about 100 nM, about 200 nM, about 300 nM, about 400 nM, about 500 nM, about 600 nM, about 700 nM, about 800 nM, about 900 nM, or about 1 mM. In one embodiment, the candidate therapeutic molecule is present in the culture media at a concentration of about 100nM to about 800 nM, about 100 nM to about 500 nM, or about 100 nM to about 300 nM.

[0080] Another aspect of the present disclosure is directed to an in vitro method of predicting in vivo immunogenicity of a candidate therapeutic molecule utilizing the in vitro system describe supra. In particular, this method comprises providing a plurality of mammalian lymphoid cell cultures, e.g., human lymphoid cell cultures, each cell culture comprising lymphoid tissue derived B cells and T cells in culture media, where the plurality of lymphoid cell cultures collectively express a plurality of different MHC alleles (e.g., a plurality of different HLA class II alleles). The method further involves administering a first and second dose of the candidate therapeutic molecule to each of the plurality of cell cultures, where the second dose is administered between 3–7 days after administering the first dose. The cells, the culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures are harvested after administering the second dose of the candidate therapeutic molecule and one or more markers of a de novo immune response is assessed in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures.In vivo immunogenicity of the candidate therapeutic molecule is determined based on the assessment of the one or more markers of the de novo immune response across the plurality of cell cultures.

[0081] In accordance with this aspect of the disclosure, the suitable composition and source of the plurality of mammalian (e.g., human) lymphoid cell cultures comprising lymphoid tissue-derived B and T cells in culture media is described supra in the context of the in vitro system of the disclosure. In a preferred embodiment, the mammalian lymphoid cell cultures are depleted of CD25+cells to produce a mammalian lymphoid cell culture comprising CD25–immune cells.

[0082] In one embodiment, the day the lymphoid tissue-derived B and T cells (e.g., CD25–cells) are introduced into the cell culture well comprising cell culture media is considered day 0 of culture. In one embodiment, the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture. A candidate therapeutic molecule is administered to the plurality of cell cultures by adding it to the cell culture media and ensuring that it is evenly distributed throughout the volume of the media via gentle mixing or agitation of the media. Suitable candidate therapeutic molecules to be administered to the plurality of cell cultures are described supra. The candidate therapeutic molecule is administered in an amount to achieve a final concentration of about 100 nM to about 1000 nM, or about 100 nM to about 800 nM or about 100 nM to about 500 nM, or about 100 nM to about 300 nM in the cell culture media of each of the plurality of cell cultures.

[0083] In one embodiment, the plurality of mammalian (e.g., human) lymphoid cell cultures comprising lymphoid tissue-derived CD25–cells are cultured, starting at day 0, in a cell culture media comprising the first dose of the candidate therapeutic molecule and IL-4. In one embodiment, after culturing the plurality of cell cultures in cell culture media comprising IL-4 for a period of 3-7 days, the cell culture media is optionally supplemented with one or more cytokines selected from interleukin-10 (IL-10), interleukin-6 (IL-6), interleukin-2 (IL-2), interleukin-21 (IL-21), and interleukin-15 (IL-15). An effective concentration of the one or more cytokines in the cell culture media ranges from 25 ng / mL to 200 ng / mL. As described in the Examples herein, it was discovered that depletion of CD25+ cells (i.e., regulatory B cells, activated T cells, and / or TREGs) coupled with IL-4 media supplementation reduces background, non-candidate therapeutic molecule specific cell activation, and helps maintain naïve B cells. Additionally, supplementing the cell cultures with one or more of the aforementioned cytokines (i.e., IL-10, IL-6, IL-2, IL-21, IL-15, or any combination thereof) aids B cell differentiation into antigen-specific antibody secreting cells.

[0084] As noted above, a second dose of the candidate therapeutic is administered to each of the plurality of cell cultures about 3 to 7 days after administering the first dose of the candidate therapeutic. In one embodiment, the second dose of the therapeutic candidate molecule is administered 3 days after the first dose. In one embodiment, the second dose of the therapeutic candidate molecule is administered 4 days after the first dose. In one embodiment, the second dose of the therapeutic candidate molecule is administered 5 days after the first dose. In one embodiment, the second dose of the therapeutic candidate molecule is administered 6 days after the first dose. In one embodiment, the second dose of the therapeutic candidate molecule is administered 7 days after the first dose.

[0085] In one embodiment, a third dose of the candidate therapeutic molecule is administered to each of the plurality of cell cultures. In one embodiment, the third dose is administered 3 days after the second dose of the candidate therapeutic molecule is administered to the cell cultures. In one embodiment, the third dose is administered 4 days after the second dose of the candidate therapeutic molecule is administered to the cell cultures. In one embodiment, the third dose is administered 5 days after the second dose of the candidate therapeutic molecule is administered to the cell cultures. In one embodiment, the third dose is administered 6 days after the second dose of the candidate therapeutic molecule is administered to the cell cultures. In one embodiment, the third dose is administered 7 days after the second dose of the candidate therapeutic molecule is administered to the cell cultures.

[0086] In one embodiment, the in vitro method of predicting immunogenicity of a candidate therapeutic molecule involves administering three doses of the candidate therapeutic molecule. In accordance with this embodiment, the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 or day 1 of culture, the second dose of the candidate therapeutic molecule is administered 3–7 days after the first dose is administered, and the third dose of the candidate therapeutic molecule is administered 3–4 days after the second dose is administered. In one embodiment, the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture, the second dose of the candidate therapeutic molecule is administered on day 3, 4, 5, 6, or 7 of culture, and the third dose of the candidate therapeutic molecule is administered on day 6, 7, 8, 9, 10, or 11 of culture. In one embodiment, the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture, the second dose is administered on day 4, 5, 6, or 7 of culture, and the third dose of the candidate therapeutic molecule is administered 3 days after the second dose. In a preferred embodiment, the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture,the second dose is administered on day 7 of culture, and the third dose of the candidate therapeutic molecule is administered on day 10 of culture.

[0087] The method of predicting in vivo immunogenicity of a candidate therapeutic molecule as described herein is based on the induction of a de novo immune response by the lymphoid tissue- derived cells of the cell culture. Assessing a de novo immune response can be achieved by evaluating one or more markers of the immune response in the harvested cells of the cell culture, the harvested cell culture supernatant of the culture, or in both the harvested cells and the harvested cell culture supernatant. Accordingly, the cells and / or culture supernatant are harvested 3–5 days following administration of the last dose of the candidate therapeutic molecule, i.e., 3–5 days following administration of the second dose or the third dose. In one embodiment, the first dose of the candidate therapeutic molecule is administered on day 0 or day 1 of culture, the second dose of the candidate therapeutic molecule is administered 3–7 days after the first dose is administered, the third dose of the candidate therapeutic molecule is administered 3–4 days after the second dose is administered, and the cells and / or culture supernatant are harvested 3–5 days after the third dose is administered. In one embodiment, a first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture, the second dose is administered on day 3, 4, 5, 6, or 7 of culture, the third dose of the candidate therapeutic molecule is administered 3 days after the second dose, and the cells and culture supernatant are harvested 4 days after the third dose is administered. In one embodiment, the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture, the second dose is administered on day 7 of culture, and the cells and / or culture supernatant are harvested between days 10-12 of culture. In one embodiment, the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture, the second dose is administered on day 7 of culture, the third dose of the candidate therapeutic molecule is administered on day 10 of culture, and the cells and / or culture supernatant are harvested on day 14 of culture.

[0088] As demonstrated in the Examples herein, it has been determined that a multi-dose administration schedule as described herein is critical to reliably generating a detectable de novo candidate therapeutic molecule-specific antibody response in the mammalian lymphoid tissue derived cell culture system. If the candidate therapeutic molecule is administered only once, or in some cases only twice, the de novo antibody response is not detectable, leading to a false negative readout of the marker being examined and a finding that the candidate therapeutic is not immunogenic. This isdemonstrated in FIG. 10B, where the number of plasmablast cells in the lymphoid cell culture administered a single dose of a novel antigen is relatively similar to the number of plasmablast cells in the corresponding control culture not exposed to the antigen (compare top scatterplots of FIG.10B). Only after three doses of the novel antigen, is a significant increase in the number of plasmablasts in the lymphoid cell culture observed in comparison to the corresponding control culture (compare bottom scatterplots of FIG. 10B). This multi-dosing administration schedule described herein is distinct from the single-dose administration schedule previously taught to be sufficient to detect a recall response in lymphoid tissue-derived cell cultures (see e.g., Wagar et al., Nature Medicine 27(1): 125-135 (2021)). As shown in FIG. 10A (top scatterplots), a single dose of a recall antigen generates a robust and detectable increase in the proportion of memory B cells and plasmablasts, which is consistent with previous reports. However, application of the multi-dose administration schedule in the context of examining a recall response is detrimental in that it drives exhaustion and near total depletion of plasmablasts as shown in FIG.10A, bottom scatterplots. Thus, the requirement of a multi- dosing administration schedule to detect a de novo antibody response is a unique feature of the system and methods described herein.

[0089] In addition to the multi-dose administration schedule, it was also discovered that the timing of the B cell survival factor introduction into the culture media of lymphoid tissue-derived cell cultures is important for the reliable generation of a detectable de novo antibody response to a candidate therapeutic molecule. As demonstrated in the Examples herein, delaying introduction of the B cell survival factor until at least day 3 of culture significantly improves the sensitivity of the cultures to generating a detectable de novo antibody response as measured, for example, by IgM secretion (FIG.11A) or antigen specific antibody production (FIG.11B). Accordingly, in one embodiment, the method of predicting in vivo immunogenicity involves introducing the B cell survival factor, e.g., the BAFF receptor agonist as described supra, into the culture media of each of the plurality of lymphoid cell cultures at 3 to 5 days after the first dose of the candidate therapeutic molecule. In one embodiment, the B cell survival factor is not administered on day 0 of culture, and is first introduced to the cultures at day 3 of culture. In one embodiment, the B cell survival factor is not administered on day 0 of culture, and is first introduced to the cultures at day 4 of culture. In one embodiment, the B cell survival factor is not administered on day 0 of culture, and is first introduced to the cultures at day 5 of culture.

[0090] Following the first introduction of the B cell survival factor to the lymphoid cell cultures, the cell cultures are periodically supplemented with the B cell survival factor to maintain a constant concentration of the B cell survival factor in each of the plurality of lymphoid cell cultures. In one embodiment, the concentration of the B cell survival factor, e.g., the BAFF receptor agonist, is maintained at a concentration of 0.01-5.0 μg / mL in each of the plurality of lymphoid cell cultures. In one embodiment, the concentration of the B cell survival factor, e.g., the BAFF receptor agonist, is maintained at a concentration of 0.1-1.0 μg / mL in each of the plurality of lymphoid cell cultures.

[0091] As described supra, immunogenicity of the candidate therapeutic molecule is predicted by assessing one or more markers of a de novo immune response. As referred to herein, “predicting” in vivo immunogenicity of a candidate therapeutic molecule means to determine the likelihood that the candidate therapeutic molecule will induce an immune response in a living organism, e.g., a human, upon administration. In some embodiments, the methods described herein determine the likely magnitude of that immune response in a living organism, e.g., a human. Markers of a de novo immune response, which are described below in more detail, include, without limitation, (i) the presence of anti-candidate therapeutic molecule antibody secreting cells in the harvested cells from the lymphoid cell cultures; (ii) the presence of anti-candidate therapeutic molecule antibodies in the harvested cell culture supernatant; (iii) an increase in frequency of plasmablasts in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of plasmablasts in corresponding control cell cultures (not administered the candidate therapeutic molecule); (iv) an increase in frequency of germinal center (GC) B cells in harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of GC B cells in corresponding control cell cultures; (v) an increase in frequency of GC B cells and plasmablasts in harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of GC B cells and plasmablasts in corresponding control cell cultures; (vi) an increase in frequency of CD4+T cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of CD4+T cells in corresponding control cell cultures; (vii) an increase in frequency of T follicular helper cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of T follicular helper cells in corresponding control cell cultures; (viii) an increase in T follicular helper cell function and / or proliferation in harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures; and (ix) an increase in the frequency of dendritic cells and / or macrophages in theharvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of dendritic cells and / or macrophages, respectively, in corresponding control cell cultures. In one embodiment, immunogenicity of a candidate therapeutic molecule is determined by assessing one of the markers of a de novo immune response as described herein. In one embodiment, immunogenicity of a candidate therapeutic molecule is determined by assessing at least two different markers of a de novo immune response as described herein. In one embodiment, immunogenicity of a candidate therapeutic molecule is determined by assessing at least three of the markers of a de novo immune response as described herein.

[0092] In one embodiment, the marker of a de novo immune response is the presence of anti- candidate therapeutic molecule antibodies (i.e., anti-drug antibodies) secreted by plasmablasts of the lymphoid cell culture into the cell culture supernatant. In one embodiment, the presence of anti- candidate therapeutic molecule antibodies can be assessed using a standard enzyme-linked immunosorbent assay (ELISA) technique (e.g., the ELISpot Assay as described in the Examples herein) or any other standard binding assay known in the art. For example, the presence of anti- candidate therapeutic molecule antibodies can be assessed by contacting the harvested culture supernatant with a solid support comprising an immobilized candidate therapeutic molecule. If anti- candidate therapeutic molecule antibodies are present in the culture supernatant, they will bind the immobilized candidate therapeutic molecule thereby becoming immobilized on the solid support. The immobilized antibodies are contacted with a detectable secondary antibody molecule, e.g., a labeled or tagged anti-IgG or detectable anti-IgM antibody. Detection of the detectable secondary antibody on the solid support indicates that anti-candidate therapeutic molecule antibodies are present in the culture supernatant, which is a positive indicator of a de novo immune response. Solid supports suitable for capturing anti-candidate therapeutic molecule antibodies from the supernatant for binding characterization can be formed from any porous or non-porous material, including, but not limited to materials such as silica, glass, metal (e.g., silver, gold, titanium), ceramic, plastic, or polymeric material (e.g., poly(methyl methacrylate) (PMMA), polyvinylidene fluoride (PVDF), polystyrene, polyurethane acrylate, polydimethylsiloxane (PDMS), polycarbonate, and cycloolefin copolymers (COC)), or any combination of these materials). Suitable solid supports can be in the form of a column, membrane, filter, beads, particles, etc.

[0093] In another embodiment, the presence of anti-candidate therapeutic molecule antibodies can be assessed by contacting the harvested culture supernatant with a solid support comprising asuitable capture agent, e.g., an anti-human Fc antibody. If anti-candidate therapeutic molecule antibodies are present in the culture supernatant, they will bind the immobilized capture agent thereby becoming immobilized on the solid support. The immobilized antibodies are then contacted with a detectable candidate therapeutic molecule, e.g., a candidate therapeutic molecule coupled to a detectable label or tag. Detection of the labeled candidate therapeutic molecule on the solid support indicates that anti-candidate therapeutic molecule antibodies are present in the culture supernatant, which is a positive indicator of a de novo immune response. Solid supports suitable for immobilizing anti-candidate therapeutic molecule antibodies from the supernatant for binding characterization can be formed from any porous or non-porous material, including, but not limited to materials such as silica, glass, metal, ceramic, plastic, or polymeric material (e.g., poly(methyl methacrylate) (PMMA), polyvinylidene fluoride (PVDF), polystyrene, polyurethane acrylate, polydimethylsiloxane (PDMS), polystyrene, polycarbonate, and cycloolefin copolymers (COC)), or any combination of these materials. Suitable capture agents for immobilizing antibodies of the supernatant onto the solid support include any capture agent that can bind an antibody. In one embodiment, the capture agent is an anti-human Fc antibody, e.g., anti-IgG antibody, anti-IgM antibody, or anti-IgE antibody which are capable of binding to human IgG, IgM or IgE antibodies, respectively. Alternatively, the capture agent can be protein A or protein G, which are also known to bind human antibodies.

[0094] In one embodiment, the plasmablast population of the cultures is isolated and total RNA and / or DNA is obtained from the isolated population of cells. Sequencing the isolated RNA and / or DNA from the plasmablasts provides the nucleic acid and / or amino acid sequence of the anti- candidate therapeutic antibodies produced by the plasmablasts.

[0095] The presence of a positive marker of immunogenicity, e.g., the presence of anti- candidate therapeutic molecule antibodies in the harvested cell culture supernatant, in >10%, >20%, >30%, >40% or >50% of the plurality of lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. In one embodiment, the presence of one or more positive markers of immunogenicity in an indicator of potential in vivo immunogenicity of the candidate therapeutic molecule. In one embodiment, the indicator of potential in vivo immunogenicity of the candidate therapeutic molecule. In onecultures tested is an indicator of potential in vivo immunogenicity of the candidate therapeutic molecule.

[0096] In one embodiment, the marker of a de novo immune response is determined by detecting the presence of anti-candidate therapeutic molecule antibody secreting cells within a population of lymphoid cell cultures administered the candidate therapeutic molecule. Detection of anti-candidate therapeutic molecule antibody secreting cells (ASCs) is a positive marker of a de novo immune response. The presence of anti-candidate therapeutic molecule ASCs in the lymphoid cell culture can be assessed using a standard ELISpot technique as described in the Examples herein. Briefly, following treatment, harvested cells are incubated in the presence of the immobilized candidate therapeutic molecule. Antibodies specific to the candidate therapeutic molecule secreted from the harvested cells bind to the immobilized candidate therapeutic molecule and are detected with the appropriate labeled secondary antibody (anti-IgG or anti-IgM antibody). The level of detected anti-candidate therapeutic molecule antibodies is indicative of the number of ASCs in the population. This level is compared to the detected level of corresponding antibodies in control cultures comprised of lymphoid tissue-derived cells from the same donor that were not administered the candidate therapeutic molecule. The detection of anti-candidate therapeutic molecule antibodies, and thus ASCs, in cultures exposed to the candidate therapeutic molecule compared to the control culture is a positive marker of a de novo immune response. The presence of anti-candidate therapeutic molecule ASCs in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. In one embodiment, the presence of anti- assessed in the method indicates the candidate therapeutic molecule will likely exhibit in vivo immunogenicity. In one embodiment, the presence of anti-candidate therapeutic molecule ASCs in 20% of the lymphoid cell cultures assessed in the method indicates the candidate therapeutic molecule will likely exhibit in vivo immunogenicity.

[0097] In one embodiment, the marker of a de novo immune response is a change in the proportion of plasmablasts (i.e., antibody producing B cells) in the cell culture. In one embodiment, an increase in the proportion or frequency of plasmablasts relative to the total B cell population is a positive marker of a de novo immune response. In accordance with this embodiment, the cell culture administered the candidate therapeutic molecule and a corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample. These cell cultures are cultured inparallel under the same conditions such that the only difference between them is the exposure to the candidate therapeutic molecule. The proportion of plasmablasts in these cell cultures following treatment with a candidate therapeutic molecule or negative control molecule is assessed by harvesting the cells and labeling the harvested cells with the appropriate cell surface markers to detect plasmablasts (CD27+ / CD38highcells) and total B cells (CD19+cells) of the culture. The proportion of plasmablasts in the culture exposed to the candidate therapeutic molecule is compared to the proportion of plasmablasts in the corresponding control culture that was not administered the candidate 1.5-fold increase in the proportion of plasmablasts in the cell cultures exposed to the candidate therapeutic molecule compared to the control culture is a positive marker of a de novo immune response. In one embodiment, the frequency of plasmablasts within a population is determined using FACs as described herein. An increase (e.g., -fold increase) in the plasmablast frequency in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. In one embodiment, -10% of the lymphoid cell cultures assessed isan indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the generalpopulation. - 20% of thelymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0098] In one embodiment, the marker of a de novo immune response is a change in the proportion of germinal center (GC) B cells in the cell culture. In one embodiment, an increase in the proportion or frequency of GC B cells relative to the total B cell population is a positive marker of a de novo immune response. In accordance with this embodiment, the cell culture administered the candidate therapeutic molecule and a corresponding control cell culture, comprise lymphoid tissue- derived cells from the same donor tissue sample. These cell cultures are cultured in parallel under the same conditions such that the only difference between them is the exposure to the candidate therapeutic molecule. The proportion of GC B cells in these cell cultures following treatment with a candidate therapeutic molecule or negative control molecule is assessed by harvesting the cells and labeling the harvested cells with the appropriate cell surface markers to detect GC B cells (CD27+ / CD38+cells) and total B cells (CD19+cells) of the culture. The proportion of GC B cells in the culture exposed to the candidate therapeutic molecule is compared to the proportion of GC B cells in the corresponding control culture that was not administered the candidate therapeutic molecule. A1.5-fold increase in the proportion of GC B cells in the cell cultures exposed to the candidate therapeutic molecule compared to the control culture is a positive marker of a de novo immune response. In one embodiment, the frequency of GC B cells within a population is determined using FACs as described herein. An increase in GC B cell frequency in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. -fold increase in the GC B cell 10% of the lymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population. -fold that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0099] In one embodiment, the marker of a de novo immune response is a change in the proportion of plasmablasts and germinal center B cells in the cell culture. In one embodiment, an increase in the proportion or frequency of plasmablasts and GC B cells relative to the total B cell population is a positive marker of a de novo immune response. In accordance with this embodiment, the cell culture administered the candidate therapeutic molecule and a corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample. These cell cultures are cultured in parallel under the same conditions such that the only difference between them is the exposure to the candidate therapeutic molecule. The proportion of plasmablasts and GC B cells in these cell cultures following treatment with a candidate therapeutic molecule or negative control molecule is assessed by harvesting the cells and labeling the harvested cells with the appropriate cell surface markers to detect plasmablasts (CD27+ / CD38highcells), GC B cells (CD27+ / CD38+cells) and total B cells (CD19+cells) of the culture. The proportion of plasmablasts and GC B cells in the culture exposed to the candidate therapeutic molecule is compared to the proportion of plasmablasts and GC B cells in the corresponding control culture that was not administered the candidate therapeutic -fold increase in the proportion of plasmablasts and GC B cells in the cell cultures exposed to the candidate therapeutic molecule compared to the control culture is a positive marker of a de novo immune response. In one embodiment, the frequency of plasmablasts and GC B cells within a population is determined using FACs as described herein. An increase in the plasmablast and GC B cell frequency in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. In one embodiment, a -fold increase in the plasmablast and GC B cell proportion 10% of thelymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population. -fold increase in the plasmablast therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0100] In one embodiment, the marker of de novo immune response is a change in the proportion or frequency of CD4+T cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures. In one embodiment, an increase in the proportion of CD4+T cells relative to the total T cell population (CD3+cells) is a positive marker of a de novo immune response to the candidate therapeutic molecule. In accordance with this embodiment, the cell culture administered the candidate therapeutic molecule and its corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample. These cell cultures are cultured in parallel under the same conditions such that the only difference between them is the exposure to the candidate therapeutic molecule. The proportion of CD4+T cells in these cell cultures is determined by labeling the cells in each culture with one or more cell specific markers to detect CD4+T cells and total T cells (CD4+ / CD8- / CD3+). The proportion of CD4+T cells in the culture exposed to the candidate therapeutic molecule is compared to the proportion of CD4+T cells in the corresponding control culture. A 1.5-fold increase in the CD4+T cell proportion in the cell culture administered the candidate therapeutic molecule as compared to the corresponding cell culture not receiving the candidate therapeutic molecule indicates the presence of a candidate therapeutic molecule specific immune response. In one embodiment, the frequency of CD3+, CD8-, and CD4+positive cells within a population is determined using FACs as described in the Examples herein. An increase in the CD4+T cell frequency in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. -fold increase in CD4+T cell proportion 10% of the lymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population. -fold increase in CD4+T cell proportion the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0101] In one embodiment, the marker of de novo immune response is an increase in the proportion of follicular helper T (Tfh) cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures. In accordancewith this embodiment, the cell culture administered the candidate therapeutic molecule and its corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample and cultured in parallel as described above. Tfh cells are a subset of CD4+ helper T cells that are involved in the regulation and development of antigen-specific B cell survival and proliferation. The proportion of Tfh cells in cell cultures administered the candidate therapeutic molecule (treated) and cell cultures not administered the candidate therapeutic is determined by labeling the cells in each culture with one or more cell specific markers to detect Tfh cells and total T cells. The proportion of Tfh cells in the culture exposed to the candidate therapeutic molecule is compared to the proportion of Tfh cells in the corresponding control culture. 1.5-fold increase in the Tfh cell proportion in the cell culture administered the candidate therapeutic molecule as compared to the corresponding cell culture not receiving the candidate therapeutic molecule indicates the presence of a candidate therapeutic molecule specific immune response. A suitable Tfh cell surface marker profile that can be utilized to determine the frequency of Tfh cells within a culture population includes, without limitation, CD4+and CXCR5+. The cell surface marker profile Tfh cells can further comprise one or more of the following markers, ICOS+, PD-1+, BLTA+, CD3+, CD8-, CD14-, CD19-, CD40 Ligand+, CD57 / B3GAT1+, CD84 / SLAMF5+, CXCR4+, IL-6 receptor alpha+, IL-21 receptor+, CD10+, OX40+, and SLAM / CD150+. In one embodiment, the frequency of Tfh positive cells within a population is determined using FACs. An increase in the Tfh cell frequency in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. -fold increase in CD4+CXCR5+Tfh cell proportion 10% of the lymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population. In one embodiment, a -fold increase in CD4+CXCR5+Tfh cell proportion is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0102] In one embodiment, the marker of a de novo immune response is an increase in the proportion of activated dendritic cells (DCs) in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures. In accordance with this embodiment, the cell culture administered the candidate therapeutic molecule and its corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample and cultured in parallel as described above. An increase in proportion of activated DCs in cellcultures administered the candidate therapeutic molecule and cell cultures not administered the candidate therapeutic or administered a negative control is determined by labeling the cells in each culture with one or more surface markers to detect activated DCs. The proportion of activated DCs in the culture exposed to the candidate therapeutic molecule is compared to the proportion of activated DCs 1.5-fold increase in the frequency of DCs in the cell culture administered the candidate therapeutic molecule as compared to a corresponding control cell culture not receiving the candidate therapeutic molecule indicates the presence of a candidate therapeutic molecule specific immune response. Suitable markers of DC activation include, without limitation, MHC class II, B7-1 / CD80, B7-2 / CD86, CD40 / TNFRS5, and CD83 expression. In one embodiment, the frequency of activated DCs within a population are determined using FACs. An increase in the frequency of activated DCs in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population.

[0103] In one embodiment, the marker of de novo immune response is an increase in frequency of macrophages in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures. In accordance with this embodiment, the cell culture administered the candidate therapeutic molecule and its corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample and cultured in parallel as described above. The frequency of macrophages in cell cultures administered the candidate therapeutic molecule and cell cultures not administered the candidate therapeutic or administered a negative control is determined by labeling the cells in each culture with one or more markers to detect macrophages. The proportion of macrophages in the culture exposed to the candidate therapeutic 1.5- fold increase in the proportion of activated macrophage in the cell culture administered the candidate therapeutic molecule as compared to a corresponding cell culture not receiving the candidate therapeutic molecule indicates the presence of a candidate therapeutic molecule specific immune response. Suitable markers of macrophage include, without limitation, CD14 and / or CD11b expression. In one embodiment, the frequency of macrophages within a population are determined using FACs. An increase in the frequency of macrophages in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population.

[0104] If a candidate therapeutic molecule is determined to induce a de novo immune response in the lymphoid cell cultures as described in the methods herein, a further aspect of the disclosure comprises characterizing the immune response to determine the immunogenic component of the candidate therapeutic molecule. In one embodiment, characterization of the immune response involves collecting the anti-candidate therapeutic molecule antibodies that are generated in response to administration of the candidate therapeutic molecule and determining the immunogenic B cell epitope of the candidate therapeutic molecule. Determining the B cell epitope(s) of the candidate therapeutic molecule can be achieved using low or high resolution epitope mapping techniques, including, without limitation, x-ray crystallography, cryo-electron microscopy (EM), hydrogen deuterium exchange (HDX) coupled to mass spectrometry (MS), and plasma induced modification of biomolecules (PLIMB). Once the B cell epitope of the candidate therapeutic molecule is determined, the epitope can be modified to partially or completely mitigate the immunogenicity of the candidate therapeutic molecule. These same methods (i.e., X-ray crystallography, cryo-EM, HDX-MS, and PLIMB) can also be utilized to determine the paratope of the anti-candidate therapeutic molecule antibodies. In some embodiments, methods of characterizing the anti-candidate therapeutic molecules involves first sequencing the antibodies to facilitate recombinant production of the antibodies or fragments thereof to have an amount of antibody sufficient to carry-out one or more characterization assays (e.g., epitope mapping).

[0105] Another aspect of the present disclosure is directed to a method of predicting in vivo immunogenicity of a candidate therapeutic molecule that involves assessing an early, surrogate marker of immunogenicity, e.g., T cell activation and / or proliferation. This method involves providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising IL4. In accordance with this method, the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles. The candidate therapeutic molecule is administered to each of the plurality of cell cultures, and the cells, the culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures are harvested 5-8 days after the candidate therapeutic molecule was administered. The method further involves measuring one or more markers of immune cell activation in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. The in vivo immunogenicity of the candidate therapeutic molecule is predicted based on the measured markers of immune cell activation.

[0106] In accordance with this embodiment of the disclosure, the candidate therapeutic molecule is only administered one time to each of the plurality of cell cultures at day 0, i.e., at the time cell culture is initiated. The candidate therapeutic molecule is added to the cell culture media comprising the IL-4, and optionally GM-CSF. In accordance with this method, no additional growth or cytokine supplements are added to the media over the course of 6-8 days, at which time the cells, cell culture supernatant, or both are collected and the one or more markers of immune cell activation are measured.

[0107] This method of predicting in vivo immunogenicity is more conducive to high- throughput screening and analysis as it examines one or more early surrogate markers of immunogenicity, i.e., B cell and / or T cell activation that precede a full immunogenic antibody response. In accordance with this aspect of the disclosure, suitable surrogate markers of immunogenicity include, without limitation, an increase in T cell expression of one or more activation proteins selected from HLA-DR, OX40, 41BB, CD25, PD-1, CD69, CD40 ligand, ICOS, CXCR5 or any combination thereof as described herein. Alternatively, a suitable surrogate marker of immunogenicity is CD4+ T cell proliferation, where an increase in CD4+ T cell proliferation in cell cultures which have been administered a candidate therapeutic molecule relative to a control culture is considered a positive marker of immunogenicity. CD4+ T cell proliferation can be examined in cell cultures using a known proliferation markers, including, without limitation, EdU, BrdU, CD69, CD127, Ki67, and CFSE, as described herein. In yet another embodiment, a suitable surrogate marker of immunogenicity is the production of cytokines associated with T cell activation. These cytokines include, without limitation IL2, Interferon gamma, IL21, TNF-alpha, and IL10

[0108] When assessing earlier markers of B cell and / or T cell activation, it is critical to reduce background proliferation in the unstimulated cultures. This reduction in background proliferation allows for accurate detection of these early markers. As described in the Examples, levels of background (non-candidate therapeutic molecule specific) cell activation in non-stimulated cultures can be high and variable across the donor-derived lymphoid cell cultures due to the heterogeneric donor population. High levels of background cell activation can interfere with the ability to detect candidate therapeutic molecule-induced response generated by the non-activated cells in the culture. Accordingly, it was discovered that depleting the tonsil tissue derived cells of CD25+ activated immune cells (B and T cells) prior to initial seeding significantly reduces this background proliferation. Additionally, culturing the CD25-depleted cell cultures in the presence of culture mediacontaining IL-4 alone or in combination with GM-CSF further lowers the background proliferation sufficiently to reproducibly and accurately detect B cell and / or T cell activation induced by a candidate therapeutic molecule.

[0109] In one embodiment, the marker of immune cell activation is an increase in T cell proliferation in harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of control cell cultures. In one embodiment, an increase in T cell proliferation is a positive marker of immune cell activation in response to the candidate therapeutic molecule. In accordance with this embodiment, the cell culture, which has been administered the candidate therapeutic molecule, and its corresponding control cell culture, comprise lymphoid tissue- derived cells from the same donor tissue sample. These cell cultures are cultured in parallel under the same conditions such that the only difference between them is exposure to the candidate therapeutic molecule. T cell proliferation in these cell cultures is determined by labeling the cells in each culture with a proliferation marker, e.g., thymidine analogs such as 5-ethynyl-2’-deoxyuridine (EdU) and bromodeoxyuridine (BrdU), or expression / phosphorylation of one or more proteins involved in cell proliferation including, but not limited to, Ki67 (a nuclear protein expressed during active phases of the cells cycle), Proliferating Cell Nuclear Antigen (PCNA), Minichromosome Maintenance Protein 2 (MCM2), and phosphor-histone H3. The proportion of CD4+T cells positive for the proliferation marker in the culture exposed to the candidate therapeutic molecule is compared to the proportion of CD4+T cells positive for the proliferation marker -fold increase in the CD4+proliferating T cell proportion in the cell culture administered the candidate therapeutic molecule as compared to the corresponding cell culture not receiving the candidate therapeutic molecule indicates the presence of candidate therapeutic molecule specific immune cell activation. In one embodiment, the frequency of CD4+proliferating T cells within a population is determined using FACs as described in the Examples herein. An increase in the CD4+proliferating T cell frequency in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. In one -fold increase in CD4+proliferating T cell proportion 10% of the lymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population. -fold increase in CD4+proliferating T cell proportion therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0110] In one embodiment, the marker of immune cell activation is an increase in T cell activation in harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of control cell cultures. In one embodiment, an increase in T cell activation is a positive marker of immune cell activation in response to the candidate therapeutic molecule. In accordance with this embodiment, the cell culture which has been administered the candidate therapeutic molecule and its corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample. These cell cultures are cultured in parallel under the same conditions such that the only difference between them is exposure to the candidate therapeutic molecule. T cell activation in these cell cultures is detected based on T cell expression levels of one or more T cell activation markers, including without limitation, expression levels of HLA-DR, OX40, 41BB, CD25, PD-1, CD69, CD40 ligand, ICOS, CXCR5 or any combination thereof. In one embodiment, the proportion of CD4+T cells positive for the activation marker in the culture exposed to the candidate therapeutic molecule is compared to the proportion of CD4+T cells positive for the activation marker -fold increase in the proportion of activated CD4+T cell in the cell culture administered the candidate therapeutic molecule as compared to the corresponding cell culture not receiving the candidate therapeutic molecule indicates the presence of candidate therapeutic molecule specific immune cell activation. In one embodiment, the frequency of activated CD4+T cells within a population is determined using FACs as described in the Examples herein. An increase in the activated CD4+T cell frequency in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. -fold increase in activated CD4+T cell proportion 10% of the lymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population. -fold increase in activated CD4+T cell proportion % of the lymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0111] In one embodiment, the level of activation marker expression in CD4+T cells of the culture exposed to the candidate therapeutic molecule is compared to the level of corresponding activation marker expression in CD4+-fold increase in the activated marker expression level in CD4+T cells of the cell culture administered the candidate therapeutic molecule as compared to the corresponding cell culture not receiving the candidate therapeutic molecule indicates the presence of candidate therapeutic molecule specificimmune cell activation. In one embodiment, the activation marker expression level in CD4+T cells within a population is determined using FACs. An increase in the activation marker expression level in CD4+T cells in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. In one -fold increase in activation marker expression level in CD4+T cells the lymphoid cell cultures assessed is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0112] In one embodiment, the marker of immune cell activation is an increase in cytokine production and secretion by harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of control cell cultures. Cytokines such as IL-2, IL-21 INF-TNF -10 are associated with CD4+ T cell activation. Therefore, an increase in production orsecretion of one or more of these cytokines serves as a positive marker of immune cell activation in response to the candidate therapeutic molecule. In accordance with this embodiment, the cell culture which has been administered the candidate therapeutic molecule and its corresponding control cell culture, comprise lymphoid tissue-derived cells from the same donor tissue sample. These cell cultures are cultured in parallel under the same conditions such that the only difference between them is exposure to the candidate therapeutic molecule. T cell activation in these cell cultures is detected based on expression and / or secretion of activation cytokines, including, without limitation, IL-2, IL-21 INF- -10 or any combination thereof. The level of cytokine production and / orsecretion in the culture exposed to the candidate therapeutic molecule is compared to corresponding cytokine production and / or secretion -fold increase in activation cytokine expression and / or secretion in the cell culture administered the candidate therapeutic molecule as compared to the corresponding cell culture not receiving the candidate therapeutic molecule indicates the presence of candidate therapeutic molecule specific immune cell activation. In one embodiment, cytokine expression by immune cells in the culture is determined using FACs as described in the Examples herein. An increase in cytokine expression and / or secretion in >10%, >20%, >30%, >40% or >50% of the lymphoid cell cultures assessed in the method is utilized to predict the risk of in vivo immunogenicity in the general population. - fold increase in cytokine expression and / or secretion is an indicator that the therapeutic molecule will likely exhibit in vivo immunogenicity in the general population.

[0113] Another aspect of the present disclosure is directed to a method of producing an in vitro immune responsive lymphoid cell culture. This method comprises subjecting isolated mammalian lymphoid tissue, e.g., human lymphoid tissue, to mechanical and enzymatic dissociation to produce a suspension of lymphoid tissue derived B cells, T cells, follicular dendritic cells, dendritic cells and endothelial cells. The method further comprises, introducing the suspension of lymphoid tissue derived cells, after the subjecting, into a cell culture well comprising cell culture media. The cell culture media comprises a candidate therapeutic molecule and does not contain a B cell survival factor. The B cell survival factor is added to the cell culture media at 3-5 days after the suspension of lymphoid derived cells are introduced into culture to produce the immune responsive lymphoid cell culture. The present disclosure is further directed to an in vitro mammalian lymphoid cell culture produced by this method. In one embodiment, the in vitro mammalian lymphoid cell culture produced by this method is a human lymphoid cell culture.

[0114] In accordance with this method, the isolated lymphoid tissue, e.g., human or cyno tonsil tissue, spleen tissue, or lymph tissue, is subjected to mechanical and enzymatic dissociation to produce a suspension of lymphoid tissue derived cells sufficient to generate an in vitro immune responsive lymphoid cell culture. These cells include lymphoid tissue-derived B cells and T cells. Preferably, these cells further include follicular dendritic cells, dendritic cells and endothelial cells. As demonstrated herein the combination of both mechanical and enzymatic dissociation methods are required to obtain the combination of B cells, T cells, follicular dendritic cells, dendritic cells and endothelial cells.

[0115] In accordance with this embodiment of the disclosure, mechanical dissociation can be achieved by cutting or slicing of lymphoid tissue into small pieces and further mechanically disrupting the tissue by crushing, pulverizing, vortexing, or processing through a strainer.

[0116] Enzymatic dissociation of the lymphoid tissue is carried out after the mechanical dissociation step and involves the use of specific protein enzymes to disaggregate cells within the tissue. The incorporation of this step was found essential to ensure the presence of dendritic cells and endothelial cells in the culture. Suitable enzymes to carry out enzymatic dissociation include, without limitation, trypsin, pronase, dispase, collagenase, and any combination thereof.

[0117] Following the mechanical and enzymatic dissociation steps, excess cell debris is removed by a series of washing and centrifugation steps to enrich the sample for the cells of interest. In one embodiment, CD25+ cells are removed from the cell sample. Removal of CD25+ cells from amammalian lymphoid cell sample can be achieved using standard cell separation techniques, e.g., using commercially available antibodies and standard fluorescence-activated cell sorting (FACs) or magnetic-activated cell sorting (MACs) protocols.

[0118] The cell sample enriched for CD25–immune cells is resuspended in the appropriate cell culture media and introduced into a suitable cell culture dish. In one embodiment, the cell culture media is supplemented with recombinant mammalian IL-4, e.g., recombinant human IL-4 at a concentration effective to suppress background levels of immune cell proliferation (i.e., non-test molecule related cell proliferation). A suitable concentration of IL-4 in the cell culture media comprises about 25 ng / mL to about 200 ng / mL. In one embodiment, the cell culture media is additionally supplemented with recombinant mammalian GM-CSF, e.g., recombinant human GM- CSF at a concentration effective to suppress background levels of immune cell activation (i.e., non- test molecule related cell activation and / or proliferation). A suitable concentration of GM-CSF in the cell culture media comprises about 25 ng / mL to about 200 ng / mL. The day the cells are introduced into the culture well is designated as day 0 of culture. At this time, the candidate therapeutic molecule is added to the cell culture media in the well containing the cells. Suitable candidate therapeutic molecules are described supra. The therapeutic molecule is added to the cell culture media in an amount to achieve a concentration of the candidate therapeutic molecule in the culture media of between about 100nM to about 1000 nM, or about 100 nM to about 800 nM, or about 100 nM to about 500 nM.

[0119] To generate a tonsil cell culture suitable for assessing candidate therapeutic molecule specific de novo immune responses, e.g. candidate therapeutic molecule-specific antibody production, delayed addition of a B cell survival factor, i.e., added three to five days after the cells are initially introduced into the cell culture dish, enhances the immune responsiveness of the cell culture. Accordingly, the B cell survival factor is not present in the cell culture media at the time the cells are introduced into the cell culture well. Accordingly, the B cell survival factor is first introduced into the cell culture media at day 2 of culture, at day 3 of culture, at day 4 of culture, at day 5 of culture, at day 6 of culture, or at day 7 of culture. In one embodiment, the B cell survival factor is introduced at day 3, at day 4 or at day 5 of cell culture. In one embodiment, the B cell survival factor is introduced at day 3 of cell culture. Following the introduction of the B cell survival factor into the cell culture, the cell culture is periodically supplemented with the B cell survival factor to maintain a constant concentration (e.g., between 0.1μg / mL–1.0μg / mL) of the B cell survival factor in the lymphoid cellculture. Periodic supplementing of the cell culture can be carried out every 2-4 days of culture. As described supra, suitable B cell survival factors include, without limitation, BAFFR agonists. In one embodiment, the B cell survival factor is BAFF. In one embodiment, the B cell survival factor is human BAFF.

[0120] As described supra, the lymphoid tissue-derived B cell and T cells are cultured in cell culture wells comprising culture media. The lymphoid tissue derived cells are preferably cultured in a standard flat, uncoated, polycarbonate cell culture well. The cells of the culture do not attach, adhere or embed within the surface of the culture dish. Any culture media comprising a basal medium (e.g., IMDM, MEM, DMEM, RPMI 1640, Alpha Medium or McCoy's Medium, or an equivalent) supplemented with appropriate growth factors and cytokines to support growth of primary cells in culture is suitable for culturing the lymphoid tissue-derived cells of the present disclosure.

[0121] In one embodiment, the cell culture media of the lymphoid cell cultures does not contain an adjuvant or any other strong immunostimulatory agent capable of inducing or enhancing an immune response in the lymphoid tissue-derived cells of the culture. However, this does not preclude the addition of one or more cytokines to the cell culture media that are typically present in vivo and aid plasma cell differentiation. Accordingly, in one embodiment, the cell culture media comprises one or more cytokines that aid B cell differentiation into antigen-specific antibody secreting cells. Suitable cytokines for media supplementation include, without limitation, IL-10, IL6, IL-2, IL- 21, IL15, and any combination thereof. A suitable concentration of these cytokines in the cell culture media comprises about 25 ng / mL to about 200 ng / mL. In one embodiment, the cell culture media is supplemented with one or more of these cytokines starting on day 3, day 4, day 5, or day 6 of culture and the supplementation is maintained for the remainder of the culture duration.

[0122] In some embodiments, the culture media of the lymphoid cell cultures comprises a serum component as it is an important source of growth and adhesion factors, hormones, lipids and minerals. However, as demonstrated herein, the use of fetal bovine serum (FBS), which is a typical serum type for cell culture, can induce an immune response from the lymphoid tissue-derived cells of the culture because it is a foreign protein. Therefore, in one embodiment, the cell culture media comprises a concentration of FBS that does not induce an immune response from the lymphoid-tissue derived cells of the culture. This will minimize or avoid false positive results regarding the potential immunogenicity of the candidate therapeutic molecule also present in the culture media. In one embodiment, the cell culture media comprises a concentration of FBS that is less than 10%. In oneembodiment, the concentration of FBS in the media is <9.5%, <9.0%, <8.5%, <8%, <7.5%, <7.0%, <6.5%. <6%, <5.5%, or <5%. In one embodiment, the culture media comprises a concentration of 7.5% FBS. As demonstrated herein, this concentration is sufficient to maintain cell culture health while not inducing an immune response in the culture, which is important to the accurate detection of candidate therapeutic molecule mediated immunogenicity.

[0123] In an alternative embodiment, the culture media of the lymphoid cell cultures, particularly human lymphoid cell cultures, comprises human serum to avoid or further minimize non- warranted immune cell responsiveness in the human lymphoid-tissue derived cell culture. In one embodiment, the concentration of human serum in the media is less than 10%. In one embodiment, the concentration of human serum in the media is <9.5%, <9.0%, <8.5%, <8%, <7.5%, <7.0%, <6.5%. <6%, <5.5%, or <5%. In one embodiment, the culture media comprises a concentration of 7.5% human.

[0124] Another aspect of the present disclosure is directed to an in vitro mammalian lymphoid cell culture. This cell culture comprises mammalian lymphoid tissue derived B cells and T cells, e.g., human lymphoid tissue derived B cells and T cells, in a cell culture well comprising culture media. The cell culture further comprises a candidate therapeutic molecule in the culture media. In one embodiment, the lymphoid cell culture further comprises plasmablasts and / or plasma cells, wherein the plasmablasts and / or plasma cells secrete anti-candidate therapeutic molecule antibodies. Methods and markers specific for identifying the presence of plasmablast and plasma cells in the culture and for identifying the presence of secreted anti-candidate therapeutic molecule antibodies are described supra. In one embodiment, the mammalian lymphoid cell culture is depleted of CD25+ cells. In one embodiment, the cell culture comprises human lymphoid tissue derived, CD24–B cells and T cells in a cell culture well comprising culture media, where the culture media is supplemented with IL-4. In one embodiment, the cell culture comprises human lymphoid tissue derived, CD24–B cells and T cells in a cell culture well comprising culture media, where the culture media is supplemented with IL-4 and further supplemented with IL-10, IL-6, IL-2, IL-21, IL-15, or a combination thereof.

[0125] Another aspect of the present disclosure is directed to an in vitro mammalian lymphoid cell culture. This cell culture comprises lymphoid tissue-derived B cells and T cells in a cell culture well comprising culture media. This cell culture further comprises an antigen and an antigen delivery system. In one embodiment, this mammalian lymphoid cell culture is a human lymphoid cell culture.

[0126] In one embodiment, the mammalian lymphoid cell culture is depleted of CD25+ cells. In one embodiment, the cell culture comprises human lymphoid tissue derived CD24–B cells and T cells in a cell culture well comprising culture media, where the culture media is supplemented with IL-4. In one embodiment, the cell culture comprises human lymphoid tissue derived CD24–B cells and T cells in a cell culture well comprising culture media, where the culture media is supplemented with IL-4 and further supplemented with IL-10, IL-6, IL-2, IL-21, IL-15, or a combination thereof.

[0127] The cell and cell culture media components of this in vitro lymphoid cell culture are described supra. In this embodiment, the lymphoid cell cultures are preferably human lymphoid cell cultures or lymphoid cell cultures capable of generating human antibodies (e.g., lymphoid cell culture derived from a transgenic animal capable of generating human antibodies). Unique to the lymphoid cell culture of this aspect of the present disclosure is the presence of the antigen and antigen delivery system as described below. The presence of the antigen and antigen delivery system facilitates an in vitro culture system for producing therapeutic antibodies. A fully human in vitro model for antibody discovery provides a means to overcome limitations associated with current in vivo antibody discovery models, e.g., XenoMouse. In particular, a human cell-based model will facilitate generation of appropriate immune responses to highly homologous antigen or structurally intractable antigens.

[0128] In one embodiment, the antigen delivery system comprises an artificial antigen presentation scaffold. This scaffold comprises a substrate and a lipid layer surrounding the substrate. The antigen delivery system further comprises the antigen, wherein the antigen is immobilized directly to a surface on the lipid layer. In an alternative embodiment, the antigen is immobilized to a surface on the lipid layer via an immune-complex. Accordingly, the antigen delivery system further comprises an immune complex that comprises (i) an immune-complex receptor protein, wherein the immune-complex receptor protein is immobilized to a surface on the lipid layer, and (ii) an immune- complex receptor ligand. The immune-complex receptor ligand is coupled to the antigen and is bound to the immobilized immune-complex receptor protein on the surface of the lipid layer. In either of these embodiments, this artificial antigen presentation scaffold mimics the functionality of follicular dendritic cells in the presentation of antigen to B cells in vivo to stimulate B cell survival, activation, and maturation.

[0129] In accordance with this aspect of the disclosure, the substrate of the artificial antigen presentation scaffold comprises a porous substrate material. Suitable porous substrate materials include, without limitation, biocompatible materials such as synthetic polymeric materials such aspolyesters, polyorthoesters, polylactic acid, polyglycolic acid, polycaprolactone, or polyanhydrides, including polymers or copolymers of glycolic acid, lactic acid, or sebacic acid. Substrates comprising silica particles or proteinaceous polymers are also suitable for use in the antigen delivery system described herein. Collagen gels, collagen sponges and meshes, and substrates based on elastin, fibronectin, laminin, or other extracellular matrix or fibrillar proteins may also be employed.

[0130] In one embodiment, the substrate of the artificial antigen presentation scaffold is a porous silica substrate, such as a mesoporous silica particle substrate. Mesoporous silica is a porous body with hexagonal close-packed, cylinder-shaped, uniform pores. This material can be synthesized by using a rod-like micelle of a surfactant as a template, which is formed in water by dissolving and hydrolyzing a silica source such as alkoxysilane, sodium silicate solution, kanemite, silica fine particle in water or alcohol in the presence of acid or basic catalyst (see e.g., U.S. Patent Appl. Pub. No. 20150072009 and Hoffmann et al., Angewandte Chemie International Edition, 45:3216-3251 (2006)). Suitable surfactants include, without limitation, cationic, anionic, and nonionic surfactants. In one embodiment, alkyl trimethylammonium salt of cationic surfactant is utilized to produce a mesoporous silica having a suitable specific surface area and a pore volume (see U.S. Patent Appl. Publ. No. 2013 / 0052117 and Katiyar et al., J. Chromatography 1122 (1-2): 13-20 (2006)).

[0131] The mesoporous silica substrate of the antigen delivery system can be provided in various forms, e.g., microspheres, irregular particles, rectangular rods, round nanorods, etc. The particles can have various pre-determined shapes, including, e.g., a spheroid shape, an ellipsoid shape, a rod-like shape, or a curved cylindrical shape. Methods of assembling mesoporous silica to generate microrods and other forms are known in the art (see e.g., Wang et al., Journal of Nanoparticle Research 15:1501 (2013)).

[0132] The mesoporous silica substrate comprises pores of between 2-50 nm in diameter, e.g., pores of between 2-5 nm, 5-10 nm, 10-20 nm, 10-30 nm, 10-40 nm, 20-30 nm, 30-50 nm, 30-40 nm, 40-50 nm or 50-100 nm. In particular embodiments, the mesoporous silica substrate comprises pores of approximately 5-10 nm in diameter.

[0133] In one embodiment, the mesoporous silica substrate comprises micro rods wherein themicro rods have a length, ranging from about 2 10 embodiment, the microrods comprise a length of 25-90 25-800 50-80 0-70 300-600 . In otherembodiments, the micro 805 20 25 3 350 4 450 , 5 550 , 600650 , 7 750 or more.

[0134] The substrate of the artificial antigen presentation scaffold comprises a lipid layer surrounding the substrate, e.g., a lipid layer surrounding the mesoporous silica substrate. As referred to herein, a “lipid” refers to any substance that comprises long, fatty-acid chains, preferably containing 10-30 carbon units, alternatively containing 14-23 carbon units, or alternatively containing 16-18 carbon units. In one embodiment, the lipid layer is a monolayer. In one embodiment, the lipid layer is a bilayer. A lipid bilayer is a thin polar membrane made of two layers of lipid molecules. In the context of surrounding the substrate, the lipid bilayer is a supported bilayer, where the outer face of the bilayer is exposed and the inner face of the bilayer is in contact with the substrate. This supported lipid bilayer is stable and amendable to modification, derivatization, and chemical conjugation with chemical and / or biological moieties.

[0135] The lipid layer can be immobilized on the substrate, e.g., the mesoporous silica substrate, using known methods, including covalent and non-covalent interactions. Types of non- covalent interactions include, for example, electrostatic interactions, van der Waals' interactions, hydrophobic interactions, etc. In one embodiment, the lipid layer is adsorbed on the surface of the substrate. In another embodiment, the lipid layer is attached or tethered to the surface of the substrate via covalent interactions.

[0136] A suitable lipid bilayer may comprise a lipid selected from dimyristoylphosphatidylcholine (DMPC), dipalmitoylphosphatidylcholine (DPPC), distearoylphosphatidylcholine (DSPC), palmitoyl-oleoylphosphatidylcholine (POPC), dioleoylphosphatidylcholine (DOPC), dioleoyl-phosphatidylethanolamine (DOPE), dimyristoyl- phosphatidylethanolamine (DMPE) and dipalmitoyl-phosphatidylethanolamine (DPPE) or any combination thereof. In one embodiment, the lipid bilayer comprises cholesterol. In one embodiment, the lipid bilayer comprises a sphingolipid. In one embodiment, the lipid bilayer comprises a phospholipid. In one embodiment, the lipid is a phosphatidylethanolamine, a phosphatidylcholine, a phosphatidylserine, a phosphoinositide a phosphosphingolipid with saturated or unsaturated tails comprising 6-20 carbons, or a combination thereof.

[0137] In one embodiment, the artificial antigen presentation scaffold further comprises an antigen immobilized directly to the surface of the lipid layer surrounding the substrate of the scaffold, e.g., via biotin-streptavidin conjugation. In another embodiment, the antigen is immobilized to thesurface of the lipid layer indirectly via an immune-complex. In accordance with this embodiment, the artificial antigen presentation scaffold further comprises an immune-complex receptor protein immobilized to the surface of the lipid layer surrounding the substrate of the scaffold. An immune- complex receptor protein is a cell surface receptor that participates in antigen presentation to B cells in vivo. The immobilized immune-complex receptor is bound to its corresponding immune-complex ligand. An immune-complex ligand is the in vivo ligand of the immune-complex receptor protein that associates with antigen in vivo and, together with the immune-complex receptor protein presents the associated antigen to B cells in vivo.

[0138] In one embodiment, the immune-complex receptor protein is a human Fc receptor protein, and the immune-complex receptor ligand is an Fc-containing polypeptide. In one embodiment, the Fc receptor protein is human Fc-gamma receptor I (CD64) or a functional fragment thereof. Human Fc-gamma receptor I (CD64) (UniProt ID No. P12314) comprises the amino acid sequence of SEQ ID NO:1 as provided below. MWFLTTLLLWVPVDGQVDTTKAVITLQPPWVSVFQEETVTLHCEVLHLPGSSSTQWFLNG TATQTSTPSYRITSASVNDSGEYRCQRGLSGRSDPIQLEIHRGWLLLQVSSRVFTEGEPL ALRCHAWKDKLVYNVLYYRNGKAFKFFHWNSNLTILKTNISHNGTYHCSGMGKHRYTSAG ISVTVKELFPAPVLNASVTSPLLEGNLVTLSCETKLLLQRPGLQLYFSFYMGSKTLRGRN TSSEYQILTARREDSGLYWCEAATEDGNVLKRSPELELQVLGLQLPTPVWFHVLFYLAVG IMFLVNTVLWVTIRKELKRKKKWDLEISLDSGHEKKVISSLQEDRHLEEELKCQEQKEEQ LQEGVHRKEPQGAT (SEQ ID NO: 1)

[0139] In one embodiment, the Fc receptor protein is human Fc-gamma receptor II-B (CD32) or a functional fragment thereof. Human Fc-gamma receptor II-B (CD32) (UniProt ID No. P31994) comprises the amino acid sequence of SEQ ID NO:2 as provided below. MGILSFLPVLATESDWADCKSPQPWGHMLLWTAVLFLAPVAGTPAAPPKAVLKLEPQWIN VLQEDSVTLTCRGTHSPESDSIQWFHNGNLIPTHTQPSYRFKANNNDSGEYTCQTGQTSL SDPVHLTVLSEWLVLQTPHLEFQEGETIVLRCHSWKDKPLVKVTFFQNGKSKKFSRSDPN FSIPQANHSHSGDYHCTGNIGYTLYSSKPVTITVQAPSSSPMGIIVAVVTGIAVAAIVAA VVALIYCRKKRISALPGYPECREMGETLPEKPANPTNPDEADKVGAENTITYSLLMHPDA LEEPDDQNRI (SEQ ID NO: 2)

[0140] Suitable Fc-containing polypeptides that serve as the immune-complex receptor ligand for CD64 or CD32 receptors include, without limitation, human IgG antibodies, antibody Fc- containing fragments, and Fc-antigen fusion proteins containing a suitable Fc domain sequence that is capable of binding CD64 or CD32. A suitable Fc domain sequence includes the amino acid sequence of human immunoglobulin heavy constant gamma 1 (UniProt ID No. P01857) provided below as SEQ ID NO: 3 and functional binding fragments thereof. ASTKGPSVFPLAPSSKSTSGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSS GLYSLSSVVTVPSSSLGTQTYICNVNHKPSNTKVDKKVEPKSCDKTHTCPPCPAPELLGG PSVFLFPPKPKDTLMISRTPEVTCVVVDVSHEDPEVKFNWYVDGVEVHNAKTKPREEQYN STYRVVSVLTVLHQDWLNGKEYKCKVSNKALPAPIEKTISKAKGQPREPQVYTLPPSRDE LTKNQVSLTCLVKGFYPSDIAVEWESNGQPENNYKTTPPVLDSDGSFFLYSKLTVDKSRW QQGNVFSCSVMHEALHNHYTQKSLSLSPGK (SEQ ID NO: 3)

[0141] In another embodiment, the immune-complex receptor protein is a human complement receptor 1 (CR1) and / or human complement receptor 2 (CR2) and the immune-complex receptor ligand is human complement factor C3b and / or complement factor C3d. The amino acid sequences of human CR1 (UniProt ID No. P17927) and human CR2 (UniProt ID No. P20023) are provided below as SEQ ID NOs: 4 and 5, respectively. The amino acid sequences of human C3b and C3d are provided below as SEQ ID NOs: 6 and 7. MGASSPRSPEPVGPPAPGLPFCCGGSLLAVVVLLALPVAWGQCNAPEWLPFARPTNLTDE FEFPIGTYLNYECRPGYSGRPFSIICLKNSVWTGAKDRCRRKSCRNPPDPVNGMVHVIKG IQFGSQIKYSCTKGYRLIGSSSATCIISGDTVIWDNETPICDRIPCGLPPTITNGDFIST NRENFHYGSVVTYRCNPGSGGRKVFELVGEPSIYCTSNDDQVGIWSGPAPQCIIPNKCTP PNVENGILVSDNRSLFSLNEVVEFRCQPGFVMKGPRRVKCQALNKWEPELPSCSRVCQPP PDVLHAERTQRDKDNFSPGQEVFYSCEPGYDLRGAASMRCTPQGDWSPAAPTCEVKSCDD FMGQLLNGRVLFPVNLQLGAKVDFVCDEGFQLKGSSASYCVLAGMESLWNSSVPVCEQIF CPSPPVIPNGRHTGKPLEVFPFGKTVNYTCDPHPDRGTSFDLIGESTIRCTSDPQGNGVW SSPAPRCGILGHCQAPDHFLFAKLKTQTNASDFPIGTSLKYECRPEYYGRPFSITCLDNL VWSSPKDVCKRKSCKTPPDPVNGMVHVITDIQVGSRINYSCTTGHRLIGHSSAECILSGN AAHWSTKPPICQRIPCGLPPTIANGDFISTNRENFHYGSVVTYRCNPGSGGRKVFELVGE PSIYCTSNDDQVGIWSGPAPQCIIPNKCTPPNVENGILVSDNRSLFSLNEVVEFRCQPGF VMKGPRRVKCQALNKWEPELPSCSRVCQPPPDVLHAERTQRDKDNFSPGQEVFYSCEPGY DLRGAASMRCTPQGDWSPAAPTCEVKSCDDFMGQLLNGRVLFPVNLQLGAKVDFVCDEGF QLKGSSASYCVLAGMESLWNSSVPVCEQIFCPSPPVIPNGRHTGKPLEVFPFGKAVNYTC DPHPDRGTSFDLIGESTIRCTSDPQGNGVWSSPAPRCGILGHCQAPDHFLFAKLKTQTNASDFPIGTSLKYECRPEYYGRPFSITCLDNLVWSSPKDVCKRKSCKTPPDPVNGMVHVITD IQVGSRINYSCTTGHRLIGHSSAECILSGNTAHWSTKPPICQRIPCGLPPTIANGDFIST NRENFHYGSVVTYRCNLGSRGRKVFELVGEPSIYCTSNDDQVGIWSGPAPQCIIPNKCTP PNVENGILVSDNRSLFSLNEVVEFRCQPGFVMKGPRRVKCQALNKWEPELPSCSRVCQPP PEILHGEHTPSHQDNFSPGQEVFYSCEPGYDLRGAASLHCTPQGDWSPEAPRCAVKSCDD FLGQLPHGRVLFPLNLQLGAKVSFVCDEGFRLKGSSVSHCVLVGMRSLWNNSVPVCEHIF CPNPPAILNGRHTGTPSGDIPYGKEISYTCDPHPDRGMTFNLIGESTIRCTSDPHGNGVW SSPAPRCELSVRAGHCKTPEQFPFASPTIPINDFEFPVGTSLNYECRPGYFGKMFSISCL ENLVWSSVEDNCRRKSCGPPPEPFNGMVHINTDTQFGSTVNYSCNEGFRLIGSPSTTCLV SGNNVTWDKKAPICEIISCEPPPTISNGDFYSNNRTSFHNGTVVTYQCHTGPDGEQLFEL VGERSIYCTSKDDQVGVWSSPPPRCISTNKCTAPEVENAIRVPGNRSFFSLTEIIRFRCQ PGFVMVGSHTVQCQTNGRWGPKLPHCSRVCQPPPEILHGEHTLSHQDNFSPGQEVFYSCE PSYDLRGAASLHCTPQGDWSPEAPRCTVKSCDDFLGQLPHGRVLLPLNLQLGAKVSFVCD EGFRLKGRSASHCVLAGMKALWNSSVPVCEQIFCPNPPAILNGRHTGTPFGDIPYGKEIS YACDTHPDRGMTFNLIGESSIRCTSDPQGNGVWSSPAPRCELSVPAACPHPPKIQNGHYI GGHVSLYLPGMTISYICDPGYLLVGKGFIFCTDQGIWSQLDHYCKEVNCSFPLFMNGISK ELEMKKVYHYGDYVTLKCEDGYTLEGSPWSQCQADDRWDPPLAKCTSRTHDALIVGTLSG TIFFILLIIFLSWIILKHRKGNNAHENPKEVAIHLHSQGGSSVHPRTLQTNEENSRVLP (Human CR1; SEQ ID NO: 4) MGAAGLLGVFLALVAPGVLGISCGSPPPILNGRISYYSTPIAVGTVIRYSCSGTFRLIGE KSLLCITKDKVDGTWDKPAPKCEYFNKYSSCPEPIVPGGYKIRGSTPYRHGDSVTFACKT NFSMNGNKSVWCQANNMWGPTRLPTCVSVFPLECPALPMIHNGHHTSENVGSIAPGLSVT YSCESGYLLVGEKIINCLSSGKWSAVPPTCEEARCKSLGRFPNGKVKEPPILRVGVTANF FCDEGYRLQGPPSSRCVIAGQGVAWTKMPVCEEIFCPSPPPILNGRHIGNSLANVSYGSI VTYTCDPDPEEGVNFILIGESTLRCTVDSQKTGTWSGPAPRCELSTSAVQCPHPQILRGR MVSGQKDRYTYNDTVIFACMFGFTLKGSKQIRCNAQGTWEPSAPVCEKECQAPPNILNGQ KEDRHMVRFDPGTSIKYSCNPGYVLVGEESIQCTSEGVWTPPVPQCKVAACEATGRQLLT KPQHQFVRPDVNSSCGEGYKLSGSVYQECQGTIPWFMEIRLCKEITCPPPPVIYNGAHTG SSLEDFPYGTTVTYTCNPGPERGVEFSLIGESTIRCTSNDQERGTWSGPAPLCKLSLLAV QCSHVHIANGYKISGKEAPYFYNDTVTFKCYSGFTLKGSSQIRCKADNTWDPEIPVCEKE TCQHVRQSLQELPAGSRVELVNTSCQDGYQLTGHAYQMCQDAENGIWFKKIPLCKVIHCH PPPVIVNGKHTGMMAENFLYGNEVSYECDQGFYLLGEKKLQCRSDSKGHGSWSGPSPQCL RSPPVTRCPNPEVKHGYKLNKTHSAYSHNDIVYVDCNPGFIMNGSRVIRCHTDNTWVPGV PTCIKKAFIGCPPPPKTPNGNHTGGNIARFSPGMSILYSCDQGYLLVGEALLLCTHEGTW SQPAPHCKEVNCSSPADMDGIQKGLEPRKMYQYGAVVTLECEDGYMLEGSPQSQCQSDHQ WNPPLAVCRSRSLAPVLCGIAAGLILLTFLIVITLYVISKHRARNYYTDTSQKEAFHLEA REVYSVDPYNPAS (Human CR2; SEQ ID NO: 5) SPMYSIITPNILRLESEETMVLEAHDAQGDVPVTVTVHDFPGKKLVLSSEKTVLTPATNH MGNVTFTIPANREFKSEKGRNKFVTVQATFGTQVVEKVVLVSLQSGYLFIQTDKTIYTPG STVLYRIFTVNHKLLPVGRTVMVNIENPEGIPVKQDSLSSQNQLGVLPLSWDIPELVNMG QWKIRAYYENSPQQVFSTEFEVKEYVLPSFEVIVEPTEKFYYIYNEKGLEVTITARFLYG KKVEGTAFVIFGIQDGEQRISLPESLKRIPIEDGSGEVVLSRKVLLDGVQNPRAEDLVGK SLYVSATVILHSGSDMVQAERSGIPIVTSPYQIHFTKTPKYFKPGMPFDLMVFVTNPDGS PAYRVPVAVQGEDTVQSLTQGDGVAKLSINTHPSQKPLSITVRTKKQELSEAEQATRTMQ ALPYSTVGNSNNYLHLSVLRTELRPGETLNVNFLLRMDRAHEAKIRYYTYLIMNKGRLLK AGRQVREPGQDLVVLPLSITTDFIPSFRLVAYYTLIGASGQREVVADSVWVDVKDSCVGS LVVKSGQSEDRQPVPGQQMTLKIEGDHGARVVLVAVDKGVFVLNKKNKLTQSKIWDVVEK ADIGCTPGSGKDYAGVFSDAGLTFTSSSGQQTAQRAELQCPQPAA (Human C3b; SEQ ID NO: 6)HLIVTPSGCGEQNMIGMTPTVIAVHYLDETEQWEKFGLEKRQGALELIKKGYTQQLAFRQ PSSAFAAFVKRAPSTWLTAYVVKVFSLAVNLIAIDSQVLCGAVKWLILEKQKPDGVFQED APVIHQEMIGGLRNNNEKDMALTAFVLISLQEAKDICEEQVNSLPGSITKAGDFLEANYM NLQRSYTVAIAGYALAQMGRLKGPLLNKFLTTAKDKNRWEDPGKQLYNVEATSYALLALL QLKDFDFVPPVVRWLNEQRYYGGGYGSTQATFMVFQALAQYQKDAPDHQELNLDVSLQLP SR (Human C3d: SEQ ID NO: 7)

[0142] The immune-complex receptor ligand is coupled to an antigen of interest for presentation to the lymphoid-tissue derived B cells of the lymphoid cultures for the purpose of stimulating antibody production by the cultured B cells. In accordance with this and other aspects of the disclosure, suitable antigens include a peptide, protein or fragment thereof, polysaccharides, lipids, nucleic acids, or other biomolecules. In some embodiments, the antigen can be a viral protein, a bacterial protein, a growth factor, a cancer related protein, a cancer related peptide, an auto-immune disease related protein, an auto-immune disease related peptide, or fragment thereof. The antigen can be a naturally occurring biomolecule, e.g., a naturally occurring protein or fragment thereof, or a variant of a naturally occurring biomolecule, where the variant is engineered to have enhanced immunogenicity to facilitate antibody production in the in vitro lymphoid cell culture system as describe herein. For delivery of the antigen via the artificial antigen presenting scaffolds as described herein, the antigen is further engineered to comprise a coupling moiety, e.g., a HIS-tag, suitable for coupling the antigen to the immune-complex receptor ligand, i.e., an Fc-containing polypeptide. Alternatively, an antigen-immune-complex ligand fusion protein, e.g., an antigen-Fc polypeptide fusion protein, can be utilized for this purpose.

[0143] In one embodiment, the artificial antigen presentation scaffold further comprises a B cell co-stimulatory molecule. The B cell co-stimulatory molecules are immobilized to the surface of the lipid layer of the antigen delivery system. As referred to herein, a B cell co-stimulator molecule is molecule that promotes B cell response to antigenic stimuli and promotes B cell differentiation and proliferation in response to the antigenic stimuli. Suitable B cell co-stimulator molecules include, without limitation, recombinant CD320, CD40, CD40L, OX-40, 4-1BB, CD30, CD27, CD28, and ICOS. In one embodiment, the B cell co-stimulatory molecule immobilized to the surface of the lipid layer is recombinant CD320 or a functional fragment thereof.

[0144] The immune-complex receptor protein and B cell co-stimulatory molecules are immobilized to the lipid surface of the artificial antigen presentation scaffold. Immobilization or conjugation of these components to the lipid surface can be achieved via affinity pairing or chemicalcoupling. For example, in one embodiment, the immune-complex receptor protein and / or B cell co- stimulatory molecules are coupled to the lipid surface via affinity pairing comprising a biotin-biotin binding agent pair (e.g., biotin-streptavidin pair, biotin-avidin pair), an antibody-antigen pair, an antibody-hapten pair, an aptamer affinity pair, a capture protein pair, an Fc receptor-IgG pair, a metal- chelating lipid pair, a metal-chelating lipid-histidine (HIS)-tagged protein pair, or a combination thereof. In one embodiment, the lipid layer surrounding the mesoporous silicate substrate is functionalized with biotin and the immune-complex receptor protein and / or B cell co-stimulatory molecule is coupled to a biotin-binding protein, such as streptavidin. The immune-complex receptor protein and / or B cell co-stimulatory molecule is conjugated to the lipid surface via the formation of a biotin:biotin-binding protein interaction. In one embodiment, the lipid layer surrounding the mesoporous silicate substrate is functionalized with biotin and a biotin-binding protein, e.g., streptavidin, and the immune-complex receptor protein and / or B cell co-stimulatory molecule is coupled to biotin. The immune-complex receptor protein and / or B cell co-stimulatory molecule is conjugated to the lipid surface via the formation of a biotin:biotin-binding protein interaction.

[0145] Alternatively, in one embodiment, the immune-complex receptor protein and / or B cell co-stimulatory molecules are conjugated to the lipid surface via chemical coupling, e.g., using click chemistry reagents and reaction such as azide-alkyne chemical (AAC) reaction, dibenzo-cyclooctyne ligation (DCL), or tetrazine-alkene ligation (TAL).

[0146] In one embodiment, the artificial antigen presentation scaffold further comprises one or more stimulatory cytokines adsorbed to a surface of the substrate beneath the lipid layer. In one embodiment, the cytokine is a cytokine that stimulates or activate B cells, e.g., a B cell survival factor such as a BAFF receptor agonist. In one embodiment, the cytokine is BAFF. In one embodiment, the cytokine is a cytokine that stimulates or activate T cell immune response. In one embodiment, the T cell stimulatory molecule comprises IL-21. In one embodiment, the artificial antigen presentation scaffold comprises a B cell activator (e.g., BAFF), cytokines, such as IL-21 or IL-6, or a combination of a B cell survival factor and cytokines adsorbed to a surface of the substrate beneath the lipid layer.

[0147] In one embodiment, the antigen delivery system of the in vitro human lymphoid cell culture further or alternatively comprises one or more adjuvants. Suitable adjuvants include, without limitation, aluminum salts, Freund's adjuvant, Poly-IC, Poly-ICLC, MDP, MPL, CpG ODN, Virosome, MF59, AS01, Flagellin, R837 / R848, AS04, AS02, AS03, mineral adjuvants such as aluminum hydroxide, phosphate adjuvants, calcium phosphate adjuvants, imiquimod, ISA51, or anycombination thereof. In one embodiment, the in vitro human lymphoid cell culture comprises tissue- derived B cells and T cells in a cell culture well comprising culture media, where the culture media comprises one or more adjuvants in combination with the antigen. In another embodiment, the in vitro human lymphoid cell culture comprises tissue-derived B cells and T cells in a cell culture well comprising culture media, where the culture media comprises one or more adjuvants in combination with the artificial antigen presentation scaffold (e.g., liposome coated mesoporous silica rods) comprising immobilized antigen (either directly immobilized antigen or antigen immobilized via an immune-complex).

[0148] In one embodiment, the antigen delivery system of the in vitro human lymphoid cell culture further or alternatively comprises one or more proinflammatory cytokines. Suitable proinflammatory cytokines include, without limitation, IL-1, IL-2, IL-6, IL-11, IL15, IL-17, IL-18,IL-21, IL-33, TNF- , TNF- INF- or any combination thereof. In one embodiment, a suitablecombination of cytokines include IL-10, IL-6, IL-2, IL-21, and / or IL-15. In one embodiment, the in vitro lymphoid cell culture comprises tissue-derived B cells and T cells in a cell culture well comprising culture media, where the culture media comprises one or more cytokines in combination with the antigen. In another embodiment, the in vitro human lymphoid cell culture comprises tissue- derived B cells and T cells in a cell culture well comprising culture media, where the culture media comprises one or more cytokines in combination one or more adjuvants and / or in combination with the artificial antigen presentation scaffold (e.g., liposome coated mesoporous silica rods) comprising immobilized antigen (either directly immobilized antigen or antigen immobilized via an immune- complex).

[0149] Another aspect of the present disclosure is directed to an in vitro method of generating antibodies against a target antigen. This method comprises providing the lymphoid cell culture comprising human lymphoid tissue derived B cells and T cells and introducing, to the cell culture, an antigen delivery system comprising the target antigen. This method further comprises incubating the cell culture, after said introducing, under conditions suitable for B cells of the culture to produce antibodies against the antigen. In some embodiments, the method further involves collecting the lymphoid cell culture supernatants after the culture has been incubated with the antigen delivery system, and evaluating the culture supernatants for the presence of the antigen-specific antibodies.

[0150] The lymphoid cell cultures are produced as described supra from donor lymphoid tissue, e.g., tonsil tissue, lymph tissue, etc. In one embodiment, the mammalian lymphoid cell cultureis depleted of CD25+ cells. In one embodiment, the cell culture comprises human lymphoid tissue derived, CD24–B cells and T cells in a cell culture well comprising culture media, where the culture media is supplemented with IL-4. In one embodiment, the cell culture comprises human lymphoid tissue derived CD24–B cells and T cells in a cell culture well comprising culture media, where the culture media is supplemented with IL-4 and further supplemented with IL-10, IL-6, IL-2, IL-21, IL- 15, or a combination thereof.

[0151] Once the culture is initiated, e.g., on day 0 or day 1, the antigen delivery system comprising an antigen is administered to the lymphoid cell culture by introducing it into the culture media. In one embodiment, the antigen delivery system comprises the artificial antigen presentation scaffold as described supra. In one embodiment, administration of the artificial antigen presentation scaffold to the lymphoid cell cultures is repeated one or two additional times to maintain a constant concentration of the antigen in the culture. In one embodiment, one or more adjuvants is introduced into the culture along with the artificial antigen presentation scaffold. Suitable adjuvants are disclosed supra.

[0152] The lymphoid cell cultures are incubated with the artificial antigen presentation scaffold alone or in conjunction with one or more adjuvants for 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or more days to allow for antibody production by B cells (i.e., plasmablasts) of the culture. The presence of antigen-specific antibody production by B cells of the culture can be assessed by collecting and evaluating the culture supernatants as described supra. If antigen-specific antibodies are detecting in the supernatant of the lymphoid cultures, the antibody producing B cells of the culture can be harvested for obtaining the nucleic acid sequences encoding the antigen-specific antibodies and cloning the antibody for further production and characterization (e.g., characterization of binding affinity and specificity).

[0153] Another aspect of the present disclosure is directed to an antigen delivery system comprising the artificial antigen presentation scaffold for presenting antigen to the lymphoid cell cultures described herein. As described supra, this artificial antigen presentation scaffold comprises a substrate and a lipid layer surrounding the substrate. In one embodiment, an antigen is immobilized directly to the surface of the lipid layer surrounding the substrate of the scaffold. In another embodiment, the antigen is immobilized to the surface of the lipid layer indirectly via an immune- complex. In accordance with this embodiment, the artificial antigen presentation scaffold further comprises an immune-complex receptor protein and an immune-complex receptor ligand. Theimmune-complex receptor protein is immobilized to a surface on the lipid layer, and the immune- complex receptor ligand is coupled to an antigen and is bound to the immobilized immune-complex receptor proteins on the surface of the lipid layer.

[0154] Suitable substrate materials for the artificial antigen presentation scaffold are described supra. In one embodiment, the artificial antigen presentation scaffold comprises a mesoporous silica particle substrate, e.g., rod particles, coated with a liposome layer. Suitable lipid materials for the liposome layer are disclosed supra. The liposome layer is functionalized with one or more coupling agents, e.g., one of the binding partners of an affinity binding complex. Suitable affinity binding complexes are described supra. In one embodiment, the liposome layer is functionalized with biotin. In one embodiment, the liposome layer is functionalized with biotin and a biotin binding protein, streptavidin. The immune-complex receptor protein, e.g., C64 or CD32, is coupled to the other binding partner of the affinity binding complex and is immobilized to the surface of the liposome layer via the binding of the affinity binding pairs. The immune-complex receptor protein is bound to its corresponding immune-complex ligand, e.g. an Fc-containing polypeptide, which is coupled or fused to the target antigen of interest. Computational Models

[0155] Some aspects of the present disclosure relate to a machine learning model trained on immunogenicity data and using the machine learning model to predict one or more immunogenic properties of a candidate therapeutic molecule. Such a machine learning model may allow for in silico immunogenicity prediction and assessment of candidate therapeutic molecules during early- stage screening of possible candidate therapeutic molecules, selecting those molecules with desired immunogenic properties (e.g., those molecules predicted to have reduced risk of immunogenicity) for further evaluation and testing as a potential therapy. In this way, the number of candidate therapeutic molecules can be reduced via in silico filtering using the machine learning model. In some embodiments, the possible candidate therapeutic molecules screened by the machine learning model may be identified using a protein language model (e.g., a protein language model fine-tuned on immunogenic data as further described herein). In such embodiments, the machine learning model in combination with the protein language model may be part of a workflow for selection of candidate therapeutic molecules predicted to have reduced immunogenic risk (e.g., the machine learning model outputs a prediction of low immunogenic risk for the candidate therapeutic molecules).

[0156] Some embodiments involve training a machine learning model using one or more markers of a de novo immune response and / or one or more markers of immune cell activation described herein. In such embodiments, training the machine learning model may involve using sequence embeddings generated by a protein language model (e.g., as input features to the protein language model). Such a sequence embedding corresponds to a numeric output (e.g., a vector of real numbers) representing an encoding of an amino acid sequence by a protein language model. In embodiments that involve training the machine learning model using sequence embeddings (e.g., as input features to the protein language model), the sequence embeddings correspond to molecules associated with the one or more markers of a de novo immune response and / or the one or more markers of immune cell activation. The trained machine learning model is configured to receive a sequence embedding corresponding to a candidate therapeutic molecule as input and generate a prediction for one or more immunogenic properties of the candidate therapeutic molecule. In some embodiments, the one or more immunogenic properties may include one or more markers of a de novo immune response and / or one or more markers of immune cell activation described herein. Accordingly, some embodiments involve using one or more machine learning models (e.g., a machine learning model trained on one or more markers of a de novo immune response and / or one or more markers of immune cell activation) to predict one or more immunogenic properties (e.g., in vivo immunogenicity) of a candidate therapeutic molecule.

[0157] The machine learning model(s) may include any type of machine learning model suitable for predicting one or more immunogenic properties of a candidate therapeutic molecule, as aspects of the technology described herein are not limited in this respect. For example, the machine learning model may include any suitable type of classification or regression model. For example, the machine learning model may include a linear regression model, a linear classification model (e.g., logistic regression), or a non-linear regression model (e.g., random forest regression), or a non-linear classification model (e.g., a support vector machine with a radial basis function kernel, gradient- boosted decision trees, or neural networks). The machine learning model may also include a single model or an ensemble of models, and may be trained using any suitable supervised or semi-supervised learning technique, as aspects of the technology described herein are not limited in this respect. Example machine learning models and techniques for training such models are described herein including at least in the section “Machine Learning Model.”

[0158] Some aspects of the present disclosure relate to a protein language model fine-tuned using immunogenicity data (e.g., one or more markers of a de novo immune response and / or one or more markers of immune cell activation described herein). Some embodiments involve fine-tuning a pre-trained protein language model (e.g., AMPLIFY, ESM-2) using immunogenicity data corresponding to candidate therapeutic molecules to obtain a modified protein language model. By being trained on immunogenicity data, the modified protein language model may generate sequence embeddings representing an encoding of an amino acid sequence and immunogenicity information associated with the amino acid sequence. Sequence embeddings generated by the modified protein language model may be used as input for downstream applications, including classification and regression tasks. Some embodiments involve using the modified protein language model to obtain a sequence embedding corresponding to a candidate therapeutic molecule and using the sequence embedding as input into a machine learning model (e.g., a machine learning model trained using one or more markers of a de novo immune response and / or one or more markers of immune cell activation described herein) to predict one or more immunogenic properties of the candidate therapeutic molecule. Example pre-trained protein language models and techniques for fine-tuning such models are described here including at least in the section “Protein Language Model.”

[0159] Fine-tuning a pre-trained protein language model may involve creating a regression or classification task and updating parameters of the pre-trained protein language model to improve performance of the regression or classification task. In embodiments where fine-tuning involves a classification task, creating the classification task may include discretizing the immunogenicity data. Fine-tuning the pre-trained protein language model may involve optimizing a loss function based on a comparison between a prediction for the regression or classification task and a corresponding ground-truth. Fine-tuning may involve updating parameters of the pre-trained protein language model where the modified protein language model has the same number of parameters as the pre-trained protein language model but the values for the parameters are different. Thus, in some embodiments, the pre-trained protein language model includes a number of parameters having a first set of values and the modified protein language model includes the same number of parameters having a second set of values. In some embodiments, fine-tuning involves modifying the architecture of the pre-trained protein language model by inserting additional layers and removing the additional layers after updating parameters of the pre-trained protein language model to obtain the modified protein language model. An example of a fine-tuning technique that may be used in obtaining a protein language model fine-tuned using immunogenicity data is low-rank adaption (LoRA), which is described by Hu, E., et al. (“LoRA: Low-Rank Adaption of Large Language Models.” arXiv:2106.09685), which is incorporated by reference herein in its entirety.

[0160] Some embodiments provide for a method of generating a computational model for predicting in vivo immunogenicity of molecules. In some embodiments, the method comprises obtaining one or more markers of a de novo immune response corresponding to one or more molecules. In some embodiments, obtaining the one or more markers of a de novo immune response corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived B cells and T cells in culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering a first and second dose of the one or more molecules to each of the plurality of cell cultures, wherein the second dose is administered between 3–7 days after administering the first dose; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures after administering the second dose of the one or more molecules; and assessing the one or more markers of a de novo immune response in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method comprises training, using at least one computer hardware processor and the one or more markers of a de novo immune response, a machine learning model for predicting in vivo immunogenicity of molecules. In some embodiments, the method further comprises determining, using the machine learning model and the at least one computer hardware processor, a prediction for in vivo immunogenicity of a candidate therapeutic molecule.

[0161] Some embodiments provide for a system, comprising: at least one computer hardware processor; and at least one non-transitory computer-readable storage medium storing processor- executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a computational model for predicting in vivo immunogenicity of molecules. In some embodiments, the method comprises obtaining one or more markers of a de novo immune response corresponding to one or more molecules and training, using the one or more markers of a de novo immune response, a machine learning model for predicting in vivo immunogenicity of molecules. In some embodiments, obtaining the one or more markers of a de novo immune response corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprisinglymphoid tissue derived B cells and T cells in culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering a first and second dose of the one or more molecules to each of the plurality of cell cultures, wherein the second dose is administered between 3–7 days after administering the first dose; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures after administering the second dose of the one or more molecules; and assessing the one or more markers of a de novo immune response in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises determining, using the machine learning model, a prediction for in vivo immunogenicity of a candidate therapeutic molecule.

[0162] Some embodiments provide for at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a computational model for predicting in vivo immunogenicity of molecules. In some embodiments, the method comprises obtaining one or more markers of a de novo immune response corresponding to one or more molecules and training, using the one or more markers of a de novo immune response, a machine learning model for predicting in vivo immunogenicity of molecules. In some embodiments, obtaining the one or more markers of a de novo immune response corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived B cells and T cells in culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering a first and second dose of the one or more molecules to each of the plurality of cell cultures, wherein the second dose is administered between 3–7 days after administering the first dose; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures after administering the second dose of the one or more molecules; and assessing the one or more markers of a de novo immune response in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises determining, using the machine learning model, a prediction for in vivo immunogenicity of a candidate therapeutic molecule.

[0163] Some embodiments provide for a method of generating a protein language model fine- tuned on immunogenic data. In some embodiments, the method comprises obtaining one or moremarkers of a de novo immune response corresponding to one or more molecules. In some embodiments, obtaining the one or more markers of a de novo immune response corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived B cells and T cells in culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering a first and second dose of the one or more molecules to each of the plurality of cell cultures, wherein the second dose is administered between 3–7 days after administering the first dose; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures after administering the second dose of the one or more molecules; and assessing the one or more markers of a de novo immune response in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method comprises fine-tuning, using the one or more markers of a de novo immune response and at least one computer hardware processor, a pre-trained protein language model to obtain a modified protein language model. In some embodiments, the method further comprises generating, using the modified protein language model and the at least one computer hardware processor, a sequence embedding for a candidate therapeutic molecule. In some embodiments, the method further comprises determining, using the sequence embedding and a machine learning model for predicting in vivo immunogenicity of molecules, a prediction for in vivo immunogenicity of the candidate therapeutic molecule.

[0164] Some embodiments provide for a system, comprising: at least one computer hardware processor; and at least one non-transitory computer-readable storage medium storing processor- executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a protein language model fine-tuned on immunogenic data. In some embodiments, the method comprises obtaining one or more markers of a de novo immune response corresponding to one or more molecules and fine- tuning, using the one or more markers of a de novo immune response, a pre-trained protein language model to obtain a modified protein language model. In some embodiments, obtaining the one or more markers of a de novo immune response corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived B cells and T cells in culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering a first and second doseof the one or more molecules to each of the plurality of cell cultures, wherein the second dose is administered between 3–7 days after administering the first dose; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures after administering the second dose of the one or more molecules; and assessing the one or more markers of a de novo immune response in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises generating, using the modified protein language model, a sequence embedding for a candidate therapeutic molecule. In some embodiments, the method further comprises determining, using the sequence embedding and a machine learning model for predicting in vivo immunogenicity of molecules, a prediction for in vivo immunogenicity of the candidate therapeutic molecule.

[0165] Some embodiments provide for at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a protein language model fine-tuned on immunogenic data. In some embodiments, the method comprises obtaining one or more markers of a de novo immune response corresponding to one or more molecules and fine-tuning, using the one or more markers of a de novo immune response, a pre-trained protein language model to obtain a modified protein language model. In some embodiments, obtaining the one or more markers of a de novo immune response corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived B cells and T cells in culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering a first and second dose of the one or more molecules to each of the plurality of cell cultures, wherein the second dose is administered between 3–7 days after administering the first dose; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures after administering the second dose of the one or more molecules; and assessing the one or more markers of a de novo immune response in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises generating, using the modified protein language model, a sequence embedding for a candidate therapeutic molecule. In some embodiments, the method further comprises determining, using the sequence embedding and a machine learning model for predicting in vivoimmunogenicity of molecules, a prediction for in vivo immunogenicity of the candidate therapeutic molecule.

[0166] As described herein, examples of markers of de novo immune response that may be used for training a machine learning model and / or fine-tuning a protein language model include the presence of anti-candidate therapeutic molecule antibodies, the presence of anti-candidate therapeutic molecule antibody secreting cells, a change in the proportion of plasmablasts (i.e., antibody producing B cells) in the cell culture, a change in the proportion of germinal center (GC) B cells in the cell culture, a change in the proportion of plasmablasts and germinal center B cells in the cell culture, a change in the proportion or frequency of CD4+T cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures, an increase in the proportion of follicular helper T (Tfh) cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures, an increase in the proportion of activated dendritic cells (DCs) in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures, and an increase in frequency of macrophages in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of the control cell cultures. It should be appreciated that some or all of these markers of de novo immune response may be used in obtaining a machine learning model trained to predict one or more immunogenic properties of a candidate therapeutic molecule or a protein language model fine-tuned using immunogenicity data as described herein.

[0167] Some embodiments provide for a method of generating a computational model for predicting in vivo immunogenicity of molecules. In some embodiments, the method comprises obtaining one or more markers of immune cell activation corresponding to one or more molecules. In some embodiments, obtaining the one or more markers immune cell activation corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering the one or more molecules to each of the plurality of cell cultures; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5-8 days after administering the one or more molecules; measuring the one or more markers immune cell activation in the harvested cells, harvestedculture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method comprises training, using at least one computer hardware processor and the one or more markers immune cell activation, a machine learning model for predicting in vivo immunogenicity of molecules. In some embodiments, the method further comprises determining, using the machine learning model and the at least one computer hardware processor, a prediction for in vivo immunogenicity of a candidate therapeutic molecule.

[0168] Some embodiments provide for a system, comprising: at least one computer hardware processor; and at least one non-transitory computer-readable storage medium storing processor- executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a computational model for predicting in vivo immunogenicity of molecules. In some embodiments, the method comprises obtaining one or more markers of immune cell activation corresponding to one or more molecules and training, using the one or more markers immune cell activation, a machine learning model for predicting in vivo immunogenicity of molecules. In some embodiments, obtaining the one or more markers immune cell activation corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering the one or more molecules to each of the plurality of cell cultures; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5- 8 days after administering the one or more molecules; measuring the one or more markers immune cell activation in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises determining, using the machine learning model, a prediction for in vivo immunogenicity of a candidate therapeutic molecule.

[0169] Some embodiments provide for at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a computational model for predicting in vivo immunogenicity of molecules. In some embodiments, the method comprises obtaining one or more markers of immune cell activation corresponding to one or more molecules and training, using the one or more markers immune cell activation, a machine learning model for predicting in vivo immunogenicity of molecules. In someembodiments, obtaining the one or more markers immune cell activation corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering the one or more molecules to each of the plurality of cell cultures; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5-8 days after administering the one or more molecules; measuring the one or more markers immune cell activation in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises determining, using the machine learning model, a prediction for in vivo immunogenicity of a candidate therapeutic molecule.

[0170] Some embodiments provide for a method of generating a protein language model fine- tuned on immunogenic data. In some embodiments, the method comprises obtaining one or more markers of immune cell activation corresponding to one or more molecules. In some embodiments, obtaining the one or more markers immune cell activation corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering the one or more molecules to each of the plurality of cell cultures; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5-8 days after administering the one or more molecules; measuring the one or more markers immune cell activation in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method comprises fine-tuning, using the one or more markers of a de novo immune response and at least one computer hardware processor, a pre-trained protein language model to obtain a modified protein language model. In some embodiments, the method further comprises generating, using the modified protein language model and the at least one computer hardware processor, a sequence embedding for a candidate therapeutic molecule. In some embodiments, the method further comprises determining, using the sequence embedding, a machine learning model for predicting in vivo immunogenicity of molecules, and the at least one computer hardware processor, a prediction for in vivo immunogenicity of the candidate therapeutic molecule.

[0171] Some embodiments provide for a system, comprising: at least one computer hardware processor; and at least one non-transitory computer-readable storage medium storing processor- executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a protein language model fine-tuned on immunogenic data. In some embodiments, the method comprises obtaining one or more markers of immune cell activation corresponding to one or more molecules and fine-tuning, using the one or more markers of immune cell activation and a pre-trained protein language model, to obtain a modified protein language model. In some embodiments, obtaining the one or more markers immune cell activation corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering the one or more molecules to each of the plurality of cell cultures; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5-8 days after administering the one or more molecules; measuring the one or more markers immune cell activation in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises generating, using the modified protein language model, a sequence embedding for a candidate therapeutic molecule. In some embodiments, the method further comprises determining, using the sequence embedding and a machine learning model for predicting in vivo immunogenicity of molecules, a prediction for in vivo immunogenicity of the candidate therapeutic molecule.

[0172] Some embodiments provide for at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of generating a protein language model fine-tuned on immunogenic data. In some embodiments, the method comprises obtaining one or more markers of immune cell activation corresponding to one or more molecules and fine-tuning, using the one or more markers of immune cell activation and a pre- trained protein language model, to obtain a modified protein language model. In some embodiments, obtaining the one or more markers immune cell activation corresponding to one or more molecules comprises: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4,wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering the one or more molecules to each of the plurality of cell cultures; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5-8 days after administering the one or more molecules; measuring the one or more markers immune cell activation in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures. In some embodiments, the method further comprises generating, using the modified protein language model, a sequence embedding for a candidate therapeutic molecule. In some embodiments, the method further comprises determining, using the sequence embedding and a machine learning model for predicting in vivo immunogenicity of molecules, a prediction for in vivo immunogenicity of the candidate therapeutic molecule.

[0173] As described herein, examples of markers of immune cell activation that may be used for training a machine learning model and / or fine-tuning a protein language model include marker of immune cell activation is an increase in T cell proliferation in harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of control cell culture, marker of immune cell activation is an increase in T cell activation in harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of control cell cultures, and marker of immune cell activation is an increase in cytokine production and secretion by harvested cells of cell cultures administered the candidate therapeutic molecule compared to harvested cells of control cell cultures. It should be appreciated that some or all of these markers of immune cell activation may be used in obtaining a machine learning model trained to predict one or more immunogenic properties of a candidate therapeutic molecule or a protein language model fine-tuned using immunogenicity data as described herein.

[0174] Protein Language Model

[0175] Some embodiments involve fine-tuning a protein language model using one or more markers of a de novo immune response and / or one or more markers of immune cell activation described herein. In some embodiments, fine-tuning a pre-trained protein language model involves using a pre-trained model and one or more markers of a de novo immune response and / or one or more markers of immune cell activation described herein. The pre-trained protein language model may be any suitable protein language model trained to encode amino acid sequences by processing information representing an amino acid sequence to obtain a numeric output (e.g., a vector of real numbers) representing the encoding of the amino acid sequence, as aspects of the technology describedherein are not limited in this respect. Examples of protein language models include AMPLIFY, the ESM-1b model, the ESM-1v model, the ESM-2 model, the ESM-3 model, the ESM Cambrian model, the ProGen model, the ProGen2 models (e.g., ProGen2-small, ProGen2-medium, ProGen2-large), and the ProtTrans models (e.g., ProtBert, ProtT5). AMPLIFY is described by Fournier, Q., et al. ("Protein language models: is scaling necessary?." bioRxiv (2024): 2024-09.), which is incorporated by reference herein in its entirety. The ESM-1b model is described by Rives, A., et al. ("Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences." Proceedings of the National Academy of Sciences 118.15 (2021): e2016239118.), which is incorporated by reference herein in its entirety. The ESM-1v model is described by Meier, J., et al. ("Language models enable zero-shot prediction of the effects of mutations on protein function." Advances in Neural Information Processing Systems 34 (2021): 29287-29303.), which is incorporated by reference herein in its entirety. The ESM-2 model is described by Lin, Z., et al. ("Evolutionary- scale prediction of atomic-level protein structure with a language model." Science 379.6637 (2023): 1123-1130.), which is incorporated by reference herein in its entirety. ESM-3 is described by Hayes, Thomas, et al. ("Simulating 500 million years of evolution with a language model." Science (2025): eads0018.), which is incorporated by reference herein in its entirety. ESM Cambrian is described by ESM Team. ("ESM Cambrian: Revealing the mysteries of proteins with unsupervised learning." EvolutionaryScale Website, December 4, 2024. evolutionaryscale.ai / blog / esm-cambrian.), which is incorporated by reference herein in its entirety. ProGen is described by Madani, A., et al. (“Large language models generate functional protein sequences across diverse families.” Nature Biotechnology 41, 1099-1106 (2023)), which is incorporated by reference herein in its entirety. ProGen2 models are described by Nijkamp, E., et al. (“ProGen2: Exploring the Boundaries of Protein Language Models.” arXiv:2206.13517), which is incorporated by reference herein in its entirety. The ProtTrans models are described by Elnaggar, A., et al. (“ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning.” IEEE, Vol. 44, No. 10 (2022)), which is incorporated by reference herein in its entirety.

[0176] Machine Learning Model

[0177] Some embodiments involve training one or more machine learning models using one or more markers of a de novo immune response and / or one or more markers of immune cell activation described herein. Some embodiments involve using one or more trained machine learning models (e.g., a machine learning model trained on one or more markers of a de novo immune response and / orone or more markers of immune cell activation) to predict one or more immunogenic properties (e.g., in vivo immunogenicity) of a candidate therapeutic molecule. The machine learning model(s) may include a non-linear regression model (e.g., a random forest regression model), a linear regression model, a support vector machine, a Gaussian mixture model, a random forest classifier model, a decision tree classifier, a gradient boosted decision tree classifier, a neural network model, and / or any other suitable type of machine learning model, as aspects of the technology described herein are not limited in this respect. In some embodiments, the machine learning model(s) may include an ensemble of machine learning models of any suitable type.

[0178] In some embodiments, the machine learning model(s) may be implemented as a decision tree classifier. Any suitable type of decision tree classifier may be used and may be trained using any suitable supervised decision tree learning technique. For example, the decision tree classifier may be trained by the iterative dichotomizer technique (e.g., the ID3 algorithm as described, for example, in Quinlan, J. R. 1986. Induction of Decision Trees. Mach. Learn. 1, 1 (Mar. 1986), 81– 106)), the C4.5 technique (e.g., as described, for example, in Quinlan, J. R. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, 1993), the classification and regression tree (CART) technique (e.g., as described, for example, in Breiman, Leo; Friedman, J. H.; Olshen, R. A.; Stone, C. J. (1984). Classification and regression trees. Monterey, CA: Wadsworth & Brooks / Cole Advanced Books & Software). It should be appreciated that a decision tree classifier may be trained using any other suitable training method, as aspects of the technology described herein are not limited in this respect.

[0179] In some embodiments, a gradient-boosted decision tree classifier may be used. The gradient-boosted decision tree classifier may be an ensemble of multiple decision tree classifiers (sometimes called "weak learners"). The prediction (e.g., classification) generated by the gradient- boosted decision tree classifier is formed based on the predictions generated by the multiple decision trees part of the ensemble. The ensemble may be trained using an iterative optimization technique involving calculation of gradients of a loss function (hence the name "gradient" boosting). Any suitable supervised training algorithm may be applied to training a gradient-boosted decision tree classifier including, for example, any of the algorithms described in Hastie, T.; Tibshirani, R.; Friedman, J. H. (2009). "10. Boosting and Additive Trees". The Elements of Statistical Learning (2nd ed.). New York: Springer. pp. 337–384. In some embodiments, the gradient-boosted decision tree classifier may be implemented using any suitable publicly available gradient boosting framework suchas XGBoost (e.g., as described, for example, in Chen, T., & Guestrin, C. (2016). XGBoost: A Scalable Tree Boosting System. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp.785–794). New York, NY, USA: ACM.). The XGBoost software may be obtained from http: / / xgboost.ai, for example). Another example framework that may be employed is LightGBM (e.g., as described, for example, in Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., … Liu, T.-Y. (2017). Lightgbm: A highly efficient gradient boosting decision tree. Advances in Neural Information Processing Systems, 30, 3146–3154.). The LightGBM software may be obtained from https: / / lightgbm.readthedocs.io / , for example).

[0180] In some embodiments, a neural network classifier may be used. The neural network classifier may be trained using any suitable neural network optimization software. The optimization software may be configured to perform neural network training by gradient descent, stochastic gradient descent, or in any other suitable way. In some embodiments, the Adam optimizer (Kingma, D. and Ba, J. (2015) Adam: A Method for Stochastic Optimization. Proceedings of the 3rd International Conference on Learning Representations (ICLR 2015)) may be used.

[0181] In some embodiments, a support vector machine (SVM) may be used. The SVM may be implemented using any suitable techniques such as, for example, any of the techniques described by Cristianini, N., and Shawe-Taylor, J. (“An introduction to support vector machines and other kernel-based learning methods.” Cambridge university press, 2000.), which is incorporated by reference herein in its entirety.

[0182] In some embodiments, a Gaussian mixture model may be used. The Gaussian mixture model may be implemented using any suitable techniques such as, for example, any of the techniques described by Reynolds, D. ("Gaussian mixture models." Encyclopedia of biometrics 741.659-663 (2009)), which is incorporated by reference herein in its entirety.

[0183] In some embodiments, a random forest model may be used. The random forest model may be implemented using any suitable techniques such as, for example, any of the techniques described by Biau, G. ("Analysis of a random forests model." The Journal of Machine Learning Research 13.1 (2012): 1063-1095.), which is incorporated by reference herein in its entirety.

[0184] Computer Implementation

[0185] An illustrative implementation of a computer system 2300 that may be used in connection with any of the embodiments of the technology described herein is shown in FIG.23. The computer system 2300 includes one or more processors 2310 and one or more articles of manufacturethat comprise non-transitory computer-readable storage media (e.g., memory 2320 and one or more non-volatile storage media 2330). The processor 2310 may control writing data to and reading data from the memory 2320 and the non-volatile storage media 2330 in any suitable manner, as the aspects of the technology described herein are not limited to any particular techniques for writing or reading data. To perform any of the functionality described herein, the processor 2310 may execute one or more processor-executable instructions stored in one or more non-transitory computer-readable storage media (e.g., the memory 2320), which may serve as non-transitory computer-readable storage media storing processor-executable instructions for execution by the processor 2310.

[0186] Computing system 2300 may include a network input / output (I / O) interface 2340 via which the computing device may communicate with other computing devices. Such computing devices may be interconnected by one or more networks in any suitable form, including a local area network or a wide area network, such as an enterprise network, and intelligent network (IN) or the Internet. Such networks may be based on any suitable technology and may operate according to any suitable protocol and may include wireless networks, wired networks or fiber optic networks.

[0187] Computing system 2300 may also include one or more user I / O interfaces 2350, via which the computing device may provide output to and receive input from a user. The user I / O interfaces may include devices such as a keyboard, a mouse, a microphone, a display device (e.g., a monitor or touch screen), speakers, a camera, and / or various other types of I / O devices.

[0188] Further, it should be appreciated that a computer may be embodied in any of a number of forms, such as a rack-mounted computer, a desktop computer, a laptop computer, or a tablet computer, as examples. Additionally, a computer may be embedded in a device not generally regarded as a computer but with suitable processing capabilities, including a Personal Digital Assistant (PDA), a smartphone, a tablet, or any other suitable portable or fixed electronic device.

[0189] The above-described embodiments can be implemented in any of numerous ways. For example, the embodiments may be implemented using hardware, software, or a combination thereof. When implemented in software, the software code can be executed on any suitable processor (e.g., a microprocessor) or collection of processors, whether provided in a single computing device or distributed among multiple computing devices. It should be appreciated that any component or collection of components that perform the functions described above can be generically considered as one or more controllers that control the above-described functions. The one or more controllers can be implemented in numerous ways, such as with dedicated hardware, or with general purpose hardware(e.g., one or more processors) that is programmed using microcode or software to perform the functions recited above.

[0190] In this respect, it should be appreciated that one implementation of the embodiments described herein comprises at least one computer-readable storage medium (e.g., RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other tangible, non-transitory computer-readable storage medium) encoded with a computer program (i.e., a plurality of executable instructions) that, when executed on one or more processors, performs the above-described functions of one or more embodiments. The computer- readable medium may be transportable such that the program stored thereon can be loaded onto any computing device to implement aspects of the techniques described herein. In addition, it should be appreciated that the reference to a computer program which, when executed, performs any of the above-described functions, is not limited to an application program running on a host computer. Rather, the terms computer program and software are used herein in a generic sense to reference any type of computer code (e.g., application software, firmware, microcode, or any other form of computer instruction) that can be employed to program one or more processors to implement aspects of the techniques described herein.

[0191] The terms “program” or “software” are used herein in a generic sense to refer to any type of computer code or set of computer-executable instructions that can be employed to program a computer or other processor to implement various aspects as described above. Additionally, it should be appreciated that according to one aspect, one or more computer programs that when executed perform methods of the present disclosure need not reside on a single computer or processor but may be distributed in a modular fashion among a number of different computers or processors to implement various aspects of the present disclosure.

[0192] Computer-executable instructions may be in many forms, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.

[0193] Also, data structures may be stored in computer-readable media in any suitable form. For simplicity of illustration, data structures may be shown to have fields that are related throughlocation in the data structure. Such relationships may likewise be achieved by assigning storage for the fields with locations in a computer-readable medium that convey relationship between the fields. However, any suitable mechanism may be used to establish a relationship between information in fields of a data structure, including through the use of pointers, tags or other mechanisms that establish relationship between data elements.

[0194] When implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers.EXAMPLES

[0195] The various inventive embodiments of the disclosure having been described above, are further illustrated in the following examples. These Examples are offered by way of illustration, and not limitation. Materials and Methods for Examples 1–9

[0196] Tissue preparation. Fresh human tonsil tissues, harvested from live donors, were minced using sterile surgical scissors and transferred to 1X Hanks’ Buffered Salt Solution (HBSS) (Sigma, Cat: H8242) with 5 mg / mL DNase I (Roche, Cat: 10104159001) and 2.5 mg / mL Liberase (Roche, Cat: 5401127001). Samples were processed using the GentleMACS tissue dissociator and incubated at 37 C for 1 hour. After digestion, the homogenized tissue was vacuum filtered through a 1000 μm cell strainer (pluriStrainer, Cat: 43-51000-03) followed by a 100 μm cell strainer (pluriStrainer, Cat: 43-51000-51) to achieve a single cell suspension. The filtered cell suspension was RBC lysed (Roche, Cat: 11814389001), washed in complete media (RPMI with 7.5% HI-FBS, 1% normocin, 1X penicillin-streptomycin, 1X L-glutamax, 1X MEM-NEAA, 1mM sodium pyruvate, 25 mM HEPES, 1.5X insulin-transferrin-selenium), and finally the tonsil cells were cryopreserved in CryoStor (StemCell, Cat: 100-1061) and stored in liquid nitrogen.

[0197] In general, tonsil cells (6.0 x 106cells in 100 μl complete media) were plated into the top chamber of a Transwell 24-well permeable support with 0.4 μm pores (Costar, Cat: 3397) with the lower chamber containing 1 mL of complete media. On day 3 of culture, cultures were supplemented with 0.5 μg / mL B cell-activating factor (BAFF; Biolegend, Cat: 559606) into the bottom chamber. Tonsil cells were maintained in culture up to 21 days, with media exchange and BAFF re-stimulation occurring approximately every 3 days. For all antigen stimulations, the indicated amount of the indicated antigen was added to the top chamber of the culture (diluted to 10uL). Cultures followed varying antigen administration schedules based on the experimental design; all single administration cultures were treated with antigen on D0 only, all multi-administration cultures were treated with antigen or clinical molecule on D0, D7 and D10 unless otherwise indicated. Cultures were typically harvested on D14 unless otherwise indicated. Response rate (i.e., immune response) was determined by assessing change in plasmablast proportion (of CD19+ cells) by flow cytometry (untreated vs. antigen-treated) or by change in antigen-specific antibody secreting cells as measured by antigen specific B cell ELISpot (untreated vs. treated). Generally, a responder culture (i.e., a culture generatingan immune response against the stimuli) was defined as a donor culture that demonstrated a greater than 2-fold increase in either of the readouts described.

[0198] ELISpot. Tonsil cells (6.0 x 106cells in 100 μl complete media) were plated into the top chamber of a Transwell 24-well permeable support with 0.4 μm pores (Costar, Cat: 3397) with the lower chamber containing 1 mL of complete media. Cultures were left untreated or stimulated for 0, 7, 14, or 21 days with Live Attenuated Influenza Vaccine (LAIV) (Seqirus), Tetanus (List Biological Laboratories or HemaCare), or Keyhole limpet haemocyanin (KLH) (Sigma). At experimental endpoint, cells were harvested and plated into 96-well filter plates with PVDF membranes (Millipore, Cat: MSIPS4510) that were coated with either goat anti-human IgG (Jackson Immunoresearch, Cat: 109-005-170), goat anti-human IgM (Jackson Immunoresearch, Cat: 109-005-129), or corresponding antigen [Influenza A / Influenza B proteins (Sino Biological), KLH (Sigma), or tetanus (List Biological Laboratories or HemaCare)] for the detection of antigen presenting cells (APCs). Cells were plated in triplicates, with 25x104total live cells seeded per well (detection of IgG / IgM) or 140 x104total live cells per well (detection of antigen). Cells were incubated at 37 C / 5% CO2for 24 hours (total IgG / IgM) or 48 hours (antigen specific), and then plates were washed with 1X PBS. For detection of IgG / IgM secretion, plates were stained with horseradish peroxidase-conjugated anti-IgG / IgM secondary antibody. For detection of antigen specific antibody secretion, plates were first stained with the appropriate biotinylated anti-IgG or anti-IgM secondary antibody, followed by horseradish- peroxidase conjugated streptavidin for signal amplification. Plates were then washed with 1X PBS and developed with AEC substrate, washed with deionized water, and left to air dry overnight. Finally, plates were read on the S6 Ultimate M2 Analyzer.

[0199] Microscopy and Immunofluorescence. Tonsil cells (2.0 x 106) were plated into a 96- well flat bottom plate (Corning, Cat:3904), stimulated with or without 3.5 μg influenza vaccine (Seqirus) or 1 μg KLH (Sigma), and cultured for 14 days at 37 C / 5% CO2 in complete media. Brightfield images were acquired using the Opera Phenix High Content Screening System (10X, Air objective) and the Harmony Analysis Software on days 0, 1, 2, 3, 7, 10 and 14. Image analysis was performed using Signals Image Artist (SImA). In brief, the sum area (μm2) of tonsil aggregates per field of view (FOV) was determined using the texture analysis function and data was averaged over 9 FOVs per well.

[0200] Immunofluorescent staining was performed using the following conjugated primary antibodies with extracellular epitopes: CD20-488 (R&D Systems, Cat:FAB42252G), CXCR4-647(R&D Systems, Cat:FAB170R), CD3-647 (R&D Systems, Cat:FAB10R), CD35-BV421 (Biolegend, CAT: 333415), and Hoechst 33342 (ThermoFisher, Cat: H1399). Isotype controls: Rabit-IgG-488 (R&D Systems, Cat:IC1051G), Mouse IgG2A-647 (R&D Systems, Cat:IC003R), Mouse IgG1-647 (R&D Systems, Cat:IC002R), and Mouse IgG1-BV421(Biolegend, Cat:400157). Live cell staining was performed by first centrifuging antibodies at 10,000xG for 3 minutes, followed by adding the antibodies directly to cells in complete media and incubating for 25 minutes at 37 C / 5% CO2 .Cells were stained with 1 ug / mL Hoechst for 5 minutes at RT, washed twice in phenol-red free RPMI imaging media (Gibco, Cat: 3240414), and then imaged in phenol-red free RPMI imaging media on the Opera Phenix High Content Screening System using the 20X Water objective. Sample z-stacks were taken at 10 μm slices.

[0201] Flow Cytometry. Cells were harvested from the top chamber of the Transwell culture plate, ensuring sufficient mixing to capture all cells. Harvested cells were transferred to a 96-well v- bottom plate. Cells were washed with 100uL of PBS and stained for viability following the protocol outlines in the Live / Dead Fixable Viability Dye Staining Kit (808 / 876) (Thermo). Cells were washed twice in PBS and resuspended in 50uL of Brilliant Violet stain buffer with Human TruStain Fc Block (BioLegend). After a 10-minute incubation, appropriate cell surface antibodies were added and cells were incubated for 45 minutes. Cells were then washed twice and read on an appropriate flow cytometer. Example 1: The In vitro Tonsil Cell Model Possesses the Complex Spatial Architecture of a Human Secondary Lymphoid Tissue (SLT).

[0202] Existing models for antibody discovery and immunogenicity studies have inherentlimitations. Therefore, the goal of this work was to develop an in vitro model of human secondary lymphoid tissue (SLT) capable of overcoming these limitations by recapitulating complex immune responses against novel antigens. To this end, cells derived from fresh human tonsil tissue where cultured under conditions as described herein that induced cell reaggregation in culture. These cell culture aggregates were first characterized for their ability to mimic the cellular composition and complex spatial architecture of a SLT, including germinal center formation with representative lightand dark zones.

[0203] Fresh tonsil tissue, harvested from live donors, was subject to mechanical andenzymatic dissociation to create a single-cell suspensions for culture as described above. Tonsil tissue derived cells (6.0 x 106) were seeded into 24-well Transwell plates in complete culture media. Within48 hours in culture, the cells were found to spontaneously form aggregates that varied by size and morphology depending on the donor (see FIGs.1A and 1B). It was also confirmed that tonsil cells can re-aggregate if seeded on PVDF membranes or polystyrene TC-treated plates (FIG.1C).

[0204] Confocal microscopy was performed on cells cultured for 3 days to visualize the proportion of lymphocytes present post-enzymatic and mechanical tissue dissociation. Live cells were stained for extracellularly bound CD3 (T cells), CD20 (B cells), and Hoechst (nuclei). As shown in the immunofluorescence images of FIGs.2A and 2B, while a diverse cell population is present, a large proportion of cells in the tonsil cultures are lymphocytes (B and T cells). Furthermore, it was confirmed that the proportions of lymphocytes vary from donor to donor as expected.

[0205] Three dimensional imaging of the cultures confirmed the formation of germinal centercores within the tonsil culture aggregates. The germinal center is a specialized microstructure that forms within SLTs in response to antigenic stimulation to produce antibody secreting plasma cells and memory B cells. Germinal centers are organized into two major zones, i.e., a dark zone and a light zone. In the dark zone, maturing B cells undergo gene mutations that modify their antigen receptors for binding to foreign antigen. The dark zone is characterized by a population of B cells expressing high levels of the chemokine receptor, CXCR4. The light zone of the germinal center is where B cells having high affinity antigen receptors are selected. The light zone is characterized by a B cell population that does not express CXCR4, and by the presence of CD35+follicular dendritic cells.

[0206] Immune cell aggregates were stained for markers of B cells (anti-CD20-488), T cells(anti-CD3-647), and a marker of germinal-center dark zones (anti-CXCR4-647). The aggregates were then imaged as a z-stack (10 steps at 10 um intervals) producing a three-dimensional image to analyze the spatial orientation of lymphocytes within the aggregates. It was found that within the spontaneously forming cellular aggregates, the lymphocytes arrange themselves such that the B cells exist primarily within the core while the T cells cluster around the periphery as shown in the image of FIG. 3A. Importantly, CXCR4-positive cells were found to exist only within the center of the aggregate and were surrounded by B cells which mimics a germinal center-like dark zone found withinlymph nodes (see FIGs. 3B and 3C).

[0207] To confirm germinal center-like structure formation in culture, tonsil aggregates were stained for CD20 (B cells) and CXCR4 (marker of germinal center dark zones) (FIG. 4A) as well as CXCR4 and CD35 (marker of follicular dendritic cell / germinal center light zone) (FIG. 4B). These data reveal aggregates containing germinal center-like organization and this organization is maintainedin culture for at least 14 days. Overall, these data suggest that the aggregates are composed of a diverse array of immune cell types similar to those found in the lymph node and that the tonsil culture model produces germinal-center like structures critical for modelling the adaptive immune response in vitro. Example 2: The Lymphoid Tissue-Derived Cell Culture Model Possesses Immune Responsive Cell Populations

[0208] In addition to mimicking the complex spatial organization of the SLT, the in vitro tonsil model described herein possesses the diverse immune-responsive cellular composition characteristic of a SLT.

[0209] B cell composition in the in vitro tonsil model was characterized in unstimulated cultures (at D0 and D14 of culture) and in cultures stimulated with influenza antigen at day 14. Cryopreserved human tonsil cells were thawed and seeded into a 24-well Transwell plate at 6.0 x 106cells per well in complete tonsil media. Cells were stimulated with influenza antigen on Day 0 (D0) and cultured for 14 days. Flow cytometry staining was performed on tonsil cells to identify B cell subpopulations at D0 and D14 with and without influenza stimulation (FIG. 5A). Enhanced populations of plasmablasts (CD27+CD38++) and germinal center (GC) B cells (CD27+CD38+) were observed across multiple donor cultures following influenza stimulation (FIG.5B, compare graphs of B cell D14 unstimulated (unstim) to B cell D14 influenza (Flu) stimulated). Additionally, there was a reduction in naïve (CD27-CD38-) and pre-GC (CD27-CD38+) B cell populations in the stimulated populations across multiple donors (FIG. 5B, compare graphs of D14 unstimulated to D14 influenza stimulated).

[0210] T cell composition in the in vitro tonsil model was also characterized in unstimulated cultures (at D0 and D14 of culture) and in cultures stimulated with influenza antigen at D14. Cells were stained and identified by flow cytometry for CD8 (CD3+CD8+), CD4 (CD3+CD4+), double- positive (DP) T cells (CD3+CD4+CD8+), double-negative (DN) T cells (CD3+CD4-CD8-), and follicular helper T cells (Tfh) (CD4+CXCR5+) (FIG.6A) The proportions of each T cell subset across multiple donor populations at D0 and D14 of unstimulated culture and at D14 after stimulation with influenza antigen are provided in the graphs of FIG.6B. The cultures comprise diverse T cell subtypes, with a notable abundance of Tfh cells, which remained consistent throughout the incubation period and following influenza stimulation.

[0211] The in vitro tonsil cell cultures were also assessed for the presence of non-B and non- T cell immune populations. Flow cytometry staining demonstrates the presence of CD11b+or CD14+macrophages (FIGs. 7A-7B), CD11c+dendritic cells (FIGs. 8A-8B), and conventional dendritic cells (cDCs) expressing clec9+(FIGs.8A-8B). While there was variability in macrophage and dendritic cell populations among donors, these populations were maintained throughout the culture period and following influenza stimulation. Notably, a distinct population of clec9+ cDC1 cells was consistently observed, validating the ability of tonsil organoid cultures to recapitulate accurate antigen processing and presentation pathways and resulting cellular immune responses.

[0212] Follicular dendritic cells (fDCs) are necessary for the spatial organization of a functional germinal center as well as the appropriate activation and maturation of GC B cells. Therefore, tonsil organoids, generated as described in herein, were assessed for the presence of follicular dendritic cells. Defined as CD45- / CD90+ / PDPN+ / CD35+ / and CD31- cell population, all tonsil cultures possessed a clear and discernible fDC population that varied in size from donor to donor. Example 3: Multi-dose Administration Schedule Required to Detect De Novo B Cell Immune Response to Candidate Therapeutic Molecules

[0213] Immune responses to novel and recall antigens are different from multiple perspectives, including kinetics and cellular interaction cascades. To determine if the tonsil culture could model these differences in vitro, immune cell cultures were established and subject to different stimulation schedules. In particular, cultures were stimulated either once (at D0) or three times (at D0, D7, and D10) with a recall antigen (Afluria Tetra Influenza vaccine at 3.5 μg) or a novel antigen (KLH at 1 μg). Changes in plasmablast proportion were assessed by flow cytometry after 14 days.

[0214] As demonstrated in the representative flow plots of FIGs. 10A, a single exposure to a recall antigen induced a significant expansion of plasmablasts (compare upper right population of “Plasma” cells in the Unstimulated and Recall antigen x 1 plots of FIG.10A), while multiple exposures to the recall antigen drove exhaustion and a near total depletion of plasmablasts (see FIG.10A, bottom right plot, compare upper right population of “Plasma” cells in the Unstimulated and Recall Antigen x3 plots). Conversely, a single exposure to a novel antigen resulted in no significant increase in plasmablast expansion after 14 days (compare upper right population of “Plasma” cells in the Unstimulated and Novel Antigen x1 plots of FIG. 10B). However, multiple exposures to the novel antigen induced a significant response and drove dramatic expansion of the plasmablast population (compare upper right population of “Plasma” cells in the Unstimulated and Novel Antigen x 3 plotsof FIG. 10B). This data demonstrates the concept that modeling B cell responses to recall vs. novel antigens is a distinct process that requires a unique protocol and schedule. Example 4: Timing of Cytokine Introduction into Lymphoid Tissue-Derived Cell Culture Critical for Generating Immune Responsive Cultures

[0215] Cytokines play a major role in regulating immune responses. B-cell Activating Factor (BAFF) is a critical regulator of B cell survival, proliferation and maturation. Competing for access to cells that secrete BAFF in the germinal center light zone forms a basis of selection for antigen specific B cell expansion and eventual affinity maturation. Here it was tested whether the timing of the addition of exogenous BAFF to the culture platform impacted response characteristics to both recall and novel antigens.

[0216] Tonsil cultures were established and stimulated with Imovax Rabies Vaccine (~0.025 IU Rabies antigen) on D0, D7 and D10 of culture while exogenous supplementation with BAFF began on D0, D3, D5 or D7 of culture. After 14 days, total IgM secreting cells were quantified by B cell ELISpot. In all 4 donors tested, stimulation with the rabies vaccine induced a significant increase in IgM secretion, however, the magnitude of this response was directly correlated with the timing of exogenous BAFF supplementation, with delayed addition of BAFF resulting in significantly more robust responses (compare D0 BAFF to D3 and D5 BAFF plates of FIG.11A).

[0217] As delaying supplementation of exogenous BAFF to D3 of culture resulted in more robust responses after stimulation with the Imovax Rabies Vaccine, whether this correlation held for recall (Afluria Tetra) and novel (KLH) antigen responses was also tested. Cultures were stimulated with 2.5 μg total protein of Afluria Tetra Flu vaccine at D0 and either received no additional cytokine supplementation or were supplemented with exogenous BAFF at D0 or D3 of culture. After 14 days, antigen (HA) specific antibody secreting cells were characterized and quantified by B cell ELISpot. As indicated, no supplementation with BAFF resulted in a 20% responder rater (showing a >2x expansion of Ag+ ASCs after 14 days) while supplementation at D0 resulted in a 10% responder rate (FIG. 11B, left graph). Consistent with data of FIG. 11A, delaying BAFF supplementation to D3 resulted in an 80% response rate against influenza HA (FIG.11B, left graph).

[0218] The novel antigen stimulated cultures (FIG.11B, right panel) were stimulated with 1μg of KLH on D0, D7 and D10 and supplemented with BAFF following the same schedule described above. After 14 days, the response rate was determined by measuring donor cultures producing anti- KLH antibodies as determined by Ag-specific ASC quantification by ELISpot. Lending furthercredence to the importance of timing, a 0% responder rate against KLH was observed when cultures were either not supplemented with exogenous BAFF or were supplemented at D0. However, when BAFF supplementation was delayed until D3 of culture, a 60% response rate was observed (FIG.11B, right graph). Example 5: Lymphoid Tissue-Derived Cell Cultures are Capable of Generating Recall Response

[0219] Tonsil tissue-derived cell cultures were established as described supra (see Materials and Methods) and stimulated with the Afluria Tetra Flu Vaccine (1 or 5 μg total protein) at D0, followed by supplementation with exogenous BAFF beginning at culture D3. A significant expansion of plasma cells in vaccine stimulated cultures was observed at D7 of culture as demonstrated by the representative flow plots of FIG. 12A and summary data graph of FIG. 12B. Additionally, anti-Flu- specific IgM antibodies were detected in stimulated culture supernatants after 14 days of culture (FIG. 12C). This data indicates that with the correct schedule of cytokine supplementation the tonsil cultures exhibit robust responses against recall antigens in vitro which culminate in anti-antigen antibody production. Example 6: Lymphoid Tissue-Derived Cell Cultures are Capable of Generating De Novo Immune Response to Highly Antigenic Stimuli

[0220] Tonsil tissue-derived cell cultures were established as described supra (see Materials and Methods) and stimulated with the model novel antigen KLH (0.1μg or 1 μg) at D0, D7 and D10 in conjunction with supplementation with exogenous BAFF beginning at culture D3. A significant expansion of plasma cells in KLH stimulated cultures was observed at D7 of culture as demonstrated by the representative flow plots of FIG.13A and summary data graph of FIG.13B. Additionally, anti- KLH IgM were detected in stimulated culture supernatants at D14 (left graph of FIG. 13C) and anti- KLH IgG were detected in culture supernatant at D17 of culture (right graph of FIG. 13C). This data indicates that the correct schedule of cytokine supplementation can drive robust responses against a novel antigen in vitro to culminate in the production of class switched antigen specific antibody production after 17 days of culture.Example 7: Lymphoid Tissue-Derived Cell Cultures are Capable of Predicting Immunogenicity of Clinical Therapeutic Molecules

[0221] In order to assess the potential of this platform to serve as an immunogenicity screening tool, the potential of cultures to respond to clinically relevant molecules was evaluated. A panel of clinical molecules (or associated biosimilars) with a range of clinical ADA rates was utilized to perform this assessment (see Table of FIG.14A). Tonsil cultures were established as described supra (see Materials and Methods). The clinical molecules were administered on Days 0, 7, and 10 and BAFF was administered on Day 3 as outlined in the top panel of FIG.14A. After 14 days, the resulting immune responses were characterized by flow cytometry-based assessment of antigen-induced plasmablast expansion (FIG. 14B) and the quantification of antigen-specific antibody secreting cells by ELISpot (FIG.14C). As demonstrated in the graph of FIG.14B, stimulation of cultures with several clinical molecules resulted in significant expansion of the plasmablast population. When compared to the known clinical ADA rates, a clear correlation between responder rate in the tonsil culture (>1.5x plasmablast expansion) and clinical ADA rate was observed. Similarly, when clinical molecule specific antibody secreting cells were quantified by ELISpot, responses against a significant number of the clinical molecules were detected (FIG. 14C, left graph). Once again, when compared to the known clinical ADA rate, the responder rate (>1.5x expansion of Ag-specific ASCs) was highly correlated with clinical ADA rate (FIG.14C, right graph). Collectively, this data demonstrates that the lymphoid cell cultures are capable of modeling responses against clinically relevant molecules and that the response characterization aligns well with available clinical data. Thus, the lymphoid cultures of the present disclosure are suitable for predicting the clinical immunogenicity of a candidate therapeutic molecule. Example 8: Lymphoid Tissue-Derived Cell Cultures are Capable of Detecting Non-Sequence based Immunogenicity of Clinical Therapeutic Molecules

[0222] In FIG.14, the capacity of the platform to effectively model responses against clinically relevant therapeutic molecules was demonstrated. In general, all the molecules tested in Example 7 contained sequence-based liabilities. Clinical immunogenicity, however, can be driven by several mechanisms and is not always dependent on the presence of immunogenic epitope(s). In this Example, the immune response against a clinically relevant molecule that possessed no obvious sequence-based risks and had low predicted immunogenicity in standard T-cell-based assays but high clinical immunogenicity was tested (FIG. 15A). In this case, the molecule in question was anantibody / cytokine mimetic fusion protein that had immunomodulatory capacity. Tonsil cultures were established as described supra (see Materials and Methods). The antibody / cytokine mimetic fusion protein or the corresponding antibody alone was administered on Days 0, 3, and 10 and BAFF was administered on Day 3 as outlined in the top panel of FIG.15A.

[0223] As demonstrated here, stimulation with the complete Ab / cytokine fusion in the tonsil culture model resulted in an 81% responder rate as determined by flow cytometric assessment of plasmablast expansion (FIG. 15B, left graph) and a 64% responder rate as determined by quantification of Ag-specific antibody secreting cells as determined by ELISpot (FIG. 15B, right graph). However, exposure to the antibody arm alone (without the cytokine) induced no measurable immune response in the tonsil cultures suggesting that the presence of the cytokine mimetic was responsible for driving the immunogenicity of the parent fusion molecule (see FIG. 15B, Ab Alone). Stimulation with the Ab / cytokine fusion molecule also resulted in significant expansion of Tfh cells in a significant number of responding donors (FIG.15C). Collectively this data demonstrates that the lymphoid cell cultures are capable of recapitulating responses against clinical molecules that carry non-sequence based immunogenic liabilities. Thus, the lymphoid cultures of the present disclosure are useful for predicting non-sequence based immunogenic liabilities of candidate therapeutic molecules.

[0224] In addition to the antibody fusion protein, the immune response against another clinically relevant molecule that possessed no obvious sequence-based risks but was demonstrated to form large immune complexes in the presence of its target was also tested. This bispecific TNF- TL1A antibody molecule had low predicted immunogenicity in standard T-cell-based assays but high clinical immunogenicity (100%) (see Kroenke et al., Front. Immunol. 12:782788 (2021)). Tonsil cultures were established as described supra and the bispecific antibody was administered on Days 0, 7, and 10 with BAFF administered on Day 3 as outlined in the top panel of FIG.16A.

[0225] As demonstrated here, stimulation with the full bispecific antibody in the tonsil culture model resulted in a 59% responder rate as determined by flow cytometric assessment of plasmablast expansion (FIG. 16B, left graph) and a 54% responder rate as determined by quantification of Ag- specific antibody secreting cells as determined by ELISpot (FIG. 16B, right graph). However, exposure to either of the Fab arms of the parent antibody alone (which are incapable of forming similarly acting immune complexes) resulted in no measurable anti-drug response in culture (FIG. 16B, Arm 1 Fab and Arm 2 Fab). Collectively this data demonstrates that the lymphoid cell cultures described herein are capable of recapitulating responses against clinical molecules that carry non-sequence based immunogenic liabilities. Thus, the lymphoid cultures of the present disclosure are useful for predicting non-sequence based immunogenic liabilities of candidate therapeutic molecules. Example 9: Reducing Donor-related Background Proliferation in Tonsil Cell Cultures Improves the Sensitivity of Immunogenicity Detection

[0226] Initial efforts to measure earlier indices of immunogenicity in the tonsil cell culture model, e.g., T cell proliferation, were hampered by high and / or variable levels of background cell activation and proliferation in unstimulated cultures across the cohort of donor samples. This variability in background cell activation and proliferation is a consequence of utilizing primary donor tissue obtained from a heterogenic donor population (i.e., variability in the status of donor subjects results in variability of the derived tissue). High background immune cell activation / proliferation is problematic because it masks a de novo immune response to a candidate therapeutic molecule by the remaining naïve (non-activated) immune cells in the cultures.

[0227] To normalize the level of background cell activation and proliferation across a donor cohort, the addition of IL-4 and GM-CSF to the culture media was tested. As shown in FIG. 17, the addition of IL-4 (25 ng / mL) and GM-CSF (100 ng / mL) to culture media of unstimulated cultures significantly reduced background IgM and IgG secretion in unstimulated cultures. The level of IgM and IgG antibody secreting cells at day 14 in non-stimulated, non-IL-4 / GM-CSF supplemented cultures as measured by ELISpot is shown in the top panel of FIG. 17. In comparison, the addition of IL-4 and GM-CSF to the cell culture media significantly reduced the number of plasmablasts and plasma cell phenotypes detected within the B cell compartment of the cultures as shown in the corresponding bottom panel of FIG.17. Reducing background proliferation was found to be critical, in some donor-derived cultures, for detecting even positive control signals. As shown in FIG. 18, without the addition of IL-4 and GM-CSF, an immune response (as measured by the fold increase in ovalbumin-specific antibody production in treated vs. non-treated cells) to the highly immunogenic antigen, ovalbumin was not detected in two donor-derived culture samples (donor 2 and donor 4). However, after culturing cells from the same donors in the presence of IL-4 and GM-CSF, a >2-fold increase in ovalbumin antibody production was observed in treated vs. non-treated cultures and the response rate across the entire donor cohort increased from 50% to 100% responders.

[0228] In addition to IL-4 media supplementation, it was discovered that removing CD25+ immune cells, which include activated and regulatory T cells and regulatory B cells, from the isolated tonsil cell preparation prior to initiating cell culture further aided in reducing background proliferationto allow for more sensitive detection of a de novo immune response. As shown in FIG.19, depletion of CD25+ immune cells (using the EasySep™ Human Pan-CD25 Positive Selection Depletion Kit (Stemcell™ Technologies) prior to culture establishment increased the magnitude of the antigen- specific immune response as determined by quantification of ovalbumin-specific antibody secreting cells by ELISpot. Example 10: Detection of T Cell Proliferation in Lymphoid Tissue-Derived Cell Cultures to Facilitate Rapid, High-Throughput Immunogenicity Screening

[0229] The preceding Examples demonstrate how the tonsil cell culture model is utilized to detect de novo antigen-specific (i.e., candidate therapeutic molecule-specific) immune responses. To expand the utility of this model, the ability to detect early surrogate markers of this de novo immune response was investigated. Because the tonsil cell culture model contains the complete human immune cell repertoire from secondary lymphoid tissue it has the potential to outperform standard immunogenicity assays (e.g., PBMC assay or DC:T assay) that are based on cell cultures containing only specific populations. The ability to detect early surrogate markers of immunogenicity, such as T cell activation and / or proliferation, also facilitates adaptation of the model to a rapid, high throughput immunogenicity screening tool that will enhance selection of non-immunogenic candidate therapeutic molecules earlier in development.

[0230] Accordingly, to assess T cell proliferation in the tonsil model, donor-derived tonsil tissue was processed as outlined above (see Materials and Methods). However, CD25+ cells were removed from the tonsil tissue cell cultures prior to seeding using the EasySep™ Human Pan-CD25 Positive Selection Depletion Kit (Stemcell™ Technologies). CD25-depleted tonsil cells were resuspended at 7.5 x 106cells / mL in RPMI supplemented with 25 ng / mL of recombinant human IL-4 protein (Sino Biological, Cat # 11846-HNAE), and 200 μL of the cell suspension was plated into flat bottom tissue culture plates. Test molecules (300 nM) were added to the culture on day 0 and cells were incubated for 7 days. On day 6 of culture, 5 μM of EdU (Click-iT™ Plus EdU Flow Cytometry Kit from ThermoFisher, Cat: C10635) was added to each culture. On day 7 of culture, cells were harvested and the protocol for analyzing DNA replication in proliferating cells was performed as outlined in the Click-iT™ Plus EdU Kit.

[0231] The stimulation index of tested molecules as a measure of proliferation was calculated as follows: the number of EdU+CD4+T cells per 100,000 live cells in test molecule stimulated wellsdivided by the number of EdU+CD4+T cells per 100,000 live cells in unstimulated wells from the same donor.

[0232] To assess the utility of CD4+T cell proliferation as an indicator of immunogenicity in the tonsil culture model, CD25-depleted tonsil cell cultures were initiated in media containing IL-4 and 300 nM of the highly immunogenic ovalbumin (OVA) antigen. As described above, on day 6 of culture, EdU was added and CD4+T cell proliferation was measured on day 7. As shown in FIG.20A, ovalbumin was capable of inducing CD4+T cell proliferation that was significantly above background levels in unstimulated cultures from the same donors. Additionally, CD4+T cell proliferation in this model is also capable of differentiating between a clinically verified non-immunogenic antibody therapeutic and highly immunogenic therapeutic molecules (FIG.20B).

[0233] As noted above, the preceding Examples have demonstrated that the tonsil cell culture model described herein is capable of producing antigen-specific antibodies against clinically relevant molecules after 14 days in culture, the frequency of which was correlated with clinical immunogenicity. In this Example, a second version of the tonsil cell culture model (i.e., a model devoid of CD25+ cells and cultured in the presence of IL-4) is capable of distinguishing immunogenicity of clinically relevant molecules after only 7 days based on the assessment of CD4+ T cell proliferation. Example 11: Development of an Antigen Delivery System to Facilitate Therapeutic Antibody Production in Tonsil Cultures

[0234] Artificial antigen delivery scaffolds were designed to mimic antigen presenting follicular dendritic cells (fDCs) to stimulate B cell survival activation and maturation (FIG. 21). Mesoporous silica micro-rods (MSRs) (FIG. 21A) were coated in a biotin-liposome layer and subsequently functionalized utilizing biotin-streptavidin chemistry (FIG. 21B). After the addition of streptavidin, biotinylated human CD64 (FIG.21C) and human CD320 (FIG.21E) proteins were added to mimic the presence of Fc receptors and mediate interaction with germinal center B cells respectively. His-tagged antigen pre-complexed to a human anti-His antibody and added to the complex via CD64 binding to human IgG Fc. Together, the CD64 / human anti-his / HA-his and CD320 provides an avenue for antigen presentation and increased B cell interaction that aims to resemble that of a natural fDC. This approach is intentionally designed to be flexible to allow functionalization with various biotinylated proteins or HIS-tagged antigens of interest.

[0235] Immune cell cultures from two different donors were stimulated with either influenza hemagglutinin (HA) loaded on antigen delivery scaffolds or as a soluble protein and cultured for 14 days. After 14 days, supernatants were collected and screened for influenza specific secreted IgG antibodies. In both donors, HA presented via the antigen delivery scaffolds stimulated cultures to produce antigen specific antibodies, whereas culture stimulated with the soluble HA failed to generate any HA specific antibodies (FIG. 22). This data demonstrates the importance of an antigen delivery system in the tonsil cultures that mimics antigen presenting follicular dendritic cells (fDCs) and stimulate B cell survival activation and maturation to facilitate antibody production.

[0236] Each reference cited herein is hereby incorporated by reference in its entirety for all that it teaches and for all purposes.

[0237] The present invention is not to be limited in scope by the specific embodiments described herein, which are intended as single illustrations of individual embodiments of the invention, and functionally equivalent methods and components are also encompassed by the invention. Indeed, various modifications of the invention, in addition to those shown and described herein will become apparent to those skilled in the art from the foregoing description and accompanying drawings. Such modifications are intended to fall within the scope of the appended claims.

Claims

1. CLAIMS 1. An in vitro system, said system comprising: a plurality of mammalian lymphoid cell cultures, each cell culture comprising: lymphoid tissue-derived B cells and T cells in a cell culture well comprising culture media; and a candidate therapeutic molecule in the culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different major histocompatibility complex (MHC) class II alleles.

2. The in vitro system of claim 1, wherein the plurality of mammalian lymphoid cell cultures comprise at least five lymphoid cell cultures, wherein the at least five lymphoid cell cultures collectively express five different MHC class II alleles.

3. The in vitro system of claim 1, wherein the plurality of mammalian lymphoid cell cultures comprise at least ten lymphoid cell cultures, wherein the at least ten lymphoid cell cultures collectively express ten different MHC class II alleles.

4. The in vitro system of any one of claims 1–3, wherein the mammalian lymphoid cell cultures are human lymphoid cell cultures.

5. The in vitro system of any one of claims 1–4, wherein the plurality of different MHC class II alleles are a plurality of different HLA-DRB1 alleles.

6. The in vitro system of any one of claims 1–5, wherein the culture media 7. The in vitro system of claim 6, wherein the serum is human serum.

8. The in vitro system of claim 6, wherein the serum is fetal bovine serum.

9. The in vitro system of any one of claims 1–8, wherein the culture media comprises a B cell survival factor.

10. The in vitro system of claim 9, wherein the B cell survival factor is a B cell- activating receptor factor receptor (BAFFR) agonist.

11. The in vitro system of claim 10, wherein the BAFFR agonist is B cell-activating factor (BAFF).

12. The in vitro system of any one of claims 1-11, wherein each of the plurality of mammalian lymphoid cell cultures further comprise: lymphoid tissue derived follicular dendritic cells, dendritic cells, macrophages, endothelial cells, or any combination thereof.

13. The in vitro system of any one of claims 1-12, wherein each of the plurality of mammalian lymphoid cell cultures are devoid of CD25+ cells.

14. The in vitro system of claim 13, wherein the culture media comprises recombinant interleukin-4 (IL-4).

15. The in vitro system of any one of claims 1–14, wherein the candidate therapeutic molecule is present in the culture media at a concentration of about 100 nM to about 500 nM.

16. An in vitro method of predicting in vivo immunogenicity of a candidate therapeutic molecule, said method comprising: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived B cells and T cells in culture media, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering a first and second dose of the candidate therapeutic molecule to each of the plurality of cell cultures, wherein the second dose is administered between 3–7 days after administering the first dose; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures after administering the second dose of the candidate therapeutic molecule; assessing one or more markers of a de novo immune response in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures; and predicting in vivo immunogenicity of the candidate therapeutic molecule based on said assessing.

17. The method of claim 16, wherein the plurality of cell cultures are provided on day 0 of culture, and the first dose of the candidate therapeutic molecule is administered to the plurality of cell cultures on day 0 of culture.

18. The method of claim 16 or claim 17, wherein the administering achieves a concentration of the candidate drug in the culture media of about 100 nM to about 500 nM.

19. The method of claim 16, wherein said harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures is carried out 3-5 days after the second dose of the candidate therapeutic molecule is administered.

20. The method of any one of claims 16–19 further comprising: administering, prior to said harvesting, a third dose of the candidate therapeutic molecule to each of the plurality of cell cultures, wherein the third dose is administered 3–4 days after the second dose is administered.

21. The method of any one of claims 16–20 further comprising: introducing a B cell survival factor into the culture media of each of the plurality of cell cultures 3–5 days after administering the first dose of the candidate therapeutic molecule.

22. The method of claim 21 further comprising: supplementing, after the introducing, the cell culture media of each of the plurality of cell cultures with the B cell survival factor to maintain a constant concentration of the B cell survival factor in each of the plurality of cell cultures.

23. The method of claim 21, wherein the B cell survival factor is a B cell activating factor receptor (BAFFR) agonist.

24. The method of claim 23, wherein the BAFFR agonist is B cell activating factor (BAFF).

25. The method of any one of claims 16–24, wherein each of the plurality of mammalian lymphoid cell cultures are devoid of CD25+ cells.

26. The method of any one of claims 16–25, wherein the culture media comprises recombinant IL-4.

27. The method of claim 25 or claim 26 further comprising: introducing one or more cytokines into the culture media of each of the plurality of cell cultures 3–5 days after administering the first dose of the candidate therapeutic molecule, wherein the one or more cytokines is selected from IL-10, IL-6, IL-2, IL-21, and IL-15.

28. The method of any one of claims 16–27, wherein each of the plurality of mammalian lymphoid cell cultures further comprise: lymphoid tissue derived follicular dendritic cells, dendritic cells, macrophages, endothelial cells, or any combination thereof.

29. The method of any one of claims 16–28, wherein the one or more markers of the de novo immune response are selected from the group consisting of: (i) presence of anti-candidate therapeutic molecule antibody secreting cells in the harvested cells; (ii) presence of anti-candidate therapeutic molecule antibodies in the harvested cell culture supernatant; (iii) an increase in frequency of plasmablasts in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of plasmablasts in harvested cells of corresponding control cell cultures not administered the candidate therapeutic molecule; (iv) an increase in the frequency of germinal center B cells in harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of germinal center B cells in harvested cells of corresponding control cell cultures not administered the candidate therapeutic molecule; (v) an increase in the frequency of germinal center B cells and plasmablasts in harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of germinal center B cells and plasmablasts in harvested cells of corresponding control cell cultures not administered the candidate therapeutic molecule; (vi) an increase in frequency of CD4+ T cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of CD4+ T cells in harvested cells of corresponding control cell cultures not administered the candidate therapeutic molecule; (vii) an increase in frequency of T follicular helper cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of T follicularhelper cells in harvested cells of corresponding control cell cultures not administered the candidate therapeutic molecule; (viii) an increase in the frequency of activated dendritic cells in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of activated dendritic cells in harvested cells of corresponding control cell cultures not administered the candidate therapeutic molecule; (ix) an increase in the frequency of macrophages in the harvested cells of cell cultures administered the candidate therapeutic molecule compared to the frequency of macrophages in harvested cells of corresponding control cell cultures not administered the candidate therapeutic molecule; (x) any combination of (i)–(ix).

30. The method of claim 29, wherein the anti-candidate therapeutic molecule antibodies comprise IgM+antibodies, IgE+antibodies, IgG+antibodies, or any combination thereof.

31. The method of claim 16 further comprising: isolating B cells from the harvested cells, and sequencing antibodies produced by the isolated B cells.

32. The method of any one of claims 16–31, wherein the mammalian lymphoid cell cultures are human lymphoid cell cultures.

33. The method of claim 32, wherein the plurality of human lymphoid cell cultures comprise at least five human lymphoid cell cultures, wherein the at least five human lymphoid cell cultures collectively express five different MHC class II alleles.

34. The method of claim 32, wherein the plurality of human lymphoid cell cultures comprise at least ten human lymphoid cell cultures, wherein the at least ten human lymphoid cell cultures collectively express ten different MHC class II alleles.

35. The in vitro system of any one of claims 1-15 or the method of any one of claims 16–34, wherein the lymphoid tissue is tonsil tissue.

36. The in vitro system of any one of claims 1-15 or the method of any one of claims 16–34, wherein the candidate therapeutic molecule is a candidate protein therapeutic.

37. The in vitro system or method of claim 36, wherein the candidate protein therapeutic is an antibody, an antibody fragment, an antibody derivative, or an antibody-drug conjugate.

38. The in vitro system or method of claim 37, wherein the candidate protein therapeutic contains one or more non-protein components.

39. The in vitro system of any one of claims 1-15 or method of any one of claims 16–34, wherein the candidate therapeutic molecule comprises a candidate nucleic acid therapeutic.

40. An in vitro method of predicting in vivo immunogenicity of a candidate therapeutic molecule, said method comprising: providing a plurality of mammalian lymphoid cell cultures, each cell culture comprising lymphoid tissue derived CD25–B cells and T cells in culture media comprising recombinant IL-4, wherein the plurality of mammalian lymphoid cell cultures collectively express a plurality of different MHC class II alleles; administering the candidate therapeutic molecule to each of the plurality of cell cultures; harvesting the cells, culture supernatant, or both the cells and culture supernatant of each of the plurality of cell cultures 5-8 days after administering the candidate therapeutic molecule; measuring one or more markers immune cell activation in the harvested cells, harvested culture supernatant, or both from each of the plurality of cell cultures; and predicting in vivo immunogenicity of the candidate therapeutic molecule based on said measuring.

41. The method of 40, wherein the one or more markers of immune cell activation is T cell proliferation, said method further comprising: adding a cell proliferation marker to each of the plurality of cell cultures prior said harvesting, wherein said measuring comprises quantifying the cell proliferation marker in CD4+ T cells of each of the plurality of cell cultures.

42. A method of producing an in vitro immune responsive mammalian lymphoid cell culture, the method comprising:subjecting isolated mammalian lymphoid tissue to mechanical and enzymatic dissociation to produce a suspension of lymphoid tissue derived B cells, T cells, follicular dendritic cells, dendritic cells and endothelial cells; introducing the suspension of lymphoid tissue derived cells, after the subjecting, into a cell culture well comprising cell culture media, wherein the cell culture media comprises a candidate therapeutic molecule and does not contain a B cell survival factor; and adding the B cell survival factor to the cell culture media at 3-5 days after said introducing to produce the immune responsive mammalian lymphoid cell culture.

43. The method of claim 42 further comprising: supplementing the cell culture media periodically with the B cell survival factor to maintain a constant concentration of the B cell survival factor in the mammalian lymphoid cell culture.

44. The method of claim 42 or claim 43, wherein the B cell survival factor is a B cell activating factor receptor (BAFFR) agonist.

45. The method of claim 44, wherein the BAFFR agonist is B cell activating factor (BAFF).

46. The method of any one of claims 42–45 further comprising: depleting CD25+ cells from the suspension of lymphoid tissue derived cells prior to said introducing.

47. The method of any one of claims 42–45 further comprising: adding IL-4 to the cell culture media during said introducing, and culturing the suspension of lymphoid tissue derived cells in the presence of IL-4 for 3- 6 days.

48. The method of claim 47 further comprising: supplementing the culture media after 3–6 days of said culturing with one or more cytokines selected from IL-10, IL-6, IL-2, IL-21, and IL-15.

49. The method of any one of claims 42–48, wherein the concentration of the candidate therapeutic molecule in the culture media is about 100 nM to about 500 nM.

50. The method of any one of claims 42–48, wherein the cell culture media 51. The method of claim 50, wherein the serum is human serum.

52. The method of claim 50, wherein the serum is fetal bovine serum.

53. The method of any one of claims 42–52, wherein the candidate therapeutic molecule is a candidate protein therapeutic.

54. The method of claim 53, wherein the candidate protein therapeutic is an antibody, an antibody fragment, an antibody derivative, or an antibody-drug conjugate.

55. The method of claim 53, wherein the candidate protein therapeutic comprises non-protein subunits.

56. The method of any one of claims 42–52, wherein the candidate therapeutic molecule is a candidate nucleic acid therapeutic.

57. The method of any one of claims 42–56, wherein the mammalian lymphoid cell culture does not contain an adjuvant.

58. The method of any one of claims 42–56, wherein the mammalian lymphoid tissue is tonsil tissue.

59. The method of claim 58, wherein the mammalian lymphoid tissue is human tonsil tissue.

60. An in vitro mammalian lymphoid cell culture produced by the method of any one of claims 42–59.

61. An in vitro mammalian lymphoid cell culture, the culture comprising: mammalian lymphoid tissue derived B cells and T cells in a cell culture well comprising culture media; and a candidate therapeutic molecule in the culture media.

62. The cell culture of claim 61, wherein the in vitro mammalian lymphoid cell culture is devoid of CD25+ cells63. The cell culture of claim 61, wherein the candidate drug molecule is a candidate protein therapeutic.

64. The cell culture of claim 63, wherein the candidate protein therapeutic is an antibody, an antibody fragment, an antibody derivative, or an antibody-drug conjugate.

65. The method of claim 63, wherein the candidate protein therapeutic comprises non-protein subunits.

66. The cell culture of claim 61, wherein the candidate drug molecule is a candidate nucleic acid therapeutic.

67. The cell culture of any one of claims 61–66, wherein the cell culture and culture media do not contain an adjuvant.

68. The cell culture of claim 61, wherein the cell culture further comprises: mammalian lymphoid tissue-derived follicular dendritic cells, dendritic cells, endothelial cells, or any combination thereof.

69. The cell culture of any one of claims 61–68, wherein the mammalian lymphoid tissue is human tonsil tissue.

70. The culture of any one of claims 61–69, wherein the culture media comprises 71. The culture of any one of claims 61–70, wherein the cell culture further comprises: plasmablasts and / or plasma cells that secrete anti-candidate therapeutic molecule antibodies.

72. The culture of claim 71, wherein the anti-candidate therapeutic molecule antibodies comprise IgM+antibodies, IgE+antibodies, IgG+antibodies, or any combination thereof.

73. An in vitro mammalian lymphoid cell culture, said cell culture comprising: mammalian lymphoid tissue-derived B cells and T cells in a cell culture well comprising culture media; an antigen; and an antigen delivery system.

74. The in vitro mammalian lymphoid cell culture of claim 73, wherein the antigen delivery system comprises: a substrate; a lipid layer surrounding the substrate, an immune-complex receptor protein, wherein the immune-complex receptor protein is immobilized to a surface on the lipid layer; and an immune-complex receptor ligand, wherein the immune-complex receptor ligand is coupled to the antigen and is bound to the immobilized immune-complex receptor protein on the surface of the lipid layer.

75. The in vitro mammalian lymphoid cell culture of claim 74, wherein the antigen delivery system further comprises: a B cell survival factor, wherein the B cell survival factor is adsorbed to a surface of the substrate beneath the lipid layer.

76. The in vitro mammalian lymphoid cell culture of claim 75, wherein the B cell survival factor is a B cell activating factor receptor (BAFFR) agonist.

77. The in vitro mammalian lymphoid cell culture of claim 76, wherein the BAFFR is B cell activating factor (BAFF).

78. The in vitro mammalian lymphoid culture of any one of claims 73–77, wherein the mammalian lymphoid tissue-derived B cells and T cells are human lymphoid tissue-derived B cells and T cells.

79. The in vitro mammalian lymphoid cell culture of any one of claims 74-78, wherein the immune-complex receptor protein is a Fc receptor (CD64) protein, and the immune- complex receptor ligand is an Fc-containing polypeptide.

80. The in vitro mammalian lymphoid cell culture of claim 79, wherein the Fc- containing polypeptide is an antibody.

81. The in vitro mammalian lymphoid cell culture of any one of claims 74–78, wherein the immune-complex receptor protein is a complement receptor 1 (CR1) and the immune- complex receptor ligand is C3b.

82. The in vitro mammalian lymphoid cell culture of any one of claims 74–81, wherein antigen delivery system further comprises: a B cell co-stimulatory molecule, wherein said B cell co-stimulatory molecules is immobilized to the surface of the lipid layer 83. The in vitro mammalian lymphoid cell culture of claim 82, wherein the immobilized B cell co-stimulatory molecule is recombinant CD320.

84. The in vitro mammalian lymphoid cell culture of any one of claims 74-83, wherein the substrate is a porous silica substrate.

85. The in vitro mammalian lymphoid cell culture of claim 84, wherein the silica substrate is silica micro-rod, wherein the micro-rod comprises a length of between 50 μm to 800 μm.

86. The in vitro mammalian lymphoid cell culture of any one of claims 73-85, wherein the antigen delivery system comprises one or more adjuvants.

87. The in vitro mammalian lymphoid cell culture of any one of claims 73-86, wherein the cell culture further comprises human lymphoid tissue-derived follicular dendritic cells, dendritic cells, endothelial cells, or any combination thereof.

88. An in vitro method of generating antibodies against a target antigen, the method comprising: providing a cell culture comprising human lymphoid tissue derived B cells and T cells; introducing, to the cell culture, an antigen delivery system comprising the target antigen; and incubating the cell culture, after said introducing, under conditions suitable for B cells of the culture to produce antibodies against the antigen.

89. The in vitro method of claim 88, wherein the antigen delivery system comprises: a substrate, a lipid layer surrounding the substrate, an immune-complex receptor protein, wherein the immune-complex receptor protein is immobilized to a surface on the lipid layer; andan immune-complex receptor ligand, wherein the immune-complex receptor ligand is coupled to the target antigen and is bound to the immobilized immune-complex receptor protein on the surface of the lipid layer.

90. The in vitro method of 89, wherein the antigen delivery system further comprises: a B cell survival factor, wherein the B cell survival factor is adsorbed to a surface of the substrate beneath the lipid layer.

91. The in vitro method of claim 90, wherein the B cell survival factor is a B cell activating factor receptor (BAFFR) agonist.

92. The in vitro method of 91, wherein the BAFFR is B cell activating factor (BAFF).

93. The in vitro method of any one of claims 88–92, wherein the immune-complex receptor protein is a human Fc receptor (CD64) protein and the immune-complex receptor ligand is an Fc-containing polypeptide.

94. The in vitro method of claim 93, wherein the Fc-containing polypeptide is an antibody.

95. The in vitro method of any one of claims 88–92, wherein the immune-complex receptor protein is human complement receptor 1 (CR1) and the immune-complex receptor ligand is human C3b.

96. The in vitro method of any one of claims 88–95, wherein the antigen delivery system further comprises: a B cell co-stimulatory molecule, wherein said B cell co-stimulatory molecules is immobilized to the surface of the lipid layer 97. The in vitro method of claim 96, wherein the immobilized B cell co-stimulatory molecule is human CD320.

98. The in vitro method of any one of claims 88-97, wherein the substrate is a porous silica substrate.

99. The in vitro method of any one of claims 88-98, wherein the substrate is in the form of a micro-rod, wherein the micro-rod comprises a length of between 50 μm to 200 μm.

100. The in vitro method of claim 88, wherein the antigen delivery system comprises one or more adjuvants.

101. The in vitro method of claim 88, wherein the antigen delivery system comprises one or more proinflammatory cytokines.

102. The in vitro method of 88 further comprising: isolating the antibody producing cells from the culture after incubating, and characterizing binding function of antibodies produced by the isolated cells.

103. The method of claim 102, wherein said method further comprises: sequencing the antibodies produced by the isolated cells.

104. An antigen delivery system, comprising: a substrate; a lipid layer surrounding the substrate; an immune-complex receptor protein, wherein said immune-complex receptor protein is immobilized to a surface on the lipid layer; and an immune-complex receptor ligand, wherein the immune-complex receptor ligand is coupled to an antigen and is bound to the immobilized immune-complex receptor proteins on the surface of the lipid layer.

105. The antigen delivery system of claim 104, wherein the antigen delivery system further comprises: a B cell survival factor, wherein the B cell survival factor is adsorbed to a surface of the substrate beneath the lipid layer.

106. The antigen delivery system of claim 105, wherein the B cell survival factor is a B cell activating factor receptor (BAFFR) agonist.

107. The antigen delivery system of claim 106, wherein the BAFFR is B cell activating factor (BAFF).

108. The antigen delivery system of any one of claims 104–107, wherein the immune-complex receptor protein is a human Fc receptor (CD64) protein, and the immune-complex receptor ligand is an Fc-containing polypeptide.

109. The antigen delivery system of claim 108, wherein the Fc-containing polypeptide is an antibody.

110. The antigen delivery system of claims 104-107, wherein the immune-complex receptor protein is a human complement receptor 1 (CR1) and the immune-complex receptor ligand is human C3b.

111. The antigen delivery system of any one of claims 104-110, wherein the system further comprises: a B cell co-stimulatory molecule, wherein said B cell co-stimulatory molecules is immobilized to the surface of the lipid layer.

112. The antigen delivery system of claim 111, wherein the B cell co-stimulatory molecule is recombinant CD320.

113. The antigen delivery system of any one of claims 104-112, wherein the substrate is a porous silica substrate.

114. The antigen delivery system of claim 113, wherein the silica substrate is silica micro-rod, wherein the micro-rod comprises a length of between 50 μm to 800 μm.

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