Peptide-targeted layer-by-layer nanoparticle for glioblastoma treatment

Abstract

Particles are provided that include (a) a liposome having a negatively charged outer surface; (b) a first layer comprising poly-L-arginine (PLR), wherein the PLR is non-covalently associated with the negatively charged outer surface of the liposome; (c) a second layer, comprising hyaluronate (HA), wherein the HA is non-covalently associated with the first layer; and (d) a blood brain barrier-targeting peptide layer electrostatically coupled to the second layer; as are particles that are loaded with a therapeutic and their use for treating a brain cancer.

Description

[0001] MIT 25659 Peptide-Targeted Layer-by-Layer Nanoparticle for Glioblastoma Treatment Statement of Government Support This invention was made with government support under CA14051 awarded by the National Institutes of Health, and W81XWH-19-1-0257 awarded by Defense Health Agency, Medical Research and Development Branch. The government has certain rights in the invention. Sequence Listing Statement A computer readable form of the Sequence Listing is filed with this application by electronic submission and is incorporated into this application by reference in its entirety. The Sequence Listing is contained in the file created on May 30, 2024 having the file name “24- 0508-WO.xml” and is 9,926 bytes in size. Background Neurological disorders, including but not limited to brain tumors and neurological diseases, are the leading global cause of years of life lost and second leading cause of death, according to data published in 2019. However, development of new treatments for neurologic disorders has been challenging, largely due to poor drug transport across the blood-brain barrier (BBB) – the specialized vascular lining of the central nervous system. At least 95% of newly discovered candidate therapies are excluded from entering the brain – even in glioma tumors and neurological diseases commonly associated with “leaky” BBBs – and there is a critical need to develop drug carriers that can transport therapeutic cargoes across the BBB. Summary In a first aspect, the disclosure provides particles, comprising: (a) a liposome having a negatively charged outer surface; (b) a first layer comprising poly-L-arginine (PLR), wherein the PLR is non- covalently associated with the negatively charged outer surface of the liposome; (c) a second layer, comprising hyaluronate (HA), wherein the HA is non- covalently associated with the first layer; and (d) a blood brain barrier-targeting peptide layer electrostatically coupled to the second layer. In one embodiment, the particle has a ratio of about 0.05 to about 1 weight equivalent of PLR to liposome lipid bilayer, or a ratio of about 0.1 to about 0.8 weight equivalent of PLR to liposome lipid bilayer. In another embodiment, the particle has a ratio of about 0.3 to about 3 weight equivalents of HA to liposome lipid bilayer, or a ratio of about 0.6 to about 2.4 weight equivalent of PLR to liposome lipid bilayer, or a ratio of about 1.2 weight equivalent of HA to liposome lipid bilayer. In one embodiment, the liposome lipid bilayer comprises cholesterol; DSPC (1,2-distearoyl-sn-glycero-3-phosphocholine); DSPE (1,2- Distearoyl-sn-glycero-3-phosphoethanolamine); and DSPG (1,2-Distearoyl-sn-glycero-3- phosphoglycerol). In another embodiment, the targeting peptide comprises or consists of the amino acid sequence selected from the group consisting of SEQ ID NO:1-8. In a further embodiment, the particle has a ratio of about 0.05 to about 5 weight equivalents of the peptide to the liposome lipid bilayer, or a ratio of about 0.2 to about 2 weight equivalents of peptide to liposome lipid bilayer. In one embodiment, the particle further comprises a therapeutic encapsulated within an aqueous core of the liposome or the liposome lipid bilayer. In one embodiment, the therapeutic is a chemotherapeutic, including but not limited to trametinib, or a pharmaceutically acceptable salt thereof. In another embodiment, the particle comprises between about 0.5 weight % and about 3 weight % trametinib per mg of liposome lipid bilayer, or between about 0.5 weight % and about 2.5 weight % trametinib per mg of liposome lipid bilayer, or between about 0.5 weight % and about 2.4 weight % trametinib per mg of liposome lipid bilayer. In a further embodiment, the particle has a diameter range between about 50 nm to about 500 nm. The disclosure also provide pharmaceutical compositions, comprising (a) a plurality of the particles of any embodiment in which the particle comprises a therapeutic encapsulated within an aqueous core of the liposome or the liposome lipid bilayer; and (b) a pharmaceutically acceptable carrier. In one embodiment, the pharmaceutical composition is formulated for intravenous administration. The disclosure also provides methods for treating a cancer in the brain, comprising administering to a subject having a cancer in the brain the particle or pharmaceutical composition of any embodiment in which the particle comprises a chemotherapeutic encapsulated within an aqueous core of the liposome or the liposome lipid bilayer, in an amount effective to treat the cancer. In one embodiment, the cancer in the brain is a glioma or a glioblastoma. In another embodiment, the particle or pharmaceutical composition is administered intravenously. The disclosure also provides methods for making the particle of any embodiment of the disclosure, comprising electrostatically attaching the targeting peptides to the particles by mixing the positively-charged targeting peptides with the particles having the PLR and HA layers, and allowing attraction of opposite charges of the targeting peptide and the HA layer to electrostatically bind the targeting peptides to the HA layer. In one embodiment, the method further comprises loading a therapeutic into the particle. Description of the Figure Figure 1. Probing nanomaterial uptake behavior in the blood-brain barrier (BBB) using fluorescently labelled layer-by-layer nanoparticles (LbL-NPs). (a) The BBB derives its barrier properties primarily from endothelial cells, which are stitched together with tight junction proteins, but express receptors, transporters, and other machinery for cell- mediated uptake. (b) Using brain endothelial cell lines, three common assays for nanomaterial uptake for in vitro BBB models are transwell transport, monolayer association, and flow cytometry using fluorescently tagged nanoparticles. The output for transwell transport is fluorescence of material that has passed through the cell layer at a given time, while monolayer association and flow cytometry respectively report fluorescence of cell populations or individual cells. (c) LbL-NPs – used here to cross-compare the effects of nanoparticle stiffness and surface chemistry – comprise one of three fluorescently labelled and negatively charged cores: anionic liposomes (lipo), acid- terminated poly (lactic-co- glycolic acid) (PLGA), or carboxylated polystyrene (PS). The cores are electrostatically layered with a polycation layer, in this case poly-L-arginine (PLR). Finally, a polyanion outer surface layer is added. The outer layers used here are carboxymethyldextran (CMDex), hyaluronic acid (HA), poly-L-aspartic acid (PLD), poly-L-glutamic acid (PLE), and polysialic acid (PSialA), giving an overall negative charge to the NP surface. Figure 2. hCMEC / D3 based models of the BBB differ in their uptake of a library of layer-by-layer assembled nanoparticles. (a) LbL-NPs are formulated by incubating charged NP cores with oppositely charged polymer solutions, followed by removal of non- adsorbed polymer. For this work, anionic cores, one polycation (PLR) and five polyanions were employed to create polymer bilayers. (b) In cells grown on solid plasticware and treated with PS core nanoparticles, flow cytometry median fluorescence intensity measured at 4, 8 and 24 hours for nanoparticle positive cells differed by outer layer chemistry, with PLE outperforming the others. This trend was mirrored closely in (c) cells treated with PLGA core nanoparticles, while (d) cells treated with liposome-core nanoparticles showed greatest uptake with CMDex capped particles instead. (e) Monolayer association in cells grown on solid plasticware indicated a preferred uptake based on NP cores with medium or low stiffness, with the exception of bare liposomes. (f) Likewise, in monolayers grown on transwells, soft liposome-core nanoparticles transported across the monolayer to a greater degree than the stiffer polymer nanoparticles, regardless of surface chemistry. Data is reported as arithmetic mean ± standard deviation of three plate replicates, with three technical replicate wells per treatment per plate. Figure 3. Outer layer chemistries on liposome-core LbL-NPs influence cellular uptake and trafficking in hCMEC / D3 monolayers grown on transwell supports, as observed by fixed sample confocal microscopy. (a) LbL-NPs coated with HA or PLE colocalized with clathrin to a greater degree than liposomes, as assessed by the Mander’s coefficient of the clathrin and nanoparticle fluorescence signals, indicating that the LbL functionalization increases the rate of uptake by clathrin directed machinery. (b) In contrast, LbL functionalization did not change the colocalization of NPs with caveolin uptake machinery. (c) PLE coated LbL-NPs had the greatest non-specific uptake as measured by colocalization with 70 kDa dextran in vesicles. (d) Low colocalization of all NPs with EEA1 indicated that all of the formulations are processed quickly through early endosomes. (e) LAMP1 staining was largely independent of NP signal for liposomes and HA-coated NPs, but aggregated PLE-coated NP signals appear to be enclosed in lysosomal vesicles. Colocalization analyses likewise indicated higher Mander’s coefficients for PLE-coated NP overlap with LAMP1. (f) Bare liposomes and HA-coated NPs colocalized more strongly with the Syntaxin 6 marker of transcytosis machinery, which was confirmed by their higher Mander’s coefficients with this marker. Data display averages of three technical replicate images on three replicate monolayers from different hCMEC / D3 cell populations, with the exception of dextran colocalization in (d), which includes only one replicate monolayer due to constraints of live cell imaging. * Treatment groups are statistically different (p < 0.05) by Kruskal–Wallis H test. Figure 4. Intravital imaging enables the calculation of NP permeability across the BBB in mice. (a) From sequential z-stack images, the starting signal for a 70 kDa FITC- dextran (FD70) blood vessel marker is used to create a mask separating vessel pixels from brain parenchyma. This mask is applied to both dextran and nanoparticle signal for the first and all subsequent time points, allowing for calculations nanoparticle transport out of the vessels and into the brain. (b) For PLD outer layer nanoparticles with differing cores, liposome-based materials displayed slightly higher BBB permeability than stiffer polymer particles. (c) For liposome core particles, an HA outer layer appeared to confer an advantage to crossing the blood brain barrier compared to other outer surface layers. (d) However, size- matched HA and PSialA polymers did not cross the blood brain barrier faster than the biologically inert dextran. (e) Repeating the monolayer association assay, now with flow of nanoparticle treatments over the cell surface, better captured the high BBB permeability behavior of HA-coated LbL-NPs. Permeability data display mean ± standard error for individual animals, based on 3-15 permeability measurements, depending on length of experiment viability. * Treatment groups are statistically different (p < 0.05) by Kruskal– Wallis H test. Uptake data display mean ± standard deviation for six technical replicate channels in series on one flow chip. Trendlines display simple linear regressions of the data, and dotted lines indicate the 90% confidence interval of the trendline. Figure 5. Cryo-TEM analysis of LbL-NPs. Diameters of nanoparticles in cryo- TEM micrographs were determined by manual measurement using ImageJTM, then compared to sizes and polydispersity index as measured by dynamic light scattering. Scale bars display 100 nm. Figure 6. Nanoparticles do not substantially aggregate when incubated in cell culture media. Nanoparticles were incubated in cell culture media for 8 hours at 37°C, then diluted into deionized water to measure size by DLS. Compared to control samples diluted in 2 mM NaCl or in 10% media (diluted in Milli-QTMwater) immediately before measuring, particles incubated in media displayed small changes in size consistent with protein adsorption but not particle aggregation. Data display mean ± standard deviation of three DLS measurements, and diameters are expressed as intensity average – rather than number average – as a metric that is more sensitive to smaller populations of particle aggregates. Figure 7. Schematic of nanoparticle composed of a chemotherapeutic drug-loaded core, electrostatically functionalized with polymer layers and targeting peptides that improve transport into the brain and accumulation into cancer cells. Figure 8. Process Development for LbL-NPs with electrostatically conjugated targeting peptides. (a) Adjusting adsorption conditions for histidine-containing peptides, here the peptide RAP12, on NPs with HA, PLD, or polyacrylic acid (PAA) outer layers did not change the nanoparticle stability behavior when compared to (b) particles formulated at pH 7.4. (c) Likewise, the change in pH did not substantially affect the retention of peptide on the NP surface, so all further experiments proceeded with pH 7.4 conditions. (d) NPs could be combined with up to 2 equivalents (peptide wt. / liposome lipid bilayer core wt.) of AP2 peptide and remain stable in their measured size, due to (e) remaining below the classical -30 mV cutoff for electro-steric colloid stability. (f) NPs incubated with 2 weight equivalents (High) AP2 retained at least 0.5 weight equivalents of this peptide on their surface. (g) Using a similar poly-L-glutamic acid outer layer (PLE) with a PEG linker and covalently attached AP2 peptides, nanoparticles were stable at the maximum peptide loading. (h) However, due to the constraints of covalently binding one peptide per chain, this yielded only 0.012 mg of peptide per mg of nanoparticle core. (i) When the AP2 was instead covalently bound to click handles on the PLD outer surface of NPs, no more than 0.25 wt. eq. of peptide could be added without destabilizing the system and leading to particle aggregation, compared to at least 2 eq. eq. using the electrostatic conjugation strategy. Data display mean ± standard deviation of three replicate measurements. Figure 9. LbL-NPs with AP2 targeting improve uptake into GBM cells. Compared to LbL-NPs with no peptide functionalization or with an adsorbed peptide scramble, LbL-NPs with HA or PLD outer layers showed greater association with GBM22 patient-derived glioma cells. Data display mean ± standard deviation of three replicate plates. Figure 10. LbL-NPs with AP2 targeting improve transport across the BBB in mice. LbL-NPs electrostatically conjugated with 2 wt. eq. AP2 showed substantial improvements in BBB permeability in mice. Normalization to 70 kDa FITC-dextran (FD70) permeability provides an internal standard by which animals can be reasonably compared. Data display mean ± standard error for individual animals, based on 3-15 permeability measurements, depending on length of experiment viability. Figure 11. LbL-NPs with AP2 targeting improve accumulation in GBM tumors in mice. Mice were intravenously injected with the small molecule gadolinium carrier Gadavist or with LbL-NPs containing lipid-anchored gadolinium. Twenty-four hours later, the brains were removed and the gadolinium content assessed by ICP-MS. LbL-NPs with electrostatically conjugated AP2 showed greater accumulation into the brain – especially into the tumor bearing hemisphere – compared to the non-targeted formulations. Each data point represents one animal. Figure 12. LbL-NPs formulated with the MEK inhibitor trametinib effectively inhibit GBM cell proliferation. (a) Trametinib was loaded into the liposome bilayers, and was retained at greater than 2.4% (wt. / wt.) after all purification and functionalization steps. In (b) parental GBM22 cells and (c) GBM22 GFP / Luc cells, encapsulation did not reduce the efficacy of the trametinib, and LbL functionalization improved the cytotoxic effect at higher doses. Importantly, drug-free Lipo-PLR-HA-AP2 dosed at the highest NP concentration did not reduce cell viability, indicating that this effect is not due to NP toxicity. For drug loading, data display three replicate measurements of a representative particle batch. For viability experiments, data display mean ± standard deviation of three replicate plates. Detailed Description As used herein and unless otherwise indicated, the terms “a” and “an” are taken to mean “one”, “at least one” or “one or more”. Unless otherwise required by context, singular terms used herein shall include pluralities and plural terms shall include the singular. Unless the context clearly requires otherwise, throughout the description and the claims, the words ‘comprise’, ‘comprising’, and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to”. Additionally, the words “herein,” “above” and "below" and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of this application. As used herein, the amino acid residues are abbreviated as follows: alanine (Ala; A), asparagine (Asn; N), aspartic acid (Asp; D), arginine (Arg; R), cysteine (Cys; C), glutamic acid (Glu; E), glutamine (Gln; Q), glycine (Gly; G), histidine (His; H), isoleucine (Ile; I), leucine (Leu; L), lysine (Lys; K), methionine (Met; M), phenylalanine (Phe; F), proline (Pro; P), serine (Ser; S), threonine (Thr; T), tryptophan (Trp; W), tyrosine (Tyr; Y), and valine (Val; V). All embodiments of any aspect of the disclosure can be used in combination, unless the context clearly dictates otherwise. As used herein, "about" will mean plus or minus 5% of the particular value. In one aspect, the disclosure provides particles, comprising (a) a liposome having a negatively charged outer surface; (b) a first layer comprising poly-L-arginine (PLR), wherein the PLR is non- covalently associated with the negatively charged outer surface of the liposome; (c) a second layer, comprising hyaluronate (HA), wherein the HA is non- covalently associated with the first layer; and (d) a blood brain barrier-targeting peptide layer electrostatically coupled to the second layer. As shown in the examples that follow, the electrostatic conjugation of targetingpeptides to nanoparticles of the disclosure allows for substantially higher degree of targetingfunctionalization than previously reported strategies. The targeting capacity of the peptide and the circulation and stability benefits of the polymer layers are shown to significantly improve accumulation in brain tumor following intravenous administration of an exemplary therapeutic (trametinib). The particles of the disclosure thus solve the problem of poor accumulation of therapies from the blood into the brain space – crossing the “blood-brain barrier” (BBB), which is the primary reason that candidate therapeutics fail to progress through, for example, glioblastoma (GBM) treatment efficacy trials. By boosting transport across the BBB, as well as improving selective uptake by the cancer cells rather than healthy brain cells – these targeted particles enable translation of a wide variety of candidate drugs. Liposomes are spherical lipid vesicles approximately 50–500 nm in diameter particle size composed of one or more lipid bilayers, as a result of emulsifying natural or synthetic lipids in an aqueous medium. Liposomes have an aqueous core. Therapeutic drugs can be loaded into the aqueous core of the liposome or into the lipid bilayers, depending on the molecular properties of the therapeutic. Thus, in various embodiments, the liposome has a diameter of between about 50 nm and about 500 nm; or about 50 nm and about 250 nm; or about 50 nm and about 150 nm; or about 50 nm and about 100 nm. Poly-L-arginine hydrochloride (PLR) is a homopolyamino acid having the structure below. The ratio of PLR to liposome lipid bilayer (used interchangeably with “liposome core” herein) in the particles may be any ratio that yields a zeta potential greater than 30 mV as measured by dynamic light scattering (DLS). In one embodiment, the particle has a ratio of about 0.05 to about 1 weight equivalent of PLR to liposome lipid bilayer, yielding a measured increase in nanoparticle diameter between 1-50 nm. In another embodiment, the particle has a ratio of about 0.1 to about 0.8 weight equivalent of PLR to liposome lipid bilayer, yielding a measured increase in particle diameter of about 5 to about 30 nm.

[0002] Poly-L-arginine hydrochloride (PLR) Hyaluronan (hyaluronic acid or hyaluronate; HA) is a linear heteropolysaccharidecomposed of [ 4)- -d-GlcA-(1 3)- -d-GlcNAc(1 ] n disaccharide repeats. The ratio ofHA to liposome lipid bilayer in the particles may be any ratio that yields a zeta potential less than – 30 mV as measured by DLS. In one embodiment, the particle has a ratio of about 0.3 to about 3 weight equivalents of HA to liposome lipid bilayer. In other embodiments, the particle has a ratio of about 0.6 to about 2.4 weight equivalent of HA to liposome lipid bilayer, or about 1.2 weight equivalent of HA to liposome lipid bilayer. Any liposome having a negatively charged outer surface can be used in the particles as suitable for an intended use. In one embodiment, the liposomal lipid bilayer comprises cholesterol; DSPC (1,2-distearoyl-sn-glycero-3-phosphocholine); DSPE (1,2-Distearoyl-sn- glycero-3-phosphoethanolamine); and DSPG (1,2-Distearoyl-sn-glycero-3-phosphoglycerol), in a ratio suitable for number average diameters between 50-100 nm as determined by DLS, and polydispersity index (PDI) less than 0.2. In one non-limiting embodiment, a suitable lipid bilayer formulation comprises about a 31:31:7:31 molar ratio of cholesterol : DSPC : DSPE : DSPG. Any suitable BBB-targeting peptide layer electrostatically coupled to the second layer that yields a stable nanoparticle (zeta potential less than -30 mV) may be used. In various non-limiting embodiments, the targeting peptide is selected from peptides comprising or consisting of the amino acid sequence of SEQ ID NO:1-8. In one embodiment, the targeting peptide comprises or consists of the amino acid sequence of SEQ ID NO:1. In another embodiment, the measured diameter of the particle (i.e., liposome-PLR-polyanion-peptide conjugate) ranges between about 50 nm to about 500 nm, or from about 100 nm to about 150 nm. The amino acid sequences of SEQ ID NO:1-8 are shown in Table 1. Table 1 Each of the peptides of SEQ ID NO:1-8 is net positively charged, and targets the BBB and permit a linked moiety to pass through the BBB. In addition, each of these peptides has anti-tumor activity that make them particularly useful for the methods of the disclosure. The targeting peptides are electrostatically attached to the particles by mixing the positively charged peptides with the polyanionic outer layer of the particles, and allow the attraction of opposite charges to stably stick the two components together. In one embodiment the particle has a ratio of about 0.05 to 5 weight equivalents of the peptide to the liposome lipid bilayer. In another embodiment, the particle has a ratio of about 0.2 to about 2 weight equivalents of peptide to liposome lipid bilayer. A noted above, one or more therapeutic drugs can be loaded into the aqueous core of the liposome or into the lipid bilayers, depending on the molecular properties of the therapeutic. In some embodiment, the therapeutic can be loaded into liposome aqueous core by adding the drug to the dried lipid film before rehydration in water. In other embodiments, the therapeutic drug can be loaded into the liposome lipid bilayer by adding it to the lipid film before liposome rehydration. The particles of the disclosure are particularly designed for administration to the brain, and particularly for treating brain tumors. Thus, in one embodiment, therapeutic comprises one or more chemotherapeutic. Any chemotherapeutic suitable for an intended treatment can be used, including but not limited to one or more therapeutic selected from the group consisting of angiogenesis inhibitors (including but not limited to axitinib, bevacizumab, cabozantinib, everolimus, lenalidomide, lenvatinib mesylate, pazopanib, ramucirumab, regorafenib, sorafenib, sunitinib, thalidomide, vandetanib, and ziv-aflibercept), anthracyclines (including but not limited to daunorubicin, doxorubicin, and epirubicin), immune checkpoint inhibitors (including, but not limited to, pembrolizumab, nivolumab, and cemiplimab as anti-PD-1 antibodies, ipilimumab as an anti-CTLA-4 antibody, and atezolizumab, avelumab, and durvalumab as anti-PD-L1 antibodies), microtubule stabilizers (including by not limited to docetaxel or paclitaxel), and other cancer growth inhibitors including but not limited to tyrosine kinase inhibitors (including but not limited to alectinib, brigatinib, ceritinib, crizotinib, entrectinib, lorlatinib, ALK, I, bosutinib, dasatinib, imatinib, nilotinib, ponatinib, afatinib, dacomitinib, erlotinib, gefitinib, lapatinib, neratinib, osimertinib, vandetanib, gilteritinib, midostaurin, erdafitinib, ruxolitinib, larotrectinib, axitinib, carbozantinib, lenvatinib, pazopanib, regorafenib, sorafenib, sunitinib, dabrafenib, encorafenib, vemurafenib, acalabrutinib, ibrutinib, binimetinib, cobimetinib, trametinib, abemaciclib, palbociclib, ribociclib, or eCF506), proteasome inhibitors (including but not limited to ortezomib, carfizomib, ixazomib, delanzomib, oprozomib, and marizomib), mTOR inhibitors (including but not limited to everolimus, sirolimus, temsirolimus, everolimus, sirolimus, sirolimus protein-bound, and everolimus), PI3K inhibitors (including but not limited to copanlisib, alpelisib, idelalisib, duvelisib and umbralisib), histone deacetylase inhibitors (including but not limited to vorinostat, romidepsin, panobinostat, and belinostat), and Hedgehog pathway blockers (including but not limited to vismodegib, sonidegib, and glasdegib), or pharmaceutically acceptable salts thereof. In one embodiment, the therapeutic comprises trametinib, or a pharmaceutically acceptable salt thereof. As shown in the examples that follow, trametinib was used to exemplify use of the particles of the disclosure. Trametinib is an MEK1 inhibitor that is currently administered clinically for low-grade gliomas. The inventors demonstrated that trametinib can be loaded into the particles of the disclosure, and that encapsulation into such particles does not interfere with the cytostatic effect of trametinib on glioblastoma cells, and had greater cytotoxic effect at higher doses than free trametinib or liposome-encapsulated drug not including the layers that the particles of the present disclosure possess. The weight % drug loaded into the particle is dependent on the therapeutic itself. In one non-limiting embodiment, the particle comprises between about 0.5 weight % and about 3 weight % trametinib per mg of liposome lipid bilayer, or between about 0.5 weight % and about 2.5 weight % trametinib per mg of liposome lipid bilayer, or between about 0.5 weight % and about 2.4 weight % trametinib per mg of liposome lipid bilayer. In another embodiment, the disclosure provides pharmaceutical composition, comprising (a) a plurality (i.e., at least 2, 5, 10.50, 100, 1000, 5000, 10,000, 50,000, 100,000 or more) of the particles of any embodiment herein that includes one or more therapeutic drugs loaded into the aqueous core of the liposome or into the lipid bilayers; and (b) a pharmaceutically acceptable carrier. In one embodiment, the one or more therapeutic comprises trametinib, or a pharmaceutically acceptable salt thereof. As used herein, the term “pharmaceutically acceptable carrier” refers to a pharmaceutically-acceptable material, composition or vehicle for administration of therapeutic described herein. Pharmaceutically acceptable carriers include any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like which are compatible with the activity of the active agent and are physiologically acceptable to the subject. Some examples of materials which can serve as pharmaceutically-acceptable carriers include: (i) sugars, such as lactose, glucose and sucrose; (ii) starches, such as corn starch and potato starch; (iii) cellulose, and its derivatives, such as sodium carboxymethyl cellulose, methylcellulose, ethyl cellulose, microcrystalline cellulose and cellulose acetate; (iv) powdered tragacanth; (v) malt; (vi) gelatin; (vii) lubricating agents, such as magnesium stearate, sodium lauryl sulfate and talc; (viii) excipients, such as cocoa butter and suppository waxes; (ix) oils, such as peanut oil, cottonseed oil, safflower oil, sesame oil, olive oil, corn oil and soybean oil; (x) glycols, such as propylene glycol; (xi) polyols, such as glycerin, sorbitol, mannitol and polyethylene glycol (PEG); (xii) esters, such as ethyl oleate and ethyl laurate; (xiii) agar; (xiv) buffering agents, such as magnesium hydroxide and aluminum hydroxide; (xv) alginic acid; (xvi) pyrogen-free water; (xvii) isotonic saline; (xviii) Ringer's solution; (xix) ethyl alcohol; (xx) pH buffered solutions; (xxi) polyesters, polycarbonates and / or polyanhydrides; (xxii) bulking agents, such as polypeptides and amino acids (xxiii) serum component, such as serum albumin, HDL and LDL; (xxiv) C2-C12 alcohols, such as ethanol; and (xxv) other non-toxic compatible substances employed in pharmaceutical formulations. Wetting agents, coloring agents, release agents, coating agents, sweetening agents, flavoring agents, perfuming agents, preservative and antioxidants can also be present in the formulation. Pharmaceutically acceptable carriers can vary in a formulation described herein, depending on the administration route. The formulations described herein can be delivered via any administration mode known to a skilled practitioner. For example, the formulations described herein can be delivered in a systemic manner, via administration routes such as, but not limited to, oral, and parenteral, including intravenous, intramuscular, intraperitoneal, intradermal, and subcutaneous. In some embodiments, the formulations described herein are in a form that is suitable for injection. When administering parenterally, a formulation described herein can be generally formulated in a unit dosage injectable form (solution, suspension, emulsion). The formulations suitable for injection include sterile aqueous solutions or dispersions. The carrier can be a solvent or dispersing medium containing, for example, water, cell culture medium, buffers (e.g., phosphate buffered saline), polyol (for example, glycerol, propylene glycol, liquid polyethylene glycol, and the like), suitable mixtures thereof. In some embodiments, the pharmaceutical carrier can be a buffered solution (e.g., PBS). Where necessary, the composition may also include a solubilizing agent and a local anesthetic such as lignocaine to ease pain at the site of the injection. In one embodiment, the pharmaceutical composition is formulated for intravenous administration. The formulations can also contain auxiliary substances such as wetting or emulsifying agents, pH buffering agents, gelling or viscosity enhancing additives, preservatives, colors, and the like, depending upon the route of administration and the preparation desired. Standard texts, such as “REMINGTON'S PHARMACEUTICAL SCIENCE”, 17th edition, 1985, incorporated herein by reference, may be consulted to prepare suitable preparations, without undue experimentation. With respect to formulations described herein, however, any vehicle, diluent, or additive used should have to be biocompatible with the active agents described herein. Those skilled in the art will recognize that the components of the formulations should be selected to be biocompatible with respect to the active agent. This will present no problem to those skilled in chemical and pharmaceutical principles, or problems can be readily avoided by reference to standard texts or by simple experiments (not involving undue experimentation). For in vivo administration, the formulations described herein can be administered with a delivery device, e.g., a syringe. Accordingly, an additional aspect described herein provides for delivery devices comprising at least one chamber with an outlet, wherein the at least one chamber comprises a pre-determined amount of any formulation described herein and the outlet provides an exit for the formulation enclosed inside the chamber. In some embodiments, a delivery device described herein can further comprise an actuator to control release of the formulation through the outlet. Such delivery device can be any device to facilitate the administration of any formulation described herein to a subject, e.g., a syringe, a dry powder injector, a nasal spray, a nebulizer, or an implant such as a microchip, e.g., for sustained-release or controlled release of any formulation described herein. In another aspect, the disclosure provides methods for treating a cancer in the brain, comprising administering to a subject having a cancer in the particle or pharmaceutical composition of any embodiment herein that includes one or more therapeutic drugs loaded into the aqueous core of the liposome or into the lipid bilayers, in an amount effective to treat the cancer. In one embodiment, the one or more therapeutic comprises trametinib, or a pharmaceutically acceptable salt thereof. In another embodiment, the cancer in the brain is a glioma or a glioblastoma. In a further embodiment, the administration comprises intravenous administration. As used herein, "treat" or "treating" means accomplishing one or more of the following: (a) reducing the severity of the disorder; (b) limiting or preventing development of symptoms characteristic of the disorder(s) being treated; (c) inhibiting worsening of symptoms characteristic of the disorder(s) being treated; (d) limiting or preventing recurrence of the disorder(s) in patients that have previously had the disorder(s); and (e) limiting or preventing recurrence of symptoms in patients that were previously symptomatic for the disorder(s). When the method comprises treating cancer, "treat" or "treating" means accomplishing one or more of the following: (a) reducing the size or volume of tumors and / or metastases in the subject; (b) limiting any increase in the size or volume of tumors and / or metastases in the subject; (c) increasing survival; (d) reducing the severity of symptoms associated with cancer; (e) limiting or preventing development of symptoms associated with cancer; and (f) inhibiting worsening of symptoms associated with cancer. The methods can be used to treat any suitable cancer, including but not limited to glioblastoma or glioma. The subject may be any subject that has a relevant disorder. In one embodiment, the subject is a mammal, including but not limited to humans, dogs, cats, horses, cattle, etc. In one embodiment, the subject is a human subject. The disclosure also provides methods for making the particles of the disclosure. In one embodiment, the methods comprise electrostatically attaching the targeting peptides to the particles by mixing the positively-charged targeting peptides with the particles having the recited PLR and HA layers, and allowing the attraction of opposite charges of the targeting peptide and the HA layer to electrostatically bind the targeting peptides to the HA layer. In one embodiment, the method further comprises loading a therapeutic into the particle. In one such embodiment, loading the therapeutic into the particle comprises loading the therapeutic into the liposome aqueous core by adding the therapeutic to a dried lipid film before rehydration of the lipid film in water to form the particle. Examples Example 1. Impact of nanoparticle core and surface materials on in vitro uptake, transport, and intracellular trafficking in brain endothelial cells Drug-carrying nanoparticles are a promising strategy to deliver therapeutics into the brain, but their translation requires better characterization of interactions between nanomaterials and endothelial cells of the blood-brain barrier (BBB). Here, we use a library of eighteen layer-by-layer electrostatically assembled nanoparticles (LbL-NPs) to independently assess the impact of nanoparticle core and surface materials on in vitro uptake, transport, and intracellular trafficking in brain endothelial cells. We demonstrate that nanoparticle core stiffness determines the magnitude of transport, while surface chemistry directs intracellular trafficking. Finally, we demonstrate that these factors similarly dictate in vivo BBB transport using intravital imaging through cranial windows in mice. We identify that hyaluronic acid surface chemistry increases transport across the BBB in vivo, and flow conditions are necessary to replicate this finding in vitro. Taken together, these findings highlight the importance of assay geometry, cell biology, and fluid flow in developing nanocarriers for delivery to the brain. Neurological disorders, including but not limited to brain tumors and neurological diseases, are the leading global cause of years of life lost and second leading cause of death, according to data published in 2019. However, development of new treatments for neurologic disorders has been challenging, largely due to poor drug transport across the blood-brain barrier (BBB) – the specialized vascular lining of the central nervous system. At least 95% of newly discovered candidate therapies are excluded from entering the brain – even in glioma tumors and neurological diseases commonly associated with “leaky” BBBs – and there is a critical need to develop drug carriers that can transport therapeutic cargoes across the BBB. Capillaries, the smallest blood vessels in the brain, are lined with specialized endothelial cells surrounded by a basal lamina composed of extra BBB-specific extracellular matrix, and are supported by pericytes and astrocytes (Figure 1a). These endothelial cells comprise the majority of the transport barrier, with tight junctions stitching the cells together to exclude passive and non-specific transport between the cells, including most small molecules; uptake of nutrients, therapeutics, and nanocarriers relies on cell-mediated, active transport to cross the BBB. For this reason, the early stages of brain therapeutic development rely on in vitro BBB models that recapitulate endothelial cell morphology and transport mechanisms to screen candidates for brain delivery, necessitating standardized, high- throughput in vitro models to develop new delivery vehicles. Within the field of in vitro BBB modelling, there are several available types of endothelial cell, each of which presents its own benefits and drawbacks. Primary brain endothelial cells, isolated from patient samples, are the most biologically sophisticated, but lose their brain-specific endothelial phenotypes quickly in cell culture. Endothelial cells derived from induced pluripotent stem cells are biologically diverse, but their ability to recapitulate a brain endothelial phenotype remains controversial. Finally, immortalized cell lines are less genetically diverse, but have stable expression of canonical BBB genes encoding junctional and transport proteins. For this reason, we used the human-derived hCMEC / D3 immortalized microcapillary endothelial cell line in this study. hCMEC / D3 has an endothelial phenotype, characteristic BBB protein expression, and recapitulates the endo- lysosomal and transcytosis systems of primary brain endothelial cells. Beyond the type of endothelial cell used, there are several model geometries – 2 or 3- dimensional – and models with or without media flow available. Each combination of these factors offers its own advantages for inter-lab consistency, ease of handling, and / or recapitulation of the physical environment of the brain capillaries. For example, there are several 3D microfluidic models currently under development for screening of therapeutics or material libraries. However, these remain difficult to standardize across labs or to scale for high-throughput studies. For these reasons, we chose to focus here on three broadly accessible, 2D static model assays to study nanoparticle uptake and transport in hCMEC / D3 BBB endothelial cells. There has been limited study of and little standardization in methodology for assessing BBB transport of nanomaterials. Three commonly used assays include nanoparticle (NP) association via flow cytometry, monolayer association of NPs, and transport of NPs across transwell- grown cell monolayers (Figure 1b). Within the transwell model, there is not consensus for how transwell pore size or monolayer development time affect transport properties and gene expression. By comparing how these geometrical parameters, along with resulting differences in barrier properties and gene expression, dictate hCMEC / D3 cell processing of a variety of nanoparticles, we hypothesize that we can inform best practices for future, high-throughput nanomaterials screens to speed development of new strategies for drug delivery to the brain, as well as identify current top candidates for drug nanocarriers that cross the BBB. To complete this screen, we employ a curated library of layer-by-layer assembled nanoparticles (LbL-NPs) to examine how these BBB models extend to nanomaterial uptake and transport behavior at the BBB. Our LbL-NP library combines three negatively charged NP cores – liposomes, poly(lactic-co-glycolic acid) (PLGA), and polystyrene (PS) – alone or with one of five polyanion outer layers – carboxymethyldextran (CMDex), hyaluronic acid (HA), poly-L-aspartic acid (PLD), poly-L-glutamic acid (PLE), or polysialic acid (PSialA) – to yield 18 formulations with defined core stiffness and surface chemistries (Figure 1c). Screening these NPs using the three previously described in vitro assays allows us to investigate how particle characteristics act as controlling factors for BBB uptake and transport, as well as how surface chemistry in particular dictates NP trafficking within hCMEC / D3 cells. Finally, to match the standard preclinical pipeline for therapeutic development, we use a select set of LbL-NPs to compare our in vitro BBB models to in vivo BBB transport in mice. We apply intravital multiphoton imaging through cranial windows to visualize NP concentrations in blood vessels and brain parenchyma, enabling us to calculate the NP permeability across the BBB. Comparing results across in vitro and in vivo assays highlights promises and pitfalls of each in vitro measure and informs design of nanocarriers for drug delivery to the brain. Results and Discussion Combinatorial LbL-NP Library We next created a library of LbL-NPs to compare in cell uptake and association assays (Figure 2a). The modularity of LbL-NPs allows for combinatorial screening of NP core materials and surface chemistries to assess the independent effects of changing each factor on their biological activity. For our library, anionic (phospholipid) liposomes, acid- terminated PLGA NPs, or carboxylated PS NPs with diameters of 80-100 nm and covalently bound fluorophores were simply mixed with poly-L-arginine (PLR) in HEPES buffer; following removal of non-adsorbed polymer by tangential flow filtration, successful PLR adsorption was confirmed by zeta potential charge conversion to > 40 mV. By the same process, the PLR-coated NPs were then layered with one of five polyanions – carboxymethyldextran (CMDex), hyaluronic acid (HA), poly-L-aspartic acid (PLD), poly-L- glutamic acid (PLE), or polysialic acid (PSialA) – at ratios chosen to give anionic outer surfaces with zeta potential more negative than -30 mV; these polyions cover a range of synthetic polypeptides, synthetic carbohydrates, and naturally occurring carbohydrates. Characterization by dynamic light scattering (DLS) is displayed in Table 2. Cryo- transmission electron microscopy (cryo-TEM) images of select formulations can be found in Figure 5. Because cationic particles undergo non-specific cellular interactions and rapid clearance from circulation in vivo, only the anionic NP cores and LbL-NPs with polyanion outer layers advanced into biological assays. Validation of hCMEC / D3 BBB Models using LbL-NPs We applied our LbL-NP library to the three orthogonal uptake or transport assays using the hCMEC / D3 endothelial cells: flow cytometry and monolayer association using cells grown in standard plasticware, and transport across a transwell monolayer. For flow cytometry, treated cells are rinsed to remove any NPs that have not been taken up or bound to the cell surface, and the cells are dissociated for cell counting and fluorescence analysis. Differing fluorophores and / or brightness between the NP cores precludes direct comparison across the groups. However, within their formulation groups, polystyrene core LbL-NPs (Figure 2b), PLGA-core LbL-NPs (Figure 2c), and liposome core LbL-NPs (Figure 2d) generally displayed increases in median fluorescence intensity (MFI) over the bare NP cores, indicating that LbL functionalization generally increases interactions with the hCMEC / D3 cells; for the purposes of this discussion, these interactions or associations of nanoparticles for cells will be referred to as nanoparticle uptake, and includes nanoparticles internalized or bound to the cell membrane surface. For PS or PLGA core LbL-NPs, the polypeptide outer layers PLD and PLE conferred an uptake advantage, while liposome core LbL-NPs with polysaccharide outer layers CMDex and HA showed greater uptake than other formulations. However, most of the groups showed only up to 2- to 3-fold difference between LbL-NP formulations. Surprisingly, despite previous reports that sialic acid functionalization of NP surfaces improves BBB transport, the PSialA coated LbL-NPs – especially those with PLGA cores – did not undergo improved uptake in this assay. We next examined the LbL-NP library for uptake using monolayer association (Figure 2e) – in monolayer association, treated cells are rinsed to remove any NPs that have not been internalized or bound to cell surfaces, then the cells are homogenized using a combination of dimethyl sulfoxide (DMSO) and heparin sulfate before examining for fluorescent NP content using a plate reader - and for transport through monolayers grown on transwell supports (Figure 2f). Because both assays enable creation of NP fluorescence calibration curves, both allow for direct cross-comparison between LbL-NP formulations with different NP cores. In both cases, uptake or transport of the compliant, liposome-based LbL-NPs was greater than or similar to the stiffer polymeric core NPs with matched outer surface layers. We hypothesize that differences can be primarily attributed to the stiffness and deformability of the core material; the elastic modulus (E) of these liposomal particles is approximately 5-10 kPa, while bulk elastic moduli for semicrystalline PLGA and glassy polystyrene have been reported at approximately 600 MPa and 3.7 GPa, respectively.47,48By comparing surface chemistries with the same core material, we again observed that LbL functionalization increases monolayer association (Figure 2d) for most formulations over the bare core, though the differences were less stark than those observed by flow cytometry. In contrast, we did not observe this relationship for transwell transport (Figure 2e), in which bare PS and PLGA particles transported as well as, or better than, several of the polymer functionalized formulations and there were not statistical enhancements for the liposomal formulations with LbL surfaces. While measuring NP fluorescence in monolayer association and transwell transport assays, we found that it was necessary to fully homogenize and solubilize our samples to obtain robust quantitative data. In the transwell assay, reading fluorescence directly from the lower chamber implied 160-180 % of theoretically maximum NP transport for PLE-coated liposomes. By homogenizing the samples – including samples used for the calibration curves – with dimethyl sulfoxide (DMSO) to dissolve the liposomes along with addition of heparin sulfate to sequester PLR away from the lipid-conjugated, sulfo-Cy5 fluorophore, we obtained the data displayed in Figures 2d and 2e. Because homogenizing the particles led to a brighter but more consistent fluorescence, we concluded that the Cy5 fluorophore attached to the liposome core is partially self-quenching, and liposome breakup allows for higher activity of solubilized lipid-fluorophore conjugates. By contrast, PLGA core LbL-NPs, which do not self-quench, do not demonstrate such discrepancies. The apparent dequenching of the Cy5 in some the liposomal LbL-NPs thus implied that the fluorophore-linked lipids forming the NP core were dissociating from one another as they transported across the cell monolayers. It is well characterized in endothelial cells that nanomaterials are sorted post-internalization into a variety of transport or processing pathways; of these the two most common are transcytosis – shuttling across the cells in vesicles with relatively unchanging, physiological conditions – and endo-lysosomal processing – packaging into vesicles with increasingly hostile enzymatic conditions and acidic pH designed to degrade their contents. Based on these behaviors, and the apparent degradation of some of our liposomal LbL-NP formulations, we hypothesized that while core identity has the largest impact on the total amount of NP taken up and transported, NP surface chemistry dictates sorting into the intracellular pathways by which particles are processed through the cells. To test this hypothesis, we selected three LbL-NP formulations (Table 3) with liposome cores to examine their intracellular trafficking by confocal microscopy in transwell- grown monolayers: bare liposomes which we hypothesize have no degradation during transport, HA-coated NPs as an LbL-NP formulation that we hypothesize undergoes minimal degradation, and PLE-coated NPs as a formulation that we hypothesize undergoes significant degradation. After eight hours of NP treatment, we imaged z-stacks of the NP-treated monolayers to construct orthogonal views, and we observed that Cy5 signal for bare liposomes and HA-coated LbL-NPs presented as small spots scattered throughout the cell bodies (Figure 3). By contrast, the PLE-coated LbL-NPs demonstrated heavy localization of large, bright areas of NP signal to the apical surfaces of the cells. We confirmed that PLE NPs remain colloidally stable in cell culture media over this time period as measured by DLS (Figure 6), and therefore this morphology is not likely an artifact of particles sedimenting to the cell surface, but rather indicates that PLE NPs traffic through different intracellular mechanisms than the bare liposomes or HA-coated LbL-NPs in hCMEC / D3 endothelial cells. To further examine intracellular trafficking, we co-stained identically treated cells with markers for proteins associated with several uptake and transport mechanisms. Neither clathrin nor caveolin-1 showed any substantial colocalization with any of the NP particle formulations. Similarly, none of the formulations colocalized strongly with the early endosome marker EEA1, indicating that the NPs are processed quickly through early endosomes and into other intracellular compartments. Live cells imaged for co-uptake of nanoparticles alongside 70 kDa fluorescent dextran demonstrated the most substantial signal overlap suggesting that a nonspecific uptake mechanism, such as macropinocytosis, is the strongest driver of nanoparticle internalization. We then investigated two major downstream pathways, and determined that bare liposomes and HA-coated LbL-NPs show strongest localization with Syntaxin 6 (Figure 3), a marker for Golgi-associated vesicles that drive transcytosis. It should be noted that the weak and diffuse staining for Syntaxin 6 required imaging settings that produced background speckles across all samples; while this may artificially increase the Mander’s Coefficients for the entire image set, we do not believe that it affects the relative reduction in colocalization of PLE particles with the marker, as compared to the other NP formulations. By contrast, the PLE-coated LbL-NPs accumulate predominantly in vesicles with high expression of LAMP1, a lysosomal marker that denotes vesicles with high degradation capacity. This difference in colocalization supports our hypothesis that the NP surface chemistry is a controlling factor in determining how the materials sort into intracellular trafficking pathways. Based on the increased association between PLE-coated LbL-NPs and the previously reported discrepancies in fluorescence- based transport data (, we can conclude that this formulation is sorted into lysosomes for degradation by the endothelial cells. By contrast, the bare liposomes and HA-coated LbL-NPs that primarily associate with transcytosis machinery would be expected to remain intact as they transport through the cells, as implied by the fluorescence readings in our monolayer transport studies. Comparison of Cell Culture Models to BBB Peremability in Mice Having investigated the role of core stiffness and surface chemistry on uptake and transport of NPs by BBB endothelial cells in vitro, we next sought to understand the extent to which these controlling factors are recapitulated in vivo. To do so, we used a select set of LbL-NPs (Table 3) to examine the BBB permeability via intravital imaging through a cranial window in mice. This method has been used in previous studies to construct static images of NP accumulation in brain, and has recently been adapted to capture a time series of 3- dimensional images for quantitative permeability measurements between the brain capillaries and parenchyma. Briefly, fluorescent dextran and fluorescent NPs are administered intravenously, then a cranial window is generated, and two-photon microscopy is used to generate a time series of multiphoton confocal images across the intact dura. The dextran signal from the first imaging time point is converted to a 3-dimensional mask to differentiate blood vessels from brain parenchyma, and the subsequent images are compared to this mask to determine the permeability of the NPs across the BBB (Figure 4a). As a passive diffusion marker, the consistent and slow leakage of high molecular weight dextran out of the blood vessels was also computed to use as a normalization factor, eliminating effects of any slight Z-shifts over time that could not be accounted for by differential slice selection. After validating that retroorbital NP injection yielded comparable results to the previously published method of tail vein injections, we used this technique to determine the BBB permeability of LbL-NPs in mice. For a constant PLD outer layer, compliant liposome- based NPs had higher permeability than PLGA and PS core LbL-NPs (Figure 4b), although the difference was less stark than in the in vitro assays. Similarly, comparing liposome core LbL-NPs, varying surface chemistry generally had a modest impact on BBB permeability (Figure 4c), and for most of the polyanion outer layers studied here, LbL functionalization did not increase NP transport over bare liposomes, consistent with observations from the transwell transport assay. Unexpectedly, we observed that HA-coated NPs did significantly out-perform all other formulations in vivo, including bare NPs and other carboxylated carbohydrates CMDex and PSialA. HA is a known binding partner for several receptors and other proteins – including CD44 and HA binding proteins (HABPs) – which are expressed by brain endothelial cells, including hCMEC / D336; however, these binding partners have not been implicated in transcytosis or other uptake activity in endothelial cells.55We hypothesized that the HA-coated NPs were undergoing random binding events with endothelial cell surface binding partners as they passed through the capillaries. This phenomenon would slow transit of nanoparticles – known to localize poorly to blood vessel walls – in the blood flow environment and enhance their localization to the BBB surface, allowing for a higher probability of nonspecific uptake by macropinocytosis, as was implied from our in vitro microscopy analysis. To probe this, we generated Cy5-labelled HA and PSialA polymers, size matched to the FD70 diffusion marker, and examined their BBB permeability in vivo (Figure 4d). Neither polymer had higher permeability than the passively diffusing dextran, thus we concluded that the polymer interactions with cell surfaces do not, on their own, drive active uptake and transcytosis. Rather, we posit that a combination of the adsorbed polymer morphology and its presentation on the NP surface with the flow conditions of the capillaries is required to convey a transport benefit. To further probe this behavior, we employed flow chips to construct a lower-throughput but dynamic version of the monolayer association assay reported in Figure 2d, with pump-driven flow of NP treatments parallel to the apical surface of the hCMEC / D3 monolayers grown on collagen- coated plasticware. Treatments were flowed over the cells at 0.79 mL / min – 1 dyne / cm2shear stress to mimic the low end of the highly heterogeneous shear range in the brain vasculature57while avoiding undue stress to statically grown cells – for 4 hours. The resulting cell uptake of nanoparticles (Figure 4e) matched well with measured nanoparticle permeability in flowing capillaries in vivo – including the identification of HA-coated NPs as a top candidate – but over-predicted the permeability for CMDex-, PLD- and PLE-coated nanoparticles compared to the in vivo permeability measurements. This further supports our hypothesis that HA coatings improve NP permeability by changing their flow behavior at the BBB. Conclusions In this work, we have comprehensively characterized the uptake and transport of a combinatorial NP library in four in vitro BBB assays, and compared these results directly with in vivo permeability in live mice. Our data highlight major differences between in vitro metrics of nanomaterial uptake / association versus transport at the endothelial barrier of the BBB. hCMEC / D3, the most commonly used human immortalized cell line for BBB modeling, expresses tight junctions that do not recapitulate BBB exclusion of small molecules, but do provide an appropriate barrier for studying interactions with nano-scale materials. We demonstrated that cell assay behavior and gene expression are consistent across a range of commonly used development times and cell culture substrates, allowing for cross-comparison with assays in the literature. For the three most common in vitro metrics of nanomaterial uptake and transport – flow cytometry, monolayer association, and transwell transport – flow cytometry provides the best correlated data to liposome-based NP uptake studies in vivo. However, monolayer association and transwell transport allow for better cross-comparison across different NP cores in LbL-NP formulations. Across our library of eighteen NPs, we show that the NP core composition consistently has the greatest effect on total uptake, with softer liposome cores undergoing the greatest magnitude of NP uptake or transport. In contrast, surface chemistry is a stronger determinant of intracellular trafficking patterns such as lysosomal versus transcytosis routing, which is highly relevant for drug delivery applications. We show that surface chemistry determines whether a NP is transported across the BBB intact or degraded in lysosomes, a finding that was only captured using transwell transport. The observations on the relative importance of LbL-NP core stiffness and surface chemistries were conserved for permeability across the mouse BBB as measured via intravital imaging, though none of the static in vitro models predicted HA functionalization to have uniquely high permeability in vivo. References 1. Feigin VL, Nichols E, Alam T, et al. Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol.2019;18(5):459-480. doi:10.1016 / S1474- 4422(18)30499-X 2. Parodi A, Rudzi ska M, Deviatkin AA, Soond SM, Baldin A V., Zamyatnin AA.Established and emerging strategies for drug delivery across the blood-brain barrier in brain cancer. Pharmaceutics.2019;11(5). doi:10.3390 / pharmaceutics11050245 3. Haumann R, Videira JC, Kaspers GJL, van Vuurden DG, Hulleman E. Overview of Current Drug Delivery Methods Across the Blood–Brain Barrier for the Treatment of Primary Brain Tumors. CNS Drugs.2020;34(11):1121-1131. doi:10.1007 / s40263- 020-00766-w 4. Sarkaria JN, Hu LS, Parney IF, et al. Is the blood-brain barrier really disrupted in all glioblastomas? A critical assessment of existing clinical data. Neuro Oncol. 2018;20(2):184-191. doi:10.1093 / neuonc / nox175 5. Sweeney MD, Sagare AP, Zlokovic B V. Blood-brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat Rev Neurol. 2018;14(3):133-150. doi:10.1038 / nrneurol.2017.188 6. Abbott NJ, Patabendige AAK, Dolman DEM, Yusof SR, Begley DJ. Structure and function of the blood-brain barrier. Neurobiol Dis.2010;37(1):13-25. doi:10.1016 / j.nbd.2009.07.030 7. Di L, Rong H, Feng B. Demystifying brain penetration in central nervous system drug discovery. J Med Chem.2013;56(1):2-12. doi:10.1021 / jm301297f 8. Urich E, Lazic SE, Molnos J, Wells I, Freskgård PO. Transcriptional profiling of human brain endothelial cells reveals key properties crucial for predictive in vitro blood-brain barrier models. PLoS One.2012;7(5). doi:10.1371 / journal.pone.0038149 9. Hollmann EK, Bailey AK, Potharazu A V., Neely MD, Bowman AB, Lippmann ES. Accelerated differentiation of human induced pluripotent stem cells to blood-brain barrier endothelial cells. Fluids Barriers CNS.2017;14(1):1-13. doi:10.1186 / s12987- 017-0059-0 10. Lu TM, Barcia Durán JG, Houghton S, Rafii S, Redmond D, Lis R. Human Induced Pluripotent Stem Cell-Derived Brain Endothelial Cells: Current Controversies. Front Physiol.2021;12(March). doi:10.3389 / fphys.2021.642812 11. Poller B, Gutmann H, Krähenbühl S, et al. The human brain endothelial cell line hCMEC / D3 as a human blood-brain barrier model for drug transport studies. J Neurochem.2008;107(5):1358-1368. doi:10.1111 / j.1471-4159.2008.05730.x 12. Eigenmann DE, Xue G, Kim KS, Moses A V., Hamburger M, Oufir M. Comparative study of four immortalized human brain capillary endothelial cell lines, hCMEC / D3, hBMEC, TY10, and BB19, and optimization of culture conditions, for an in vitro blood-brain barrier model for drug permeability studies. Fluids Barriers CNS. 2013;10(1). doi:10.1186 / 2045-8118-10-33 13. Weksler BB, Subileau EA, Perrière N, et al. Blood-brain barrier-specific properties of a human adult brain endothelial cell line. FASEB Journal.2005;19(13):1872-1874. doi:10.1096 / fj.04-3458fje 14. Ohtsuki S, Ikeda C, Uchida Y, et al. Quantitative targeted absolute proteomic analysis of transporters, receptors and junction proteins for validation of human cerebral microvascular endothelial cell line hCMEC / D3 as a human blood-brain barrier model. Mol Pharm.2013;10(1):289-296. doi:10.1021 / mp3004308 15. Dauchy S, Miller F, Couraud PO, et al. Expression and transcriptional regulation of ABC transporters and cytochromes P450 in hCMEC / D3 human cerebral microvascular endothelial cells. Biochem Pharmacol.2009;77(5):897-909. doi:10.1016 / j.bcp.2008.11.001 16. Rahman NA, Rasil AN ain HM, Meyding-Lamade U, et al. Immortalized endothelial cell lines for in vitro blood-brain barrier models: A systematic review. Brain Res. 2016;1642:532-545. doi:10.1016 / j.brainres.2016.04.024 17. Qi D, Lin H, Hu B, Wei Y. A review on in vitro model of the blood-brain barrier (BBB) based on hCMEC / D3 cells. Journal of Controlled Release.2023;358:78-97. doi:10.1016 / j.jconrel.2023.04.020 18. Toth AE, Nielsen SSE, Tomaka W, Abbott NJ, Nielsen MS. The endo-lysosomal system of bEnd.3 and hCMEC / D3 brain endothelial cells. Fluids Barriers CNS. 2019;16(1):1-13. doi:10.1186 / s12987-019-0134-9 19. Hajal C, Le Roi B, Kamm RD, Maoz BM. Biology and Models of the Blood-Brain Barrier. Annu Rev Biomed Eng.2021;23:359-384. doi:10.1146 / annurev-bioeng- 082120-042814 20. Brown TD, Nowak M, Bayles A V., et al. A microfluidic model of human brain (HuB) for assessment of blood brain barrier. Bioeng Transl Med. 2019;4(2):1-13.doi:10.1002 / btm2.10126 21. Campisi M, Shin Y, Osaki T, Hajal C, Chiono V, Kamm RD.3D self-organized microvascular model of the human blood-brain barrier with endothelial cells, pericytes and astrocytes. Biomaterials.2018;180:117-129. doi:10.1016 / j.biomaterials.2018.07.014 22. Straehla JP, Hajal C, Safford HC, et al. A predictive microfluidic model of human glioblastoma to assess trafficking of blood-brain barrier-penetrant nanoparticles. Proceedings of the National Academy of Sciences.2022;119(23):e2118697119. doi:10.1073 / pnas.2118697119 / - / DCSupplemental.Published 23. Schmid D, Buntz A, Hanh Phan TN, et al. Transcytosis of payloads that are non- covalently complexed to bispecific antibodies across the hCMEC / D3 blood-brain barrier model. Biol Chem.2018;399(7):711-721. doi:10.1515 / hsz-2017-0311 24. Gonzalez-Carter D, Goode AE, Fiammengo R, Dunlop IE, Dexter DT, Porter AE. Inhibition of Leptin–ObR Interaction Does not Prevent Leptin Translocation Across a Human Blood–Brain Barrier Model. J Neuroendocrinol.2016;28(6). doi:10.1111 / jne.12392 25. Papadia K, Markoutsa E, Antimisiaris SG. How do the physicochemical properties of nanoliposomes affect their interactions with the hCMEC / D3 cellular model of the BBB? Int J Pharm.2016;509(1-2):431-438. doi:10.1016 / j.ijpharm.2016.06.019 26. Wang C, Wu B, Wu Y, Song X, Zhang S, Liu Z. Camouflaging Nanoparticles with Brain Metastatic Tumor Cell Membranes: A New Strategy to Traverse Blood–Brain Barrier for Imaging and Therapy of Brain Tumors. Adv Funct Mater.2020;30(14):1- 11. doi:10.1002 / adfm.201909369 27. Brown TD, Habibi N, Wu D, Lahann J, Mitragotri S. Effect of Nanoparticle Composition, Size, Shape, and Stiffness on Penetration across the Blood-Brain Barrier. ACS Biomater Sci Eng.2020;6(9):4916-4928. doi:10.1021 / acsbiomaterials.0c00743 28. Markoutsa E, Pampalakis G, Niarakis A, et al. Uptake and permeability studies of BBB-targeting immunoliposomes using the hCMEC / D3 cell line. European Journal of Pharmaceutics and Biopharmaceutics.2011;77(2):265-274. doi:10.1016 / j.ejpb.2010.11.015 29. Offeddu GS, Haase K, Gillrie MR, et al. An on-chip model of protein paracellular and transcellular permeability in the microcirculation. Biomaterials.2019;212(May):115- 125. doi:10.1016 / j.biomaterials.2019.05.022 30. Srinivasan B, Kolli AR, Esch MB, Abaci HE, Shuler ML, Hickman JJ. TEER Measurement Techniques for In Vitro Barrier Model Systems. J Lab Autom. 2015;20(2):107-126. doi:10.1177 / 2211068214561025 31. Qi D, Lin H, Hu B, Wei Y. A review on in vitro model of the blood-brain barrier (BBB) based on hCMEC / D3 cells. Journal of Controlled Release.2023;358:78-97. doi:10.1016 / j.jconrel.2023.04.020 32. Daniels BP, Cruz-Orengo L, Pasieka TJ, et al. Immortalized human cerebral microvascular endothelial cells maintain the properties of primary cells in an in vitro model of immune migration across the blood brain barrier. J Neurosci Methods. 2013;212(1):173-179. doi:10.1016 / j.jneumeth.2012.10.001 33. Helms HC, Abbott NJ, Burek M, et al. In vitro models of the blood-brain barrier: An overview of commonly used brain endothelial cell culture models and guidelines for their use. Journal of Cerebral Blood Flow and Metabolism.2015;36(5):862-890. doi:10.1177 / 0271678X16630991 34. Marsh D. Structural and thermodynamic determinants of chain-melting transition temperatures for phospholipid and glycolipids membranes. Biochim Biophys Acta Biomembr.2010;1798(1):40-51. doi:10.1016 / j.bbamem.2009.10.010 35. Muller AM, Hermanns MI, Skrzynski C, Nesslinger M, Muller KM, Kirkpatrick CJ. Expression of the Endothelial Markers PECAM-1 , vWf , and CD34 in Vivo and in Vitro. Exp Mol Pathol.2002;72:221-229. doi:10.1006 / exmp.2002.2424 36. Kalari KR, Thompson KJ, Nair AA, et al. BBBomics-human blood brain barrier transcriptomics hub. Front Neurosci.2016;10(MAR):1-7. doi:10.3389 / fnins.2016.00071 37. Zakharova M, Tibbe MP, Koch LS, et al. Transwell-Integrated 2 μ m Thick Transparent Polydimethylsiloxane Membranes with Controlled Pore Sizes and Distribution to Model the Blood-Brain Barrier. Adv Mater Technol.2021;2100138(6). doi:10.1002 / admt.202100138 38. Correa S, Choi KY, Dreaden EC, et al. Highly Scalable, Closed-Loop Synthesis of Drug-Loaded, Layer-by-Layer Nanoparticles. Adv Funct Mater.2016;26(7):991- 1003. doi:10.1002 / adfm.201504385 39. Morton SW, Poon Z, Hammond PT. The architecture and biological performance of drug-loaded LbL nanoparticles. Biomaterials.2013;34(21):5328-5335. doi:10.1016 / j.biomaterials.2013.03.059 40. Poon Z, Lee JB, Morton SW, Hammond PT. Controlling in vivo stability and biodistribution in electrostatically assembled nanoparticles for systemic delivery. Nano Lett.2011;11(5):2096-2103. doi:10.1021 / nl200636r 41. Fröhlich E. The role of surface charge in cellular uptake and cytotoxicity of medical nanoparticles. Int J Nanomedicine.2012;7:5577-5591. doi:10.2147 / IJN.S36111 42. Correa S, Boehnke N, Barberio AE, et al. Tuning Nanoparticle Interactions with Ovarian Cancer through Layer-by-Layer Modification of Surface Chemistry. ACS Nano.2020;14(2):2224-2237. doi:10.1021 / acsnano.9b09213 43. Wang M, Zhang Y, Feng J, et al. Preparation, characterization, and in vitro and in vivo investigation of chitosan-coated poly (d,l-lactide-co-glycolide) nanoparticles for intestinal delivery of exendin-4. Int J Nanomedicine.2013;8:1141-1154. doi:10.2147 / IJN.S41457 44. Wielgat P, Niemirowicz-Laskowska K, Wilczewska AZ, Car H. Sialic acid— modified nanoparticles—new approaches in the glioma management—perspective review. Int J Mol Sci.2021;22(14). doi:10.3390 / ijms22147494 45. Barberio AE, Smith SG, Correa S, et al. Cancer Cell Coating Nanoparticles for Optimal Tumor-Specific Cytokine Delivery. ACS Nano.2020;14(9):11238-11253. doi:10.1021 / acsnano.0c03109 46. Kong SM, Costa DF, Jagielska A, Van Vliet KJ, Hammond PT. Stiffness of targeted layer-by-layer nanoparticles impacts elimination half-life, tumor accumulation, and tumor penetration.2021;118:2104826118. doi:10.1073 / pnas.2104826118 / - / DCSupplemental 47. Choi SH, Park TG. Synthesis and characterization of elastic PLGA / PCL / PLGA tri- block copolymers. J Biomater Sci Polym Ed.2002;13(10):1163-1173. doi:10.1163 / 156856202320813864 48. Oral I, Guzel H, Ahmetli G. Measuring the Young’s modulus of polystyrene-based composites by tensile test and pulse-echo method. Polymer Bulletin. 2011;67(9):1893-1906. doi:10.1007 / s00289-011-0530-z 49. Ribovski L, de Jong E, Mergel O, et al. Low nanogel stiffness favors nanogel transcytosis across an in vitro blood–brain barrier. Nanomedicine.2021;34:102377. doi:10.1016 / j.nano.2021.102377 50. Nowak M, Brown TD, Graham A, Helgeson ME, Mitragotri S. Size, shape, and flexibility influence nanoparticle transport across brain endothelium under flow. Bioeng Transl Med.2019;(September):1-11. doi:10.1002 / btm2.10153 51. Predescu SA, Predescu DN, Malik AB. Molecular determinants of endothelial transcytosis and their role in endothelial permeability. Am J Physiol Lung Cell Mol Physiol.2007;293(4). doi:10.1152 / ajplung.00436.2006 52. Li L, Wan T, Wan M, Liu B, Cheng R, Zhang R. The effect of the size of fluorescent dextran on its endocytic pathway. Cell Biol Int.2015;39(5):531-539. doi:10.1002 / cbin.10424 53. Eskelinen EL. Roles of LAMP-1 and LAMP-2 in lysosome biogenesis and autophagy. Mol Aspects Med.2006;27(5-6):495-502. doi:10.1016 / j.mam.2006.08.005 54. Lam FC, Morton SW, Wyckoff J, et al. Enhanced efficacy of combined temozolomide and bromodomain inhibitor therapy for gliomas using targeted nanoparticles. Nat Commun.2018;9(1). doi:10.1038 / s41467-018-04315-4 55. DeOre BJ, Partyka PP, Fan F, Galie PA. CD44 mediates shear stress mechanotransduction in an in vitro blood-brain barrier model through small GTPases RhoA and Rac1. FASEB Journal.2022;36(5):1-16. doi:10.1096 / fj.202100822RR 56. Fish MB, Banka AL, Braunreuther M, et al. Deformable Microparticles for Shuttling Nanoparticles to the Vascular Wall. Vol 7.; 2021. 57. Mairey E, Genovesio A, Donnadieu E, et al. Cerebral microcirculation shear stress levels determine Neisseria meningitidis attachment sites along the blood-brain barrier. Journal of Experimental Medicine.2006;203(8):1939-1950. doi:10.1084 / jem.20060482 58. Correa S, Boehnke N, Deiss-Yehiely E, Hammond PT. Solution Conditions Tune and Optimize Loading of Therapeutic Polyelectrolytes into Layer-by-Layer Functionalized Liposomes. ACS Nano.2019;13(5):5623-5634. doi:10.1021 / acsnano.9b00792 59. Costes S V., Daelemans D, Cho EH, Dobbin Z, Pavlakis G, Lockett S. Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophys J. 2004;86(6):3993-4003. doi:10.1529 / biophysj.103.038422 60. Dupont WD, Plummer WD. Power and Sample Size Calculations for Studies Involving Linear Regression. Control Clin Trials.1998;19(6):589-601. doi:10.1016 / S0197-2456(98)00037-3 61. Leary SL, American Veterinary Medical Association. AVMA Guidelines for the Euthanasia of Animals : 2020 Edition.62. Haase K, Gillrie MR, Hajal C, Kamm RD. Pericytes Contribute to Dysfunction in a Human 3D Model of Placental Microvasculature through VEGF-Ang-Tie2 Signaling. Advanced Science.2019;6(23). doi:10.1002 / advs.201900878 Materials and Methods Materials 1,2-distearoyl-sn-glycero-3-phospho-(1'-rac-glycerol) sodium salt (DSPG), 1,2- distearoyl-sn-glycero-3-phosphoethanolamine (DSPE), 1,2-distearoyl-sn-glycero-3- phosphocholine (DSPC) and cholesterol were purchased from Avanti. Sulfo-cyanine dyes with NHS ester or amine handles were purchased from Lumiprobe. Chloroform was purchased from TCI. Methanol, Poly(D,L-lactide-glycolide) (PLGA Resomer RG 502H, 7-17 kDa), Rhodamine B – PLGA (50:50 monomer ratio, 10-30 kDa), the hCMEC / D3 cell line, Accumax dissociation reagent, Type 1 rat tail collagen, ascorbic acid, -mercaptoethanol, lucifer yellow, FITC-labelled dextrans, dimethyl sulfoxide (DMSO), heparin sulfate, bovine serum albumin (BSA), saponin, and sulfo-N-hydroxysuccinimide were purchased from Millipore Sigma. Cy5-functionalized PLGA (10-15 kDa) was purchased from PolySciTech. Whatman NucleoporeTMpolycarbonate hydrophilic membranes (400, 200, 100 and 50 nm sizes) were purchased from GE.50 / 15 mL Falcon tubes, DNA LoBindTMtubes, 10% neutral buffered formalin, Polystyrene semi-micro cuvettes, 0.22 μm polyethersulfone syringe filters, SpectraporTMdialysis membranes, microscope slides, coverslips, slide sealer nail polish, Masterflex® size 14 platinum-cured silicone tubing, and polypropylene Masterflex® fittings were purchased from VWR. D02-E300-05-ND, 02-E100-05-N, and C02-E100-05-N tangential flow filtration filters, as well as 15 mL reservoirs for peristaltic pump circuits, were purchased from Repligen. Poly-L-arginine hydrochloride (38.5 kDa), poly-L-aspartic acid (14 kDa), and poly-L-glutamic acid (15 kDa) were purchased from Alamanda Polymers. Hyaluronic acid (40 kDa) was purchased from LifeCore Biomedical. Carboxymethyldextran and polysialic acid were purchased from Carbosynth. DTS 1070 folded capillary zeta cells were purchased from Malvern. Tissue culture plasticware (T75, T25, clear and white 96 well plates), 24-well 1 μm pore transwell plates, individual transwell inserts, Penicillin / Streptomycin and fetal bovine serum (FBS) were purchased from Corning. EBM-2 cell culture media was purchased from Lonza. Phosphate buffered saline (PBS), LabTek 8- chamber coverslips, Hoechst 33342, fluorescently labelled wheat germ agglutinin, fluorescently labelled phalloidin, AlexaFluorTM488-labelled anti-VE Cadherin (16B1), AlexaFluorTM488-labelled anti-ZO-1 (ZO1-1A12), 5 M bioreagent grade NaCl solution, 1 M bioreagent-grade HEPES, chemically defined lipid concentrate, basic fibroblast growth factor, PCR tube strips with caps, Pierce endotoxin removal columns, and yellow-green or red fluorescent polystyrene microspheres (100 nm FluospheresTM) were purchased from Thermo Fisher. RNeasyTMPlus Mini Kits for RNA extraction and QuantiTectTMReverse Transcriptase Kits were purchased from Qiagen. Roche Light CyclerTM-DNA Master SYBRTMGreen I mastermix and Corning Axygen 384-well PCR microplates were purchased through the MIT BioMicro Center / KI Genomics Core. IDTE buffer, nuclease free water, and PrimeTimeTMPCR Primers were purchased from Integrated DNA Technologies (IDT). The Voltohmmeter and accompanying electrodes were purchased from World Precision Instruments.1-Ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride (EDC) was purchased from Chem-Impex. Falcon cell strainer tubes were purchased from Fisher Scientific. Syntaxin 6 (C34B2) Rabbit mAb 2869, Caveolin-1 (D46G3) XP® Rabbit mAb 3267, Clathrin Heavy Chain (D3C6) XP® Rabbit mAb 4796, EEA1 (C45B10) Rabbit mAb 3288, and Anti-rabbit IgG (H+L), F(ab')2 Fragment (Alexa Fluor® 488 Conjugate) #4412 were purchased from Cell Signaling Technologies.6 mm biopsy punched were purchased from McKesson. VECTASHIELDTMAntifade Mounting Medium (H-1000) was purchased from Vector Laboratories. MatTek 35 mm Dishes (No.1.5 Uncoated Coverslip, 7 mm Glass Diameter) were purchased from Fisher Scientific. μ-Slide VI 0.4 chips were purchased from Ibidi®. Nanoparticle Synthesis and Characterization Liposome Synthesis Cholesterol and lipid stocks were made in chloroform and methanol, then combined in round bottom flask at a mol ratio of 31 Chol : 31 DSPC : 7 DSPE : 31 DSPG. The lipids were dried into a thin film using a BUCHI rotary evaporation system under heat (55°C, water bath) until completely dry (<30 mBar). A Branson sonicator bath was heated to 65°C, at which point the RBF with the lipid film was partially submerged in the bath and a volume of Milli-Q deionized water was added to re-suspend the lipid film to a 1 mg lipid / mL solution. The liposome solution was sonicated three times for [1 minute on, 1 minute off], then transferred to an Avestin LiposoFastTMLF-50 liposome extruder. The extruder was connected to a Cole-Parmer PolystatTMHeated Recirculator Bath to maintain a temperature of 65°C. The liposomes were extruded through nucleopore membranes until a 50-100 nm liposome was obtained. Typically, this was achieved by passing through stacked 400 and 200 nm membranes, 100 nm, and 50 nm membranes. The liposomes were analyzed by dynamic light scattering (DLS) to verify sizes less than 100 nm and PDI values less than 0.2. Fluorescently labeled liposomes were prepared via NHS-coupling of Sulfo-cyanine dyes with NHS ester handles to DSPE head group amines; reactions in 15 mM sodium carbonate buffer (pH 9), stirred at room temperature overnight. Unconjugated dye was purified away from the labelled liposomes by tangential flow filtration (TFF) before liposome characterization by DLS. PLGA Nanoparticle Synthesis 10 mg PLGA polymers was dissolved at a concentration of 5 mg / ml in acetone, with a mass ratio of 9:1 ResomerTM502H to dyed (RhodB or Cy5) polymer.12 ml of Milli-QTMwater was added to a scintillation vial and stirred gently on a stir plate while heating to 35°C. The PLGA solution was drawn up in a syringe with a 26-gauge needle then slowly added to the water under constant stirring. An additional 8 mL of 35°C deionized water was added, and the vial was left to stir, uncovered under ventilation, for at least two hours. Particles were characterized by DLS and concentrated to 1 mg / mL by TFF. Layer-by-Layer Polymer Functionalization Nanoparticles – liposomes, PLGA NPs, or commercially purchased polystyrene FluospheresTM– were layered with polyelectrolyte coatings by adding nanoparticle suspension (0.5 mg / mL when layering HA, 1 mg / mL otherwise, all in unbuffered water) to an equal volume of polyelectrolyte solution under sonication at room temperature58. This process is highly scalable and, depending on the formulation at hand, ranged from 2 mL to 40 mL in total volume. The mixture was sonicated for approximately three seconds then vortexed at maximum speed for approximately ten seconds. The weight equivalents (wt. eq.) of polyelectrolyte used with respect to liposome core were 0.4 for poly-L-arginine (PLR), 1.6 for carboxymethyldextran (CMDex), 1.2 for hyaluronic acid (HA), 0.8 for poly-L-aspartic acid (PLD), 3 for poly-L-glutamic acid (PLE), and 1.4 for polysialic acid (PSialA). Polyelectrolyte solutions were prepared in 50 mM HEPES (pH 7.4) and 40 mM NaCl, with the exception of HA, which was prepared in 2 mM HEPES. The freshly layered particles were allowed to incubate at room temperature for 5 to 30 minutes, then purified using the tangential flow filtration. Tangential Flow Filtration To purify any un-adsorbed polyelectrolytes at each step of layering, nanoparticle samples were connected to a Spectrum Labs KrosFloTMII filtration system using MasterflexTM, Teflon coated tubing. D02-E100 / E300-05-N (batch volume 12 mL) or C02- E100-05-N (batch volume < 12 mL) filters with 300 kDa (HA and CMDex purifications) or 100 kDa (all other purifications) nominal molecular weight cutoffs were used to purify free dyes or polymers away from the nanoparticle samples. For PLR purification, the filter was pre-treated using a mock sample of free PLR, so saturate adsorption sites on the anionic membrane walls. Samples were filtered at 13 mL / min for small batches or 80 mL / min for large batches, with a Milli-QTMwater inlet line to replace 1:1 the volume of waste permeate. After at least 5 sample volume equivalents of waste collection, the sample was concentrated, removed from the filter by reversing the pump direction, and brought back to 1 mg / mL nanoparticle concentration (0.5 mg / mL for HA) by backflushing a defined volume of Milli- QTMwater through the filter and into the sample. Nanoparticle Characterization Nanoparticle hydrodynamic size, polydispersity, and zeta potential were measured using DLS (Malvern ZS90 Particle Analyzer, = 633 nm, = 90°). Without additional sonication, 50 μg of each nanoparticle was diluted into 2 mM NaCl to give a total volume of 800 μL, then transferred to polystyrene cuvettes or DTS1070 folded capillary cuvettes for DLS. Refractive indices and absorption coefficients for measurements were: liposome – 1.450, 0.001; PLGA – 1.560, 0.000; PS – 1.590, 0.010. Dispersant used refractive index and viscosity values for water: 1.330, 0.8872 cP (at 25°C). Nanoparticle micrographs were acquired using Transmission Electron Microscopy (TEM) on a JEOL 2100F microscope (200 kV) under cryogenic conditions. Nanoparticle sizes from TEM images were counted manually using ImageJTM. Cell Culture Maintenance hCMEC / D3 cells – immortalized endothelial cells derived from an adult female patient11– were cultured according to manufacturer specifications in EBM-2 media supplemented with 5% FBS, 1 ng / mL bFGF, 1.4 μM hydrocortisone, 1% pen / strep, 1% chemically defined lipid concentrate, 10 mM HEPES, and 5 μg / mL ascorbic acid. Cells were cultured in flasks coated with 12 μg / cm2rat tail collagen and split twice per week at a ratio between 1:3 and 1:8, using Accumax dissociation reagent, to maintain cells below approximately 90% confluency. Between maintenance and experiments, cells were incubated at 37°C and in a 100% humidity and 5% CO2 atmosphere. Cell lines were authenticated using STR profiling, and cells were tested monthly for mycoplasma, with all results coming back negative for contamination. Cell Monolayers for Gene Expression and Uptake Experiments All plasticware for cell studies was pre-coated with rat tail collagen. hCMEC / D3 cells were suspended in media and seeded at a density of 2 × 105cells / cm2transwell supports or 96-well tissue culture plates. The cells were incubated for 7 days, with media replacement every 2-3 days. For transwells, the TEER was monitored to confirm proper barrier formation before use in any experiments. TEER is expressed as the resistance of transwell filters with cells minus transwell filters without cells. Transport Experiments General Transwell Transport Protocol Cell monolayers in transwells were transferred to 24-well plates containing 1 mL / well media. Nanoparticle or fluorescent marker treatments were added to the apical chambers at 20 μg / cm2in media; negative control wells received fresh media. Extra treatments for each experiment were used to make fluorescence calibration curves. At 4, 8, and 24 hours after treatment addition, the monolayers were transferred to new basal plates (creating quasi-sink conditions for the basal media compartment). Media from the basal plates was sampled for fluorescence measurements on a Tecan InfiniteTMM200 Pro plate reader, with 100 μL / well sample in a black 96-well plate, and applied to the calibration curves to calculate percent of nanomaterial transported. 4°C Protocol To assess active transport, nanoparticle treatments in media and basal plates with media were both equilibrated to 4°C in the refrigerator. Pre-experiment TEER values were measured with cells still at 37°C, then monolayers were transferred to the chilled treatment and basal media. The monolayers were then incubated in the 4°C refrigerator for the remainder of the experiment. DMSO Breakup and Reread To homogenize samples, 100 μL (nanoparticles in cell culture media) per well was supplemented with 100 μL / well DMSO and 50 μL / well of heparin sulfate (1 mg / mL in PBS). The plate was placed on an orbital shaker at 240 RPM for 10 minutes before repeating the fluorescence measurements. Gene Expression RNA extraction and cDNA preparation Cells were rinsed with PBS and pelleted. Total RNA was extracted according to the instructions provided with the Qiagen RNeasyTMkit (available online as the RNEasy Mini Handbook). Briefly, lysis buffer was prepared with 1% -mercaptoethanol to protect RNA from degradation. Lysate samples of 1-3 million cells in 350 L lysis buffer were mixed with 350 L ethanol and spun through the filter columns. Columns were washed once with 700 L RW1 buffer then twice with 500 L RPE buffer. Total RNA was eluted from the columns using 30 L nuclease-free water. NanodropTM(Thermo Fisher) spectrophotometry was used to assess RNA concentration and quality, and all 260 / 280 values were greater than 1.8. cDNA was synthesized according to manufacturer’s instructions using 1 g of template RNA. cDNA was stored at -20°C or placed on ice for immediate use. Real time quantitative PCR For qPCR reactions, cDNA was diluted 1:50 with nuclease-free water, and primers were diluted to 20x (10 M) in IDTE buffer according to the manufacturer’s specifications. RT-qPCR was set up in a 384-well plate with 8 L diluted cDNA, 10 L 2x SYBRTMGreen master mix, 0.8 L nuclease-free water, and 1.2 L 20x primer. Each condition was performed in technical triplicate. No primer (IDTE buffer instead of primer) and no cDNA (water instead of cDNA) controls were also used to ensure there was not contamination. RT- qPCR was run on a LightCyclerTM480 (Roche) and Ct values obtained using the second derivative. The Ct method was used to compare expression between cell lines, normalizing to beta actin. The primers have the following assay ID numbers and sequences: in vitro Confocal Imaging Fixed sample treatment and preparation For fixed cell imaging of structural proteins and nanoparticle localization within intracellular compartments, cells were cultured on collagen-coated chambered slides or transwells for seven days to allow complete monolayer development. The cells were incubated with Cy3-labelled NPs for 8 hours, then washed 3x with PBS and fixed with 4% formaldehyde in PBS for 20 minutes at room temperature, protected from light. This was followed by three washes with PBS at 5 min / wash, and samples were stored at 4°C overnight in fresh PBS. Samples were permeabilized and blocked with 0.1% saponin and 1% BSA in PBS for 30 minutes at room temperature. For samples with unlabeled primary antibodies, cells were stained for 30 minutes with primary solutions containing 0.1 % saponin, 1% BSA, and 2.5 μg / mL primary antibodies. The samples were rinsed three times with PBS over the course of fifteen minutes, then stained with solutions containing 2.5 μg / mL AlexaFluorTM488 labelled antibodies, 1.5 μg / mL Hoechst 33342, and either 10 μg / mL wheat germ agglutinin or 0.165 μM phalloidin labelled with AlexaFluorTM633. The samples were washed again with PBS three times over 15 minutes, then plastic chambers were removed from chamber slides, or transwell filters were punched out of their plastic casing using a biopsy punch and placed cell side up on a microscope slide. The samples were supplemented with VectashieldTM(H1000), secured with a coverslip, and sealed using nail polish. The samples were stored at 4°C and protected from light until imaging. Live sample treatment and preparation For live cell imaging of dextran macropinocytosis, were cultured on collagen-coated (12 μg / cm2) MatTekTMdish glass coverslips for seven days. The cells were incubated with 20 μg / cm2each Cy3-labelled NPs and 70 kDa FITC-Dextran for 8 hours, then washed 3x with fresh media. After adding fresh (HEPES-containing) media containing 10 μg / mL, the dishes were sealed using parafilm, and the live cells imaged immediately. Image capture and processing All cells were imaged with a confocal laser-scanning microscope (FV-1200, Olympus), equipped with 405, 473, 559, and 635 nm lasers. Images were acquired with 100x objectives, and all images were acquired under the same illumination settings. Images were processed using ImageJTMsoftware. For published images, bare liposome signal was linearly increased by 10%, and Syntaxin 6 background signal was reduced by raising the lower pixel limit by 10%. No other adjustments to image signals were made. With the exception of orthogonal views, images display Z projections (maximum signal) bounded by the center of the cell layer and the top of all four signals at the apical surface. Mander’s coefficients for nanoparticle signal overlap with intracellular markers was calculated on unadjusted images using ImarisTM3D software. Image stacks were trimmed to remove and discard slices outside of the cell layer, then thresholded using the built-in Costes Automatic Thresholding plugin. Flow Cytometry To assess nanoparticle association at single-cell resolution, particle-treated cells in 96- well plates were washed 3x with warm PBS, then dissociated from the well bottoms using 30 μL AccumaxTMdissociation reagent.220 μL warm media was added to quench the dissociation, and pipetted vigorously to break up clumps before transferring to new 96-well plates without collagen coating. The samples were analyzed using a BD LSRTMII Flow Cytometer with a high throughput sampler (BD Biosciences). Samples dosed with Cy5 liposomes were analyzed on the APC channel (ex.640, filters 670 / 30). Samples dosed with rhodamine B PLGA were analyzed on the PE channel (ex.561 filters 582 / 42. Samples dosed with yellow green (polystyrene) fluospheres were analyzed on the GFP channel (ex.488, filters 515 / 20). Data were analyzed using FlowJoTM(version 10), and cells were gated for single cells based on untreated cell samples using the side scatter and forward scatter plots. Monolayer Association To assess nanoparticle association at the population level, nanoparticle treated cells in 96-well plates were washed three times with ice cold PBS, then treated with 100 μL / well of 0.5 mg / mL heparin sulfate in 50% DMSO and 50% PBS. Standard curves were constructed by adding defined amounts of nanoparticles to the same solution. Samples were placed on an orbital shaker for 15 minutes at 180 RPM, then transferred to black 96-well plates to measure particle fluorescence. Ibidi® Flow Chip Association To assess nanoparticle association with cells under fluid flow conditions, hCMEC / D3 cells were seeded in 60 μL media at a density of 2 × 105cells / cm2in collagen-coated, 6- channel Ibidi® μ-Slide VI 0.4 chips, and each port supplemented with 60 μL media to total 180 μL of media per channel. Media was static during the development phase, and changed every 2-3 days for 7-8 days. Developed cells were treated with nanoparticles at 7.2 μg / mL, 10 mL total (to give 20 μg / cm2total) continuously flowing in series through all six channels on one chip. Flow was driven through a closed system loop by a peristaltic pump through sterilized Masterflex ® platinum-cured silicone tubing – size 14 – at 0.79 mL / min (1 dyne / cm2shear stress) for 4 hours, with a sterile air filter attachment preventing buildup of pressure differential along flow path. Treatments were removed, and the channels were rinsed 3 times with 180 μL PBS. Each channel was treated with 100 μL / well of 2 mg / mL heparin sulfate in 75% DMSO and 25% PBS for 30 minutes, cycling 60 μL within each channel every ten minutes. Standard curves were constructed by adding defined amounts of nanoparticles to the same homogenization solution. The samples and standards were transferred to black 384-well plates to measure particle fluorescence using the plate reader. Animal Studies Animal Care and Use All animal experiments were approved by the Massachusetts Institute of Technology Committee on Animal Care (CAC, protocol number 0919-056-22) and were conducted under the oversight of the Division of Comparative Medicine (DCM). C57BL / 6 mice were purchased from Taconic, and were housed in cages of no more than five animals withcontrolled temperature (25°C), 12 h light dark cycles and free access to food and water. Bothfemale and male mice were used in this study, and the mice were 8–20 weeks old at the time of experiment. The free-to-use PS Power Calculator (Vanderbilt) was used to determine the minimal sample size for which statistical power was greater than or equal to 0.8, leading to groups of 2 female + 2 male mice, with 1-3 image sets per animal. Intravital Imaging Mice underwent head hair removal up to 24 hours before the imaging procedure occurred. All surgical tools were one-time-use sterile products or sterilized in an autoclave prior to surgery. One at a time, animals were anesthetized via a 100 μL intraperitoneal injection of 100 mg / kg ketamine with 10 mg / kg xylazine paralytic carried in sterile PBS. Once fully anesthetized (unreactive to toe pinch stimulus), mice were injected with 70 kDa FITC-labelled dextran (2 mg / mL in PBS, sterile filtered) and red-fluorescent nanoparticles (1 mg / mL in 5% dextrose), both as 150 μL retro-orbital injections. To create the cranial window, the skull was exposed, and a high-speed hand drill (Dremel) was used to thin the skull until the dura mater was exposed over the right frontal cortex. The mice were then secured to a microscope coverslip for imaging. Multiphoton imaging was performed on an Olympus FV-1000MPE multiphoton microscope (Olympus) using a 25×, numerical aperture 1.05 objective. Excitation was achieved by using a femtosecond pulse laser at 840 nm, and emitted fluorescence was collected by photomultiplier tubes with emission filters of 425 / 30 nm for Collagen 1, 525 / 45 nm for fluorescein isothiocyanate-labeled dextran, 607 / 45 nm for red polystyrene nanoparticles, and 672 / 30 nm for Cy5TM(PLGA and liposome) nanoparticles. Collagen 1 was excited by second harmonic generation and emitted as polarized light at half the excitation wavelength. The collagen 1 signal was used to identify the dura, such that the vessels imaged were within the cortex.22Images were acquired every 2 minutes for 12 minutes for analysis, and up to three image sessions per mouse were run. Mice were maintained under anesthesia by an additional, 100 μL intraperitoneal dose of 50 mg / kg ketamine in sterile PBS, 35-40 minutes after the first injection of anesthetic. Animals were euthanized by cervical dislocation directly from anesthetic sleep, complying with American Veterinary Medical Association (AVMA) guidelines.61Acquired images from intravital imaging were then thresholded and segmented by using the Fiji distribution of ImageJTMand the Trainable Weka Segmentation plugin. Vessels below the dura and arteries were examined to ensure that these represent BBB capillaries in the mouse brain. The microvasculature filled with dextran (dextran channel) was used to generate a three-dimensional mask of the BBB mouse vessels. This mask was employed to calculate vessel surface area, as well as dextran and NP signal both inside and outside the blood vessels. After masking, analysis of NP or dextran transport was performed as previously described.22,29,62Fluorescent polymer modifications To create polymers that could be tracked in fluorescent microscopy, HA (60 kDa nominal molecular weight) and PSialA were dyed for intravital imaging using standard 1- Ethyl-3-[3-dimethylaminopropyl]carbodiimide (EDC) coupling with amine-functionalized SulfoCy5. Polymers, sulfo-N-hydroxysuccinimide (sulfo-NHS), sulfoCy5-amine, and EDC were added sequentially in a 1 monomer : 0.5 : 0.255 : 2.55 molar ratio for HA, or 1 monomer : 0.5 : 0.085 : 1.5 molar ratio for PSialA. Reactions were allowed to run overnight, then the polymers were purified away from free dye and reactants using Amicon Ultra-4TM3 kDa spin filters, followed by dialysis in Milli-QTMwater using 3.5 kDa cutoff tubing. Dialysis continued until no dye could be detected in the dialysate. Statistics Detailed statistical information is provided for each figure in the associated caption, and all tests used nonparametric comparisons based on sample sizes. Unless noted otherwise, for single comparisons, the Mann-Whitney test was used. For multiple comparison testing, the Kruskal-Wallis test was used. Mann-Whitney and Kruskal-Wallis statistics were calculated using standard arithmetic formulas in Microsoft Excel 2021, while arithmetic means, standard deviation, standard error of the mean, and 90% confidence intervals were calculated and plotted by GraphPadTMPrism Version 10.0.1. Example 2. Peptide-Targeted Layer-by-Layer Nanoparticle for Glioblastoma Treatment In Example 1, we demonstrated that nanoparticle core stiffness determines the magnitude of transport, while surface chemistry directs intracellular trafficking. We also showed that hyaluronic acid surface chemistry layered on top of liposomal NP cores give the best transport across the BBB in vivo. We further aimed to add biological targeting molecules onto the particles. We chose to work with targeting peptides, due to their combination of specificity (based on high fidelity recognition of amino acid sequences) with molecular sizes and chemical properties that are amenable to NP conjugation. While most research groups covalently attach targeting peptides to NP surfaces, we employed “electrostatic conjugation” to give a superior degree of functionalization. In this procedure, rather than chemically reacting the targeting peptides to the nanoparticle surface, we simply mix together net positively charged peptides with negatively charged nanoparticles and allow the attraction of opposite charges to stably stick the two components together. We started with a set of ten candidate peptides, which we narrowed down to two based on (1) their amenability to the electrostatic conjugation process and (2) the brain- specific marker targeted. From this group, we focused down to two peptides – RAP12 and Angiopep-2 (AP2) – that both target the nanoparticles to the same LRP1 receptor expressed on both BBB and glioblastoma (GBM) cells. Based on a higher stable degree of functionalization, we chose to move forward with bio-testing using the AP2 formulation. We developed a layer-by-layer electrostatically assembled nanoparticle (LbL-NP) composed of a nanoparticle core loaded with a small molecule therapeutic against GBM brain tumors, layers of functional polymers, and targeting peptides (Figure 7). For this embodiment, the nanoparticle core was a liposome approximately 100 nm in diameter, containing the MEK1 inhibitor trametinib as an exemplary therapeutic. The polycation layer is poly-L-arginine (PLR), and the outer layer polyanions are poly-L-aspartate (PLD) and hyaluronate (HA). The HA outer layer was additionally shown in Example 1 to improve LbL-NP transport into the brain even before the addition of targeting peptides. To add targeting peptides, LbL-NPs were modified by adding equal volumes of NP solution (1 mg / mL for PLD outer layers or 0.5 mg / mL for HA outer layers, both in water) to an equal volume of peptide solution (in 10 mM HEPES buffer at pH 7.4 + 0.6 mg / mL TCEP, unless otherwise stated) under sonication. The mixture was sonicated for roughly three seconds then vortexed for roughly ten seconds. For weight equivalent (wt. eq – mass of peptide ratio to mass of liposome core lipid) optimization, test batches were constructed using 50 L samples of the NP solution and varying concentrations. Eppendorf brand Protein LoBindTMtubes were for all experiments, to prevent nonspecific adsorption of peptides and NPs to the plastic. For larger batches, tangential flow filtration was used to purify peptide-modified LbL NPs and concentrate them to an appropriate concentration for experiments. All particles were characterized for size and zeta potential using dynamic light scattering (DLS) To measure peptide retention after purification, the ABD-F assay for thiol detection was employed to quantify the cysteine residues appended to Angiopep-2 and RAP12. NP samples were diluted 1:1 with Tris-Borate-EDTA buffer containing 2 mM TCEP (pH 8). Peptide-only calibration standards were prepared directly in the buffer. For a representative assay, 100 μL of sample solution was mixed with 100 μL of borate buffer. To this, 200 μL of ABD-F reagent in TBE buffer was added and vortexed to mix. The reactions were incubated for five minutes at 50°C using a water bath, then cooled rapidly on ice for three minutes and quenched with 120 μL of 100 mM HCl. Eppendorf brand protein LoBind tubes were used for the entirety of the assay.100 μL / well of the reaction was dispensed into a flat bottom, black 96-well plate and fluorescence was measured at 389 / 513 nm using a Tecan M1000 microplate reader. Samples of peptide-free nanoparticles and known concentrations of free peptides were used as standards to calculate the retained peptide concentration of each formulation. We initially asked whether the formulation conditions of adding the electrostatically conjugated peptides affected their retention or the targeted LbL-NP stability after purification. Compared to the standardized HEPES process, using a 10 mM MES buffer (pH 5.5) for RAP12 layering did not appreciably change the stability of peptide-conjugated NPs or significantly improve the efficiency of the process, despite the peptide sequence used containing a histidine residue that ionizes at pH 6 (Figures 8a-8c). Of eight peptides examined for their physicochemical behavior – Angiopep-2 (LRP1 target), B6 (TfR1), G23 (GM1), pGAG (NRP-1), RAP12 (LRP1), RVG (NAchR), Substance P (NKRs), and THR (TfR1I) – we chose to move forward with Angiopep-2 (AP2), due to its ability to achieve high functionalization onto stable NPs (Figures 8d-8f) combined with the dual BBB- and glioma-targeting advantage of binding the LRP1 receptors. AP2 targets the LRP1 receptor, which is over-expressed on both the blood brain barrier and on tumor cells in at least 80% of GBM patients. It is a 2.3 kDa peptide with a net charge of +2, allowing us to achieve a very high degree of functionalization on the polyanion outer layers without interfering with the overall negative surface charge. For this work the AP2 peptide has the amino acid sequence TFFYGGSRGKRNNFKTEEYC (SEQ ID NO:9), where the C-terminal cysteine (“C”) has been added to allow for peptide quantification using an assay that detects the sulfide side group of this amino acid. For clinical use, the C-terminal cysteine residue is not required. To compare the current standard of NP functionalization, LbL-NPs were constructed using variations of the outer layers employed in Example 1, pre-modified to contain click chemistry handles. These outer layers were PLE modified with a PEG chain and terminal azide, or PLD with pendant propargyl groups on the amino acid side chain. PLE-PEG-N3polymer was modified with DBCO-functionalized AP2 before layering and TFF purification. LbL-NPs with propargyl PLD were modified by mixing 50 μL (1 mg / mL) with 25 μL azide functionalized AP2 ((K*)TFFYGGSRGKRNNFKTEEY (SEQ ID NO:10), in which K* denotes modification of the N terminus with lysine–azide), 87.5 μL sodium ascorbate (1 mg / mL), and 87.5 μL CuSO4 / THPTA solution (0.016 mg / mL CuSO4, 0.0672 mg / mL tris- hydroxypropyltriazolylmethylamine). The reactions were carried out at room temperature, protected from light over 12-16 hours. Subsequently, tangential flow filtration was used to remove excess reagents and concentrate the peptide-functionalized LbL-NPs to desired concentration for experiments. We demonstrated that a poly-L-glutamic acid (PLE, chemically similar to PLD) outer layer with one PEG linker and one covalently bound peptide per chain also produced stable NPs up to the highest available functionalization (Figure 8g). However, the constraints of only one peptide per polymer chain yielded substantially lower degrees of peptide functionalization (Figure 8h). By instead using a version of PLD with a fraction of pendant groups functionalized for covalent click conjugation, we found that we could only add up to 0.25 weight equivalents of click functionalized peptide before inducing nanoparticle stabilization (Figure 8i), as compared with the 2 weight equivalents employed forelectrostatic conjugation.To begin assessing the biological function of our LbL-NPs with electrostatically adsorbed AP2, we used patient-derived glioma cells to demonstrate in vitro that nanoparticles decorated with the peptide undergo greater association – the sum of uptake and adsorption to the cell surface – than LbL-NPs with no peptide or decorated with an inactive scramble of the AP2 sequence. (Figure 9). LbL-NPs with or without AP2, or with a scrambled non-targeting AP2 peptide, were mixed with cell culture media and added onto GBM22 glioblastoma cells at 20 μg / cm2. Four, eight, or twenty-four hours later, the nanoparticle treated cells in 96-well plates were washed three times with ice cold PBS, then treated with 100 μL / well of 0.5 mg / mL heparin sulfate in 50% DMSO and 50% PBS. Standard curves were constructed by adding defined amounts of nanoparticles to the same solution. Samples were placed on an orbital shaker for 15 minutes at 180 RPM, then transferred to black 96-well plates to measure particle fluorescence. This experiment confirmed that the peptides maintain their targeting activity through the adsorption process and can boost glioma tumor accumulation of the LbL- NPs. Because AP2 targets the LRP1 receptor that is over-expressed on both GBM cells and the BBB, we also assessed the transport of functionalized NPs across the BBB in mice using intracranial intravital imaging. In example 1, we show that un-functionalized LbL-NPs with HA outer layers had greater permeability across the BBB than those with PLD outer layers. In both cases – and by using the same intravital imaging protocol as previously described – electrostatically conjugating AP2 to the LbL-NP surface significantly increased the permeability of the whole construct across the BBB and into the mouse brain (Figure 10). Importantly, this was – to our knowledge – the first time that this electrostatic conjugation strategy has been shown to work in the substantially more complex in vivo environment. Building on this result, we tracked the actual accumulation of the nanoparticles into GBM tumor bearing mouse brains. Mice with intracranially implanted GBM22 GFP / Luciferase tumors were injected retro-orbitally with 5 mg / kg of gadolinium-tagged LbL- NPs (0.9 mg / mL in 5% dextrose) or a dose-matched small molecule contrast agent containing gadolinium, one week post tumor induction. At 24 hours post NP administration, the mice were sacrificed and the brains removed. The brains were separated into the healthy and tumor-bearing hemispheres, the organ weights were recorded, then each was mixed 1:1 with the same weight of 70% HNO3 solution and digested using a Milestone UltraWAVETMorgan digester with maximum temperature 200°C and pressure 60 bar. The samples were diluted to 4% HNO3 using Milli-Q water, and an Agilent 7900 ICP-MS was used to measure the gadolinium contents. Gadolinium standards, treatment samples, and the organ weights were used to calculate percentage of injected dose per gram of brain tissue. Once again, the LbL- NPs with electrostatically conjugated AP2 accumulated in the brain – especially the tumor hemisphere - to a greater degree than a free small molecule or LbL-NP without targeting peptides (Figure 11). As a proof of concept for this targeted LbL-NP technology, we performed tumor treatment trials using the exemplary chemotherapeutic trametinib, a MEK1 inhibitor that is currently administered clinically for low-grade gliomas but not for GBM. We demonstrated that trametinib can be loaded into liposomes by adding the drug to the dried lipid film before rehydration in water, and that the NPs retain 2.4 wt.% (mg trametinib / mg liposome) through TFF purification and the complete layering process to formulate TramLipo-PLR-HA-AP2 (Figure 12a). To assess the efficacy of this drug delivery system, we seeded GBM22 cells into 96-well plates at 5000 cells / well and allowed them to attach overnight. Nanoparticles or free trametinib (solubilized in trace volumes of DMSO) were diluted using cell culture media to give trametinib concentrations ranging from 1 nM to 10 μM. Cells were incubated with 200 μL / well of NP or free drug solution for 72 hours, then the treatments were removed. CellTiterBlueTM(10 μL / well) was added to 100 μL / well cell media, and incubated for one hour.100 μL / well of the solution was then transferred to black well plates and read for fluorescence at 560 / 590 nm using a Tecan M1000 microplate reader. By comparing the trametinib-treated cells to untreated cells, a vehicle control, or a 0% viability positive control (40 μM MG-132), we showed in a parental GBM22 line (Figure 12b) and in a GBM22 GFP / Luciferase expressing line (Figure 12c) that encapsulation into NPs does not interfere with the cytostatic effect of trametinib on GBM cells. Further, both LbL-NP formulations (with and without AP2) had greater cytotoxic effect at higher doses than free drug or liposome-encapsulated drug.

Claims

We claim 1. A particle, comprising: (a) a liposome having a negatively charged outer surface; (b) a first layer comprising poly-L-arginine (PLR), wherein the PLR is non- covalently associated with the negatively charged outer surface of the liposome; (c) a second layer, comprising hyaluronate (HA), wherein the HA is non- covalently associated with the first layer; and (d) a blood brain barrier-targeting peptide layer electrostatically coupled to the second layer.

2. The particle of claim 1, wherein the particle has a ratio of about 0.05 to about 1 weight equivalent of PLR to liposome lipid bilayer, or a ratio of about 0.1 to about 0.8 weight equivalent of PLR to liposome lipid bilayer.

3. The particle of claim 1 or 2, wherein the particle has a ratio of about 0.3 to about 3 weight equivalents of HA to liposome lipid bilayer, or a ratio of about 0.6 to about 2.4 weight equivalent of PLR to liposome lipid bilayer, or a ratio of about 1.2 weight equivalent of HA to liposome lipid bilayer.

4. The particle of any one of claims 1-3, wherein the liposomal lipid bilayer comprises cholesterol; DSPC (1,2-distearoyl-sn-glycero-3-phosphocholine); DSPE (1,2-Distearoyl-sn- glycero-3-phosphoethanolamine); and DSPG (1,2-Distearoyl-sn-glycero-3-phosphoglycerol).

5. The particle of claim 4, wherein the liposomal lipid bilayer comprises about a 31:31:7:31 molar ratio of cholesterol : DSPC : DSPE : DSPG.

6. The particle of any one of claims 1-5, wherein the targeting peptide comprises or consists of the amino acid sequence selected from the group consisting of SEQ ID NO:1-8.

7. The particle of any one of claims 1-5, wherein the targeting peptide comprises or consists of the amino acid sequence of SEQ ID NO:1.

8. The particle of any one of claims 1-7, wherein the particle has a ratio of about 0.05 to about 5 weight equivalents of the peptide to the liposome lipid bilayer, or a ratio of about 0.2 to about 2 weight equivalents of peptide to liposome lipid bilayer.

9. The particle of any one of claims 1-8, further comprising a therapeutic encapsulated within an aqueous core of the liposome or the liposome lipid bilayer.

10. The particle of claim 9, wherein the therapeutic is a chemotherapeutic.

11. The particle of claim 9 or 10, wherein the therapeutic comprises one or more therapeutic selected from the group consisting of angiogenesis inhibitors (including but not limited to axitinib, bevacizumab, cabozantinib, everolimus, lenalidomide, lenvatinib mesylate, pazopanib, ramucirumab, regorafenib, sorafenib, sunitinib, thalidomide, vandetanib, and ziv-aflibercept), anthracyclines (including but not limited to daunorubicin, doxorubicin, and epirubicin), immune checkpoint inhibitors (including, but not limited to, pembrolizumab, nivolumab, and cemiplimab as anti-PD-1 antibodies, ipilimumab as an anti- CTLA-4 antibody, and atezolizumab, avelumab, and durvalumab as anti-PD-L1 antibodies), microtubule stabilizers (including by not limited to docetaxel or paclitaxel), and other cancer growth inhibitors including but not limited to tyrosine kinase inhibitors (including but not limited to alectinib, brigatinib, ceritinib, crizotinib, entrectinib, lorlatinib, ALK, I, bosutinib, dasatinib, imatinib, nilotinib, ponatinib, afatinib, dacomitinib, erlotinib, gefitinib, lapatinib, neratinib, osimertinib, vandetanib, gilteritinib, midostaurin, erdafitinib, ruxolitinib, larotrectinib, axitinib, carbozantinib, lenvatinib, pazopanib, regorafenib, sorafenib, sunitinib, dabrafenib, encorafenib, vemurafenib, acalabrutinib, ibrutinib, binimetinib, cobimetinib, trametinib, abemaciclib, palbociclib, ribociclib, or eCF506), proteasome inhibitors (including but not limited to ortezomib, carfizomib, ixazomib, delanzomib, oprozomib, and marizomib), mTOR inhibitors (including but not limited to everolimus, sirolimus, temsirolimus, everolimus, sirolimus, sirolimus protein-bound, and everolimus), PI3K inhibitors (including but not limited to copanlisib, alpelisib, idelalisib, duvelisib and umbralisib), histone deacetylase inhibitors (including but not limited to vorinostat, romidepsin, panobinostat, and belinostat), and Hedgehog pathway blockers (including but not limited to vismodegib, sonidegib, and glasdegib), or pharmaceutically acceptable salts thereof.

12. The particle of claim 9 or 10, wherein the therapeutic comprises trametinib, or a pharmaceutically acceptable salt thereof.

13. The particle of claim 12, wherein the particle comprises between about 0.5 weight % and about 3 weight % trametinib per mg of liposome lipid bilayer, or between about 0.5 weight % and about 2.5 weight % trametinib per mg of liposome lipid bilayer, or between about 0.5 weight % and about 2.4 weight % trametinib per mg of liposome lipid bilayer.

14. The particle of any one of claims 1-13, wherein the particle has a diameter range between about 50 nm to about 500 nm.

15. A pharmaceutical composition, comprising (a) a plurality of the particles of any one of claims 9-14; and (b) a pharmaceutically acceptable carrier.

16. The pharmaceutical composition of claim 15, wherein the therapeutic comprises trametinib, or a pharmaceutically acceptable salt thereof.

17. The pharmaceutical composition of claim 15 or 16, wherein the pharmaceutical composition is formulated for intravenous administration.

18. A method for treating a cancer in the brain, comprising administering to a subject having a cancer in the brain the particle or pharmaceutical composition of any one of claims 9-17 in an amount effective to treat the cancer.

19. The method of claim 18, wherein the particle comprise trametinib, or a pharmaceutically acceptable salt thereof.

20. The method of claims 18 or 19, wherein the cancer in the brain is a glioma or a glioblastoma.

21. The method of any one of claims 18-20, wherein the particle or pharmaceutical composition is administered intravenously.The method of claim one of claims 18-21, wherein the subject is a human.

23. A method for making the particle of any one of claims 1-14, comprising electrostatically attaching the targeting peptides to the particles by mixing the positively- charged targeting peptides with the particles having the PLR and HA layers, and allowing attraction of opposite charges of the targeting peptide and the HA layer to electrostatically bind the targeting peptides to the HA layer.

24. The method of claim 23, further comprising loading a therapeutic into the particle.

25. The method of 24, wherein loading the therapeutic into the particle comprises loading the therapeutic into the liposome aqueous core by adding the therapeutic to a dried lipid film before rehydration of the lipid film in water to form the particle, and / loading the therapeutic into the liposome lipid bilayer by adding it to the lipid film before liposome rehydration.

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