A modular approach toward producing nanotherapeutics targeting the innate immune system

Abstract

Immunotherapies controlling the adaptive immune system are firmly established, but regulating the innate immune system remains much less explored. The intrinsic interactions between nanoparticles and phagocytic myeloid cells make these materials especially suited for engaging the innate immune system. However, developing nanotherapeutics is an elaborate process. Here, we demonstrate a modular approach that facilitates efficiently incorporating a broad variety of drugs in a nanobiologic platform. Using a microfluidic formulation strategy, we produced apolipoprotein A1-based nanobiologics with favorable innate immune system-engaging properties as evaluated by in vivo screening. Subsequently, rapamycin and three small-molecule inhibitors were derivatized with lipophilic promoieties, ensuring their seamless incorporation and efficient retention in nanobiologics. A short regimen of intravenously administered rapamycin-loaded nanobiologics (mTORi-NBs) significantly prolonged allograft survival in a heart transplantation mouse model. Last, we studied mTORi-NB biodistribution in nonhuman primates by PET/MR imaging and evaluated its safety, paving the way for clinical translation.

Fig. 1. Investigating the nanobiologics’ stability, biodistribution, and immune cell engagement.

(A) Composition and morphology of the nanobiologics, formulated by microfluidic mixing. (B) Size and stability of the nanobiologics in PBS at 4°C, as measured by DLS. The mean of the number average size distribution is reported. While the 20-, 35-, and 65-nm formulations remained stable, the 120-nm variant shrunk over time and was therefore excluded from subsequent experiments; n = 3 for each nanobiologic size. (C) Representative cryo-TEM images of the 20-, 35-, and 65-nm-sized nanobiologics. Scale bar, 100 nm. (D to F) C57BL/6 mice were intravenously injected with ⁸⁹Zr-labeled nanobiologics. (D) Representative maximum intensity projections of PET/CT scans performed 24 hours after injection. (E) Nanobiologics’ blood pharmacokinetics were fitted with a biexponential decay function; n = 5 per formulation. (F) Nanobiologic uptake in the femur’s bone marrow divided by nanobiologic uptake in the liver, measured at 24 hours after injection. (G) C57BL/6 mice were injected with DiOC₁₈(3)-labeled nanobiologics, and DiOC₁₈(3) uptake was measured 24 hours after injection in various bone marrow cell populations by flow cytometry. Gating strategy and average mean fluorescence intensity (MFI) values are shown; n = 4 per formulation. MyP, myeloid progenitors; LSK, Lin⁻ Sca-1⁺ and c-Kit⁺. Data in (B), (E), and (F) are presented as means ± SD. *P < 0.05.

Fig. 2. Assessing the nanobiologics’ ability to deliver drugs to the bone marrow.

(A) Molecular structure of the fluorescent model drug BODIPY FL carboxylic acid as well as aliphatic and cholesterol functionalized derivatives. (B) Size of nanobiologics loaded with BODIPY or its derivatives as measured by DLS. The mean of the number average size distribution is displayed; n = 3. (C) Recovery of BODIPY and its derivatives as measured by high-performance liquid chromatography (HPLC), defined as the amount of (pro)drug in the nanobiologics divided by the amount used for their formulation; n = 2. (D) Release rate of the BODIPY derivatives from the nanobiologics when dialyzed against FBS at 37°C (10-kDa MWCO), as measured by HPLC. Data points are fitted with a biexponential decay function; n = 2. (E to G) Nanobiologics were formulated containing increasing amounts of either BODIPY-aliphatic or BODIPY-cholesterol. C57BL/6 mice were injected with identical doses of nanobiologics, leading to the administration of varying amounts of BODIPY model prodrugs; e.g., nanobiologics loaded with 5× more fluorophore were injected at a 5× higher fluorophore dose. Twenty-four hours after injection, MFI of Ly6C^hi monocytes was measured by flow cytometry. (E) Schematic overview of the experimental design. (F) Representative histograms of BODIPY signal in bone marrow Ly6C^hi monocytes from mice injected with increasing doses of BODIPY-cholesterol, but the same amount of nanobiologic. (G) MFI of the bone marrow’s Ly6C^hi monocytes after administering nanobiologics loaded with various amounts of BODIPY-aliphatic or BODIPY-cholesterol; n = 4. Lines are to guide the eye. Data in (B) to (D) and (G) are represented as means ± SD. i.v., intravenous.

Fig. 3. Establishing a library of nanotherapeutics.

(A) All drugs were functionalized with either an aliphatic chain or cholesterol using a hydrolyzable ester linkage, except for rapamycin, of which only the aliphatic derivative was synthesized. (B) Murine bone marrow cells were incubated with (pro)drugs and stimulated with lipopolysaccharide (LPS; 100 ng/ml) for 24 hours. Subsequently, tumor necrosis factor–α (TNFα) production was measured by enzyme-linked immunosorbent assay; n = 3 to 4. (C) Size of the nanobiologics as measured by DLS, showing that the type of (pro)drug incorporated has no notable effect on nanobiologic size. The mean of the number average size distribution is displayed; n = 3. (D) Recoveries of the various (pro)drugs in the nanobiologics as measured by HPLC, defined as the amount of (pro)drug in the nanobiologics divided by the amount used for nanobiologic formulation; n = 2. Data in (B) to (D) are represented as means ± SD. *P < 0.05, **P < 0.01.

Fig. 4. Using mTORi-nanobiologics to prevent organ rejection in a mouse heart allograft model.

(A to C) Nanobiologics were formulated using 1×, 3×, and 5× a reference amount of rapamycin-aliphatic (equaling prodrug/triglyceride wt % of 6.50, 19.5, and 32.5, respectively), schematically shown in (A). (B) Amount of rapamycin-aliphatic recovered and (C) size of the nanobiologics when formulated using the various amounts of rapamycin-aliphatic; n = 3 for each composition. The formulation containing 3× our reference amount of rapamycin-aliphatic (containing ~20 wt % prodrug compared to triglycerides) was chosen as lead candidate and highlighted with a gray bar. This formulation was termed mTORi-NB. (D to G) C57BL/6 mice were treated with three intravenous injections of either mTORi-NBs at 1.0 or 5.0 mg/kg, a corresponding dose of unloaded nanobiologics, or PBS. Bone marrow cells were harvested on day 6 and stimulated with LPS, schematically shown in (D). (E) TNFα and (F) IL-6 production upon in vitro LPS stimulation; n = 4 to 6. (G) Alanine aminotransferase (ALT) blood levels in U/liter; n = 10 to 12. (H to J) C57BL/6 mice received an allogenic heart transplant. (H) Representative maximum intensity projection of a PET/CT scan and (I) organ-specific uptake at 24 hours after ⁸⁹Zr-labeled mTORi-NB injection. (J) Allograft survival in mice treated with mTORi-NBs, the unloaded 35-nm nanobiologics, or PBS, directly before as well as 2 and 5 days after transplantation. Data are represented as means ± SD. P values were calculated using Mann-Whitney U tests. For survival analysis, a log-rank test was used. *P < 0.05, **P < 0.01, ****P < 0.0001.

Fig. 5. Biodistribution and safety of mTORi-nanobiologics in nonhuman primates.

Two nonhuman primates weighing 5.99 and 10.13 kg were injected with ⁸⁹Zr-labeled mTORi-NB. (A) Representative 3D-rendered images acquired in the first hour after injection using dynamic PET/MR. (B) Quantification of ⁸⁹Zr-labeled mTORi-NB PET signal in liver, spleen, kidneys, and bone marrow. (C) Representative whole-body PET/MR images, 2 and 48 hours after injection of ⁸⁹Zr-labeled mTORi-NBs. (D) PET-based quantification of ⁸⁹Zr-labeled mTORi-NB uptake in various organs at 48 hours after injection. (E) Blood pharmacokinetics measured by ex vivo gamma counting of blood samples, as well as the associated weighted blood half-life obtained by fitting the data with a biexponential decay function. (F) Aspartate aminotransferase (AST), creatinine, and blood urea nitrogen (BUN) levels before (Pre) and 48 hours after (Post) injection. White areas represent normal ranges for male cynomolgus monkeys (35). For all assays, pre- and post-values are comparable. SUV, standardized uptake value.