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Pharmacokinetic modeling of solid and hollow gold-coated superparamagnetic iron oxide nanoparticles for brain-targeted therapeutics: prediction and experiment

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Abstract

Magneto-plasmonic nanoparticles (MPNPs), such as solid gold (Au) or hollow gold (HG) coated superparamagnetic iron oxide (SPIO) nanoparticles (NPs), have attracted increasing attention for brain-targeted therapeutics. This is due to their supreme magnetic targeting capability, light-to-heat conversion efficiency, and biocompatibility. Though promising, their therapeutic efficiency is difficult to predict because of the complex absorption, distribution, metabolism, and excretion process and the intrinsic and extrinsic properties of the blood–brain barrier (BBB). This paper presents a modern physiologically based pharmacokinetic (PBPK) model to predict pharmacokinetic (PK) behaviors of brain-targeting MPNPs and investigate their morphology and surface function-dependent BBB crossing efficiency. This model quantifies intrinsic and extrinsic properties of PK parameters, including phagocytic cellular uptake rate and brain permeability. This model successfully predicts the biodistribution of functionalized Au-SPIO (18.42 ± 0.23 nm) and HG-SPIO (73.65 ± 1.46 nm) MPNPs in 8-week-old adult mice in a 16-h window after intraperitoneal (IP) injection. These predictions agree well with the experimental data with a low absolute average fold error (1.5381 for Au-SPIO and 1.1225 for HG-SPIO NPs). Interestingly, Au-SPIO MPNPs with thinner plasmonic layers result in higher magnetization levels and thus lead to more efficient BBB crossing. Static magnetic field stimulation could improve brain accumulation of IP-injected Au-SPIO and HG-SPIO NPs by up to 4.9% and 1.4%, respectively. Additionally, IP injection led to higher brain accumulation compared to intravenous injection. This modern PBPK model can guide MPNP design optimization for brain-specific therapeutics.

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Availability of data and material

The datasets generated and analyzed during the current work are available from the corresponding author upon reasonable request.

Notes

  1. In this manuscript, all MPNPs are functionalized with PEG and insulin to promote blood half-life and brain permeability unless otherwise specified.

References

  1. Elmi GR et al (2022) Recent advances of magnetic gold hybrids and nanocomposites, and their potential biological applications. Magnetochemistry 8(4):38

    Article  CAS  Google Scholar 

  2. Dykman LA, Khlebtsov NG (2014) Uptake of engineered gold nanoparticles into mammalian cells. Chem Rev 114(2):1258–1288

    Article  CAS  PubMed  Google Scholar 

  3. Wang X et al (2022) Fe3O4@PVP@DOX magnetic vortex hybrid nanostructures with magnetic-responsive heating and controlled drug delivery functions for precise medicine of cancers. Adv Compos Hybrid Mater 5(3):1786–1798

    Article  CAS  Google Scholar 

  4. Jia W et al (2021) Facile fabrication of monodisperse CoFe2O4 nanocrystals@dopamine@DOX hybrids for magnetic-responsive on-demand cancer theranostic applications. Adv Compos Hybrid Mater 4(4):989–1001

    Article  CAS  Google Scholar 

  5. Chowdhury P et al (2018) Chitosan biopolymer functionalized gold nanoparticles with controlled cytotoxicity and improved antifilarial efficacy. Adv Compos Hybrid Mater 1(3):577–590

    Article  CAS  Google Scholar 

  6. Yuan M, Wang Y, Qin YX (2017) SPIO-Au core–shell nanoparticles for promoting osteogenic differentiation of MC3T3-E1 cells: concentration-dependence study. J Biomed Mater Res, Part A 105(12):3350–3359

    Article  CAS  Google Scholar 

  7. Yuan M et al (2021) Superparamagnetic iron oxide–gold nanoparticles conjugated with porous coordination cages: towards controlled drug release for non-invasive neuroregeneration. Nanomed Nanotechnol Biol Med 35. p 102392

    Google Scholar 

  8. Yuan M et al (2019) Thermocouple-tip-exposing temperature assessment technique for evaluating photothermal conversion efficiency of plasmonic nanoparticles at low laser power density. Rev Sci Instrum 90(9):094902

  9. Yuan M, Wang Y, Qin YX (2018) Promoting neuroregeneration by applying dynamic magnetic fields to a novel nanomedicine: superparamagnetic iron oxide (SPIO)-gold nanoparticles bounded with nerve growth factor (NGF). Nanomed Nanotechnol Biol Med 14(4):1337–1347

    Article  CAS  Google Scholar 

  10. Yuan M, Wang Y, Qin YX (2019) Engineered nanomedicine for neuroregeneration: light emitting diode-mediated superparamagnetic iron oxide-gold core-shell nanoparticles functionalized by nerve growth factor. Nanomed Nanotechnol Biol Med. p 102052

    Google Scholar 

  11. Yuan M et al (2022) Magnetic fields and magnetically stimulated gold-coated superparamagnetic iron oxide nanoparticles differentially modulate L-type voltage-gated calcium channel activity in midbrain neurons. Appl Nano Mater 5(1):205–215

  12. Reddy GR et al (2006) Vascular targeted nanoparticles for imaging and treatment of brain tumors. Clin Cancer Res 12(22):6677–6686

    Article  CAS  PubMed  Google Scholar 

  13. Al-Jamal KT et al (2016) Magnetic drug targeting: preclinical in vivo studies, mathematical modeling, and extrapolation to humans. Nano Lett 16(9):5652–5660

    Article  CAS  PubMed  Google Scholar 

  14. Zhang J et al (2023) Nanoliposomal Bcl-xL proteolysis-targeting chimera enhances anti-cancer effects on cervical and breast cancer without on-target toxicities. Adv Compos Hybrid Mater 6(2):78

    Article  CAS  Google Scholar 

  15. Yuan M et al (2022) Progress, opportunities, and challenges of magneto-plasmonic nanoparticles under remote magnetic and light stimulation for brain-tissue and cellular regeneration. Nanomaterials 12(13):2242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Yuan M et al (2022) Superparamagnetic iron oxide-enclosed hollow gold nanostructure with tunable surface plasmon resonances to promote near-infrared photothermal conversion. Adv Compos Hybrid Mater. pp 1–12

    Google Scholar 

  17. Chen J et al (2022) Blood-brain barrier crossing using magnetic stimulated nanoparticles. J Control Release 345:557–571

  18. Kutumova EO et al (2022) Physiologically based pharmacokinetic modeling of nanoparticle biodistribution: a review of existing models, simulation software, and data analysis tools. Int J Mol Sci 23(20):12560 %@ 1422–0067

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Qian MR et al (2017) Diffusion-limited PBPK model for predicting pulmonary pharmacokinetics of florfenicol in pig. J Vet Pharmacol Ther 40(6):e30–e38

    Article  CAS  PubMed  Google Scholar 

  20. Utembe W et al (2020) Current approaches and techniques in physiologically based pharmacokinetic (PBPK) modelling of nanomaterials. Nanomaterials 10(7):1267

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Li M et al (2017) Physiologically based pharmacokinetic (pbpk) modeling of pharmaceutical nanoparticles. AAPS J 19(1):26–42

    Article  CAS  PubMed  Google Scholar 

  22. Li M et al (2010) Physiologically based pharmacokinetic modeling of nanoparticles. ACS Nano 4(11):6303–6317

    Article  CAS  PubMed  Google Scholar 

  23. Lin Z, Monteiro-Riviere NA, Riviere JE (2016) A physiologically based pharmacokinetic model for polyethylene glycol-coated gold nanoparticles of different sizes in adult mice. Nanotoxicology 10(2):162–172

    CAS  PubMed  Google Scholar 

  24. Aborig M et al (2019) Biodistribution and physiologically-based pharmacokinetic modeling of gold nanoparticles in mice with interspecies extrapolation. Pharmaceutics 11(4):179

  25. Chou W-C et al (2022) Development of a multi-route physiologically based pharmacokinetic (PBPK) model for nanomaterials: a comparison between a traditional versus a new route-specific approach using gold nanoparticles in rats. Part Fibre Toxicol 19(1):1–19 %@ 1743-8977

    Article  Google Scholar 

  26. Dubaj T et al (2022) Pharmacokinetics of PEGylated gold nanoparticles: in vitro—in vivo correlation. Nanomaterials 12(3):511

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. LePage KT et al (2005) On the use of neuro-2a neuroblastoma cells versus intact neurons in primary culture for neurotoxicity studies. Crit Rev Neurobiol 17(1):27–50

    Article  CAS  PubMed  Google Scholar 

  28. Yang L et al (2017) Comparisons of the biodistribution and toxicological examinations after repeated intravenous administration of silver and gold nanoparticles in mice. Sci Rep 7(1):3303

  29. Daems N et al (2020) In Vivo Pharmacokinetics, biodistribution and toxicity of antibody-conjugated gold nanoparticles in healthy mice. J Biomed Nanotechnol 16(6):985–996

    Article  CAS  PubMed  Google Scholar 

  30. Lasagna-Reeves C et al (2010) Bioaccumulation and toxicity of gold nanoparticles after repeated administration in mice. Biochem Biophys Res Commun 393(4):649–655

    Article  CAS  PubMed  Google Scholar 

  31. Sonavane G, Tomoda K, Makino K (2008) Biodistribution of colloidal gold nanoparticles after intravenous administration: effect of particle size. Colloids Surf B Biointerfaces 66(2):274–280

    Article  CAS  PubMed  Google Scholar 

  32. Betzer O et al (2017) The effect of nanoparticle size on the ability to cross the blood-brain barrier: an in vivo study. Nanomedicine (Lond) 12(13):1533–1546

    Article  CAS  PubMed  Google Scholar 

  33. Jung C et al (2014) Intraperitoneal injection improves the uptake of nanoparticle-labeled high-density lipoprotein to atherosclerotic plaques compared with intravenous injection. Circ Cardiovasc Imaging 7(2):303–311

    Article  PubMed  Google Scholar 

  34. Al Shoyaib A, Archie SR, Karamyan VT (2019) Intraperitoneal route of drug administration: should it be used in experimental animal studies? Pharm Res 37(1):12

    Article  PubMed  PubMed Central  Google Scholar 

  35. Bachler G, von Goetz N, Hungerbühler K (2013) A physiologically based pharmacokinetic model for ionic silver and silver nanoparticles. Int J Nanomed 8:3365–3382

    Google Scholar 

  36. Li D et al (2014) Physiologically based pharmacokinetic modeling of polyethylene glycol-coated polyacrylamide nanoparticles in rats. Nanotoxicology 8(sup1):128–137

    Article  PubMed  Google Scholar 

  37. Brown RP et al (1997) Physiological parameter values for physiologically based pharmacokinetic models. Toxicol Ind Health 13(4):407–484

    Article  CAS  PubMed  Google Scholar 

  38. Zarrinkoob L et al (2015) Blood flow distribution in cerebral arteries. J Cereb Blood Flow Metab 35(4):648–654

    Article  PubMed  PubMed Central  Google Scholar 

  39. Fournier RL (2017) Basic transport phenomena in biomedical engineering. CRC Press

    Google Scholar 

  40. Chen J, Wang Y (2020) Personalized dynamic transport of magnetic nanorobots inside the brain vasculature. Nanotechnology 31(49):495706

    Article  CAS  PubMed  Google Scholar 

  41. Yankova G et al (2021) Cerebral arterial architectonics and CFD simulation in mice with type 1 diabetes mellitus of different duration. Sci Rep 11(1):3969

  42. Deng L et al (2019) Endocytosis mechanism in physiologically-based pharmacokinetic modeling of nanoparticles. Toxicol Appl Pharmacol 384:114765

    Article  CAS  PubMed  Google Scholar 

  43. Chithrani BD, Ghazani AA, Chan WCW (2006) Determining the size and shape dependence of gold nanoparticle uptake into mammalian cells. Nano Lett 6(4):662–668

    Article  CAS  PubMed  Google Scholar 

  44. Chithrani BD, Chan WCW (2007) Elucidating the mechanism of cellular uptake and removal of protein-coated gold nanoparticles of different sizes and shapes. Nano Lett 7(6):1542–1550

    Article  CAS  PubMed  Google Scholar 

  45. Nambara K et al (2016) Reverse size dependences of the cellular uptake of triangular and spherical gold nanoparticles. Langmuir 32(47):12559–12567

    Article  CAS  PubMed  Google Scholar 

  46. Woodard LE et al (2018) Nanoparticle architecture preserves magnetic properties during coating to enable robust multi-modal functionality. Sci Rep 8(1):12706

  47. Mitusova K et al (2022) Overcoming the blood–brain barrier for the therapy of malignant brain tumor: current status and prospects of drug delivery approaches. J Nanobiotechnol 20(1):412

  48. Takeuchi I, Onaka H, Makino K (2018) Biodistribution of colloidal gold nanoparticles after intravenous injection: effects of PEGylation at the same particle size. Bio-Med Mater Eng 29(2):205–215

    Article  CAS  Google Scholar 

  49. Olivier J-C (2005) Drug transport to brain with targeted nanoparticles. NeuroRx 2(1):108–119

    Article  PubMed  PubMed Central  Google Scholar 

  50. Dreaden EC et al (2012) Size matters: gold nanoparticles in targeted cancer drug delivery. Ther Deliv 3(4):457–478

    Article  CAS  PubMed  Google Scholar 

  51. Hoshyar N et al (2016) The effect of nanoparticle size on in vivo pharmacokinetics and cellular interaction. Nanomedicine 11(6):673–692

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Lu F et al (2009) Size effect on cell uptake in well-suspended, uniform mesoporous silica nanoparticles. Small 5(12):1408–1413

    Article  CAS  PubMed  Google Scholar 

  53. Perrault SD et al (2009) Mediating tumor targeting efficiency of nanoparticles through design. Nano Lett 9(5):1909–1915

    Article  CAS  PubMed  Google Scholar 

  54. Jiang W et al (2008) Nanoparticle-mediated cellular response is size-dependent. Nat Nanotechnol 3(3):145–150

    Article  CAS  PubMed  Google Scholar 

  55. Shilo M et al (2015) The effect of nanoparticle size on the probability to cross the blood-brain barrier: an in-vitro endothelial cell model. J Nanobiotechnol 13(1):19

    Article  Google Scholar 

  56. Reyner E et al (2020) Intrinsic and extrinsic pharmacokinetic variability of small molecule targeted cancer therapy. Clin Transl Sci 13(2):410–418

    Article  PubMed  Google Scholar 

  57. Singh AV et al (2021) Emerging application of nanorobotics and artificial intelligence to cross the BBB: advances in design, controlled maneuvering, and targeting of the barriers. ACS Chem Neurosci 12(11):1835–1853

    Article  CAS  PubMed  Google Scholar 

  58. Peer CJ, Chau CH, Figg WD (2017) Jumping the barrier: modeling drug penetration across the blood–brain barrier. Clin Cancer Res 23(24):7437–7439

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Markicevic M et al (2021) Emerging imaging methods to study whole-brain function in rodent models. Transl Psychiatry 11(1):457

  60. Qin L et al (2022) Resveratrol-silica aerogel nanodrug complex system enhances the treatment of sports osteoarthritis by activating SIRT-1. Advanced composites and hybrid materials 6(1):3

    Article  Google Scholar 

  61. Wan J et al (2023) Novel strategy of senescence elimination via toxicity-exempted kinome perturbations by nanoliposome-based thermosensitive hydrogel for osteoarthritis therapy. Adv Compos Hybrid Mater 6(3):104

  62. Bakadia B et al (2022) Biodegradable and injectable poly(vinyl alcohol) microspheres in silk sericin-based hydrogel for the controlled release of antimicrobials: application to deep full-thickness burn wound healing. Adv Compos Hybrid Mater 5(4):2847–2872

  63. Fan G et al (2021) Dielectric dispersion of copper/rutile cermets: Dielectric resonance, relaxation, and plasma oscillation. Scripta Mater 190:1–6

    Article  CAS  Google Scholar 

  64. Fan G et al (2021) Doped ceramics of indium oxides for negative permittivity materials in MHz-kHz frequency regions. J Mater Sci Technol 61:125–131

    Article  CAS  Google Scholar 

  65. Xie P et al (2017) C/SiO2 meta-composite: overcoming the λ/a relationship limitation in metamaterials. Carbon 125:1–8

    Article  CAS  Google Scholar 

  66. Chen J, Hu H, Wang Y (2023) Magnetic-driven 3D-printed biodegradable swimming microrobots. Smart Mater Struct 32(8):085014

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Acknowledgements

The authors thank the Material Characterization Facility and the Elemental Analysis Laboratory at Texas A&M University for their help.

Funding

This work was kindly supported by the United States National Science Foundation (award # CMMI 1851635, Y.W.; award # ECCS 2021081, Y.W. and Y.L.). This work was also supported by the award R01GM110137 (J.-P.P.) from the US National Institute of General Medical Sciences.

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Author notes

  1. Hanwen Hu, Muzhaozi Yuan and Jingfan Chen are co-first author.

  2. Tianzhu Fan, Nguyen Nguyen and Caitlin A. Madison are co-second author.

Authors and Affiliations

  1. J. Mike Walker ‘66 Department of Mechanical Engineering, Texas A&M University, College Station, TX, 77843, USA

    Hanwen Hu, Muzhaozi Yuan, Jingfan Chen, Tianzhu Fan, Nguyen Nguyen, Ying Li & Ya Wang

  2. Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX, 77843, USA

    Caitlin A. Madison & Shoshana Eitan

  3. Department of Chemistry, Texas A&M University, College Station, TX, 77843, USA

    Tianhao Yan, Zhifeng Xiao, Hong-cai Zhou & Jean Phillippe Pellois

  4. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843, USA

    Ya Wang

  5. Department of Biomedical Engineering, Texas A&M University, College Station, TX, 77843, USA

    Ya Wang

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Contributions

The manuscript was written through the contributions of all authors. Hanwen Hu, Muzhaozi Yuan, Jingfan Chen, Tianzhu Fan, and Tianhao Yan performed material preparation, characterization, and results analysis. In vitro cell work was performed by Nguyen Nguyen and Zhifeng Xiao. In vivo animal work was performed by Caitlin A Madison. Hanwen Hu and Muzhaozi Yuan prepared the initial draft of the manuscript. Ying Li, Shoshana Eitan, Hong-Cai Zhou, Jean-Philippe Pellois, and Ya Wang reviewed and revised previous manuscript versions. All authors have read and approved the final version of the manuscript.

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Correspondence to Muzhaozi Yuan or Ya Wang.

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Hu, H., Yuan, M., Chen, J. et al. Pharmacokinetic modeling of solid and hollow gold-coated superparamagnetic iron oxide nanoparticles for brain-targeted therapeutics: prediction and experiment. Adv Compos Hybrid Mater 7, 76 (2024). https://doi.org/10.1007/s42114-024-00884-9

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