Properties of rapamycin solid lipid nanoparticles for lymphatic access through the lungs & part II: the effect of

Emelie Landh1,2, Lyn M Moir1,2, Daniela Traini1,2

  • 1Respiratory Technology, Woolcock Institute of Medical Research, Glebe, NSW, 2037, Australia.

Insights

Negative surface charge on inhaled rapamycin solid lipid nanoparticles (Rapa-SLN) enhances lymphatic penetration and anti-angiogenesis efficacy for treating lymphangioleiomyomatosis.

Area of Science:

  • Nanomedicine
  • Pulmonary Medicine
  • Pharmacology

Background:

  • Lymphangioleiomyomatosis (LAM) involves lung smooth muscle cell proliferation and metastasis via lymphatics.
  • Oral rapamycin for LAM has low bioavailability (~15%), limiting therapeutic effectiveness.
  • Targeting lymphatic spread requires effective drug delivery to lymphatic vessels.

Purpose of the Study:

  • To investigate the impact of surface charge on inhaled rapamycin solid lipid nanoparticles (Rapa-SLN) for LAM treatment.
  • To evaluate Rapa-SLN efficacy and lymphatic penetration based on nanoparticle charge (neutral, positive, negative).

Main Methods:

  • Synthesis and characterization of Rapa-SLN with varying surface charges (neutral, positive, negative).
  • In vitro assessment of physicochemical properties and biological efficacy.
  • Evaluation of lymphatic endothelial cell entry and anti-angiogenesis activity.

Main Results:

  • Negative Rapa-SLNs demonstrated significantly enhanced entry into lymphatic endothelium compared to neutral and positive formulations.
  • Negative Rapa-SLNs exhibited superior inhibition of lymphangiogenesis in vitro.
  • Surface charge critically influences Rapa-SLN lymphatic targeting and therapeutic potency.

Conclusions:

  • Negatively charged Rapa-SLNs offer efficient access to lymphatic vessels, suggesting improved therapeutic potential.
  • Inhaled negative Rapa-SLNs represent a promising strategy for targeting extrapulmonary lymphangioleiomyomatosis.
  • Further investigation of negative Rapa-SLNs is warranted for LAM treatment optimization.

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