Solution Conditions Tune and Optimize Loading of Therapeutic Polyelectrolytes into Layer-by-Layer Functionalized
Santiago Correa1, Natalie Boehnke2, Elad Deiss-Yehiely3
1Department of Biological Engineering , Massachusetts Institute of Technology , 21 Ames Street , Cambridge , Massachusetts 02142 , United States.
ACS Nano
|April 16, 2019
Summary
Layer-by-layer (LbL) nanoparticles are promising for drug delivery. Optimizing solution conditions like pH and ionic strength significantly improved nucleic acid loading in LbL liposomes by eightfold.
Area of Science:
- Nanotechnology
- Materials Science
- Biomedical Engineering
Background:
- Layer-by-layer (LbL) nanoparticles show potential for drug delivery, including chemotherapeutics and nucleic acids.
- Their ability to encapsulate multiple elements enables complex combination therapies with staged release.
- Colloidal LbL systems lack systematic studies on critical synthetic conditions for robust assembly.
Purpose of the Study:
- To address fundamental questions for reliable synthesis of nucleic acid-containing LbL liposomes.
- To investigate the impact of solution conditions on LbL nanoparticle preparation.
- To optimize parameters for enhanced therapeutic agent loading.
Main Methods:
- Systematic study of solution conditions: pH, ionic strength, salt composition, and valency.
- Analysis of adsorption behavior of nucleic acids and synthetic polypeptides.
- Optimization of parameters to control ionization and electrostatic screening length.
Main Results:
- Identified key solution conditions influencing the adsorption of materials onto nanoscopic templates.
- Provided insights into controlling the degree of ionization and electrostatic screening length.
- Achieved an approximately 8-fold improvement in nucleic acid loading within LbL liposomes.
Conclusions:
- Optimizing solution conditions is crucial for robust and efficient synthesis of LbL nanoparticles.
- Defined principles for constructing highly effective therapeutic nanoparticle systems.
- Demonstrated significant enhancement in nucleic acid loading through parameter optimization.
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