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Simulating particle movement inside subcutaneous injection site simulator (SCISSOR) using Monte-Carlo method.

Hao Lou1, Cory Berkland2, Michael J Hageman1

  • 1Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66047, USA; Biopharmaceutical Innovation and Optimization Center, University of Kansas, Lawrence, KS 66047, USA.

International Journal of Pharmaceutics
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PubMed
Summary

This study simulated particle movement in the Subcutaneous Injection Site Simulator (SCISSOR) using the Monte Carlo method. Key factors influencing drug release were identified, including membrane properties and injection site, offering insights for development.

Keywords:
AggregationBindingDiffusionMonte Carlo simulationSCISSORSubcutaneous formulation

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Area of Science:

  • Pharmacokinetics and Drug Delivery
  • Computational Modeling and Simulation

Background:

  • Understanding particle behavior in subcutaneous (SC) injections is crucial for drug delivery optimization.
  • The Subcutaneous Injection Site Simulator (SCISSOR) is a commercialized instrument requiring detailed simulation for performance analysis.

Purpose of the Study:

  • To simulate particle movement within the SCISSOR using the Monte Carlo method.
  • To investigate the impact of various parameters on particle release profiles in the SC space.
  • To evaluate the effects of particle diffusion, binding, and aggregation on release dynamics.

Main Methods:

  • Utilized the Monte Carlo method for particle movement simulation within the SCISSOR.
  • Incorporated parameters including instrument specifics, injection device, operation, formulation, and medium properties.
  • Modeled SC space events such as diffusion, binding, and aggregation.

Main Results:

  • Membrane area and position, SC medium diffusivity, and injection site significantly influenced release profiles.
  • Low diffusivity within the injection volume impacted release only under extreme conditions.
  • Particle binding slowed release, while aggregation reduced both the percentage and rate of release.

Conclusions:

  • The Monte Carlo method is a powerful tool for analyzing SC injection parameters and optimizing experimental design.
  • Simulation insights support parameter sensitivity analysis and the development of control strategies for drug delivery systems.
  • Identified critical factors for controlling drug release kinetics in subcutaneous injections.