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Microfluidic extensional flow device to study mass transfer dynamics in the polymer microparticle formation process.

Suryavarshini SundarGhata M NirmalSuraj BorkarSachin GoelKarthik RamachandranRansom KochharEric J HukkanenRenato A ChiarellaArun Ramachandran
Published in: Soft matter (2024)
Polymer microparticles are often used to encapsulate drugs for sustained drug-release treatments. One of the ways they are manufactured is by using a solvent extraction process, in which the polymer solution is emulsified into an aqueous bulk phase using a surfactant as a stabilizing agent, followed by the removal of the solvent. The radius of a polymer drop decreases as a function of time until the polymer reaches the gelling point, after which it is separated and dried. Among the various operating parameters, the rate of solvent extraction is a critical step that affects the morphology and porosity, and consequently, the kinetics of drug release. But a fundamental mechanistic understanding of the solvent extraction dynamics as a function of shear is still unexplored. In this study, we have developed an experimental mass transfer model to predict the extraction by using the microfluidic extensional flow device (MEFD) to probe the shear and extraction dynamics at the level of a single drop in a linear extensional flow field. We used a computer-controlled feedback algorithm to manipulate the flow field and hydrodynamically trap a Hele-Shaw drop and observe the extraction process. For the polymer solution, we used a biocompatible polymer, poly-lactic- co -glycolic acid (PLGA) with ethyl acetate (EtOAc) as the solvent. Our experiments were conducted by varying the extensional rate ( G ) in the channel from ∼0.1 s -1 to ∼10 s -1 , and using an analytical solution of the flow field, we captured the dissolution process and measured the change in drop radius ( R ) with time ( t ). Interestingly, we initially observed a short-time asymptote R ∼ t , and later the long-time asymptote of R = constant; both trends were physically explained. The transport model developed in this work can be used to predict extraction rates and polymer microparticle composition for any polymer-solvent system. This work is also an important contribution to the literature on convective mass transfer in partially miscible emulsions.
Keyphrases
  • drug release
  • ionic liquid
  • drug delivery
  • systematic review
  • high throughput
  • single cell
  • machine learning
  • solar cells
  • circulating tumor cells
  • liquid chromatography
  • electron transfer
  • neural network
  • bone regeneration