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Formulation of Gelled Non-toxic Bicontinuous Microemulsions Stabilized by Highly Efficient Alkanoyl Methylglucamides.

Ke PengNatalie PreisigThomas SottmannCosima Stubenrauch
Published in: Langmuir : the ACS journal of surfaces and colloids (2020)
Gelled non-toxic bicontinuous microemulsions have a great potential for transdermal drug delivery as the microemulsion facilitates the solubilization of both hydrophilic and hydrophobic drugs, while the gel network provides mechanical stability and thus an easy application on the skin. In our previous study, we formulated a gelled non-toxic bicontinuous microemulsion: we gelled the system H2O-isopropyl myristate (IPM)-Plantacare 1200 UP (C12G1.4)-1,2-octanediol with the low molecular weight organogelator 1,3:2,4-dibenzylidene-d-sorbitol (DBS). However, a large amount of Plantacare 1200 UP (12 wt %) is needed to form a bicontinuous microemulsion. To solve this problem, we studied a new class of surfactants, namely, alkanoyl methylglucamides (MEGA), which have been rarely used for the formulation of microemulsions. The phase behavior of microemulsions stabilized by MEGA-8/10, MEGA-12/14-PC, and MEGA-12/14-HC was compared with that of systems stabilized by alkyl polyglucosides. We found that even with 2 wt % MEGA-12/14-HC, a bicontinuous microemulsion can be formed, which is 1/6 of the amount of Plantacare 1200 UP. The bicontinuous microstructure of the non-toxic microemulsion H2O-IPM-MEGA-12/14-HC-1,2-octanediol was confirmed by small-angle neutron scattering. Furthermore, the phase boundaries remained unchanged when gelled by DBS. The rheological properties of the gel were studied by oscillatory shear rheometry. Finally, freeze-fracture electron microscopy images show the coexistence of gel fibers and bicontinuous oil and water domains. These results suggest that the new gelled non-toxic bicontinuous microemulsion is an orthogonal self-assembled system.
Keyphrases
  • drug delivery
  • highly efficient
  • wound healing
  • deep brain stimulation
  • electron microscopy
  • multiple sclerosis
  • cancer therapy
  • white matter
  • machine learning
  • risk assessment
  • hyaluronic acid
  • fatty acid