Application of a mixture experimental design in the optimization of a self-emulsifying formulation with a high drug load.
Response surface methodology (RSM) was applied to optimize the self-emulsifying drug delivery system (SEDDS) containing 25% (w/w) Drug A, a model drug with a high lipophilicity and low water solubility. The key objective of this study was to identify an optimal SEDDS formulation that: 1) possesses a minimum concentration of the surfactant and a maximum concentration of lipid and 2) generates a fine emulsion and eliminates large size droplets (> or = 1 microm) upon dilution with an aqueous medium. Three ingredient variables [PEG 400, Cremophor EL, and a mixture of glycerol dioleate (GDO), and glycerol monooleate (GMO)] were included in the experimental design, while keeping the other ingredients at a fixed level (25% Drug A, 6% ethanol, 3% propylene glycol, 4% water, and 2% tromethamine) in the SEDDS formulation. Dispersion performance of these formulations upon dilution with a simulated gastrointestinal fluid was measured, and the population of the large droplets was used as the primary response for statistical modeling. The results of this mixture study revealed significant interactions among the three ingredients, and their individual levels in the formulation collectively dictated the dispersion performance. The fitted response surface model predicted an optimal region of the SEDDS formulation compositions that generate fine emulsions and essentially eliminates large droplets upon dilution. The predicted optimal 25% Drug A-SEDDS formulations with the levels of Cremophor EL ranging from 40-44%, GDO/GMO ranging from 10-13%, and PEG 400 ranging from 2.7-9.0% were selected and prepared. The dispersion experiment results confirmed the prediction of this model and identified potential optimal formulations for further development. This work demonstrates that RSM is an efficient approach for optimization of the SEDDS formulation.
Gao
Ping
P
Michigan Pharmaceutical Sciences, Pfizer Inc., Kalamazoo, Michigan 49007, USA. ping.gao@pfizer.com
Witt
Martha J
MJ
Haskell
Roy J
RJ
Zamora
Kathryn M
KM
Shifflett
John R
JR
D000465:Algorithms; D055598:Chemical Phenomena; D002626:Chemistry, Pharmaceutical; D002627:Chemistry, Physical; D016503:Drug Delivery Systems; D004655:Emulsions; D005079:Excipients; D015233:Models, Statistical; D011409:Propylene Glycols; D012542:Scattering, Radiation; D012995:Solubility; D013501:Surface-Active Agents
D004655:Emulsions; D005079:Excipients; D011409:Propylene Glycols; D013501:Surface-Active Agents