TY - JOUR
T1 - Release phenomena of insulin from an implantable device composed of a polyion complex of chitosan and sodium hyaluronate
AU - Surini, Silvia
AU - Akiyama, Hidero
AU - Morishita, Mariko
AU - Nagai, Tsuneji
AU - Takayama, Kozo
PY - 2003/7/31
Y1 - 2003/7/31
N2 - An implant controlled-release system for protein drug delivery based on a polyion complex device composed of chitosan (CS) and sodium hyaluronate (HA) was investigated. The conditions which generated the greatest amount of the polyion solid complex were studied to ascertain the formation of polyion complex between CS and HA. The greatest amount of the polyion complex was formed at the weight ratio of 3 to 7 (CS:HA) at pH 3.5. Furthermore, the CS-HA pellets were prepared and then drug release from CS-HA pellets was evaluated using insulin as a model drug. The results demonstrated that the insulin release from CS-HA pellets was markedly influenced by both the change in the polymer mixing ratio and the total pellet weight, whereas the compression pressure did not affect the release significantly. An artificial neural network (ANN) and biharmonic spline interpolation (HSI) were employed to predict the actual relation between causal factors and the release rate constant of insulin. Although both the ANN and HSI successfully represented a non-linear relationship between the formulation factors and the release rate constant, HSI methodology gave a better estimation than that of the ANN.
AB - An implant controlled-release system for protein drug delivery based on a polyion complex device composed of chitosan (CS) and sodium hyaluronate (HA) was investigated. The conditions which generated the greatest amount of the polyion solid complex were studied to ascertain the formation of polyion complex between CS and HA. The greatest amount of the polyion complex was formed at the weight ratio of 3 to 7 (CS:HA) at pH 3.5. Furthermore, the CS-HA pellets were prepared and then drug release from CS-HA pellets was evaluated using insulin as a model drug. The results demonstrated that the insulin release from CS-HA pellets was markedly influenced by both the change in the polymer mixing ratio and the total pellet weight, whereas the compression pressure did not affect the release significantly. An artificial neural network (ANN) and biharmonic spline interpolation (HSI) were employed to predict the actual relation between causal factors and the release rate constant of insulin. Although both the ANN and HSI successfully represented a non-linear relationship between the formulation factors and the release rate constant, HSI methodology gave a better estimation than that of the ANN.
KW - Artificial neural network
KW - Biharmonic spline interpolation
KW - Chitosan
KW - Polyion-complex
KW - Sodium hyaluronate
UR - http://www.scopus.com/inward/record.url?scp=0037768709&partnerID=8YFLogxK
U2 - 10.1016/S0168-3659(03)00196-2
DO - 10.1016/S0168-3659(03)00196-2
M3 - Article
C2 - 12880696
AN - SCOPUS:0037768709
VL - 90
SP - 291
EP - 301
JO - Journal of Controlled Release
JF - Journal of Controlled Release
SN - 0168-3659
IS - 3
ER -