A multi-scale stochastic drug release model for polymer-coated targeted drug delivery systems

被引:28
|
作者
Haddish-Berhane, N
Nyquist, C
Haghighi, K
Corvalan, C
Keshavarzian, A
Campanella, O
Rickus, J
Farhadi, A
机构
[1] Purdue Univ, Dept Agr & Biol Engn, W Lafayette, IN 47907 USA
[2] Rush Univ, St Lukes Med Ctr, Chicago, IL 60612 USA
关键词
drug release; multi-scale; stochastic; modeling; colon; targeted delivery;
D O I
10.1016/j.jconrel.2005.09.046
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A multi-scale mathematical model for drug release of oral targeted drug delivery systems was developed and applied to a commercially available delayed release tablet (Asacol (R)) that delivers 5-aminosalicyclic acid (5-ASA) to the colon. Underlying physical and biochemical principles governing the involved processes (diffusion and dissolution) were employed to develop the mathematical description. Finite element formulation was used to numerically solve the model equations. Molecular dynamics (MD) simulations were used to predict macro-scale transport properties of the drug and the biologic fluid. The effect of pH variability in the gastrointestinal tract environment on the dissolution of the polymeric enteric coating was investigated using the Monte Carlo method. The direct coupling method employed (MD) predicted a sufficiently accurate diffusion coefficient (5.7 x 10(-6) cm(2) s(-1)) of the drug molecules in reasonable (3 h) computation times. The model was validated using experimental data from in vitro dissolution experiments and provided accurate prediction of the drug release from the delivery system (root mean square error of 5%). The amount of drug entering the systemic circulation, computed from the predicted drug release in varying pH environments in the small bowel, was 15-24%. This range was in good agreement with clinical in vivo data (13-36%) obtained from literature. This research shows that in silico experiments using mechanistic models and stochastic approaches can be used for drug design and optimization and as a decision making tool for physicians. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:314 / 322
页数:9
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