System and method for manufacturing oral osmotic drug delivery devices, and methods of administering same

Abstract

A system and method for manufacturing oral osmotic drug delivery devices including the use of a mathematical model in deriving relationships between parameters used in manufacturing the devices for a desired release rate of the active drug substance contained therein. The derived relationship is then used to control the parameters so that the active substance within the device is delivered at a desired rate. Methods of administering the oral osmotic drug delivery devices are also provided. Use of a mathematical model in deriving relationships between parameters used in the drug granulation process for a desired range of percentage fines of the drug granulation substance. The derived relationship is then used to control the parameters in the drug granulation process so that the desired percentage fines are obtained in the drug granulation substance.

1 - 20 . (canceled) 
   
   
       21 . A method, comprising manufacturing a plurality of oral osmotic drug delivery devices, each of which comprises a bi-layer core comprising (1) an active layer comprising particles of a mixture of isradipine and one or more excipients wherein the particles have a particle size distribution as determined by the percentage of the particles that pass through a #120 mesh screen, and (2) an osmotic layer, and a semi-permeable outer coating substantially surrounding the bi-layer core, by a method comprising obtaining a selected release rate by applying a relational mechanism relating the particle size distribution, a weight value of the plurality of bi-layer cores, and a weight value of the outer coating; and administering once daily to a subject one of the oral osmotic drug delivery devices. 
   
   
       22 . The method according to  claim 21 , wherein the relational mechanism is derived using a neural network. 
   
   
       23 . The method according to  claim 21 , wherein the relational mechanism is derived using multiple linear regression. 
   
   
       24 . The method according to  claim 21 , wherein the relational mechanism is derived using Monte Carlo simulation. 
   
   
       25 . The method according to  claim 21 , wherein the relational mechanism comprises a table.