FITTING OF DIFFUSION-COEFFICIENTS IN A 3-COMPARTMENT SUSTAINED-RELEASE DRUG FORMULATION USING A GENETIC ALGORITHM

This article presents a method of fitting diffusion coefficients in a three-compartment drug formulation to data of concentration measuremen ts. The volume of the central compartment is not constant, but increas es with time up to a certain amount. The speed of growth is proportion al to the actual distance from the final thickness. A model function b ased on Fick's second law of diffusion is used to describe the concent ration with respect to location and time. In order to find the values of the diffusion coefficients they are encoded to data structures on w hich the mechanisms of evolution can be applied: mutation and selectio n. It is shown how the convergence speed is influenced by the optimiza tion parameters: the more individuals are involved in the evolution pr ocess, the fewer the generations it takes the algorithm to fit the par ameters. There are optimal values for the rate of mutation (m approxim ate to 0.008 bit(-1)) and the selection factor, which controls the inf luence of selection in the mating process. Its optimal value is less t han unity, which means that the algorithm converges faster when someti mes the genetic information of the weaker of two individuals is passed on to the next generation.