Factors Affecting Mechanism and Kinetics of Drug Release from Matrix-Based Oral Controlled Drug Delivery Systems

Matrix technologies have often proven popular among the oral controlled drug delivery technologies because of their simplicity, ease in manufacturing, high level of reproducibility, stability of the raw materials and dosage form, and ease of scale-up and process validation. Technological advancements in the area of matrix formulation have made controlled-release product development much easier than before, and improved upon the feasibility of delivering a wide variety of drugs with different physicochemical and biopharmaceutical properties. This is reflected by the large number of patents filed each year and by the commercial success of a number of novel drug delivery systems based on matrix technologies. Matrix-based delivery technologies have steadily matured from delivering drugs by first-order or square-root-of-time release kinetics to much more complex and customized release patterns. In order to achieve linear or zero-order release, various strategies that seek to manipulate tablet geometry, polymer variables, and formulation aspects have been applied. Various drug, polymer, and formulation-related factors, which influence the in situ formation of a polymeric gel layer/drug depletion zone and its characteristics as a function of time, determine the drug release from matrix systems. Various mathematical models, ranging from simple empirical or semi-empirical (Higuchi equation, Power law) to more complex mechanistic theories that consider diffusion, swelling, and dissolution processes simultaneously, have been developed to describe the mass transport processes involved in matrix-based drug release. Careful selection of an appropriate model for drug release provides insight to the underlying mass transport mechanisms and helps in predicting the effect of the device design parameters on the resulting drug-release rate. Thus, a basic understanding of release kinetics and appropriate mechanisms of drug release from matrix system and their inter-relationships may minimize the number of trials in final optimization, thereby improving formulation development processes.