A Design of Experiment Analysis of Log-Normal Microsphere Distributions Modeling Drug Delivery

Technology transfer hurdles constantly keep effective medical treatment from healthcare. One prevalent hurdle is that of cost. Regulation from any organization or entity can drive up cost and requires thorough review before implementation. For microspheres specifically, extensive research has been conducted to minimize variation in size. How variation effects drug delivery of microspheres, however, has not been studied in depth. In this study, a preliminary approach to modeling drug delivery in microspheres with a given log-normal distribution is reported. A design of experiment statistical analysis was performed using incremental values of mean and standard deviation. To estimate the rate of drug diffusing from the microspheres, a simplified Fick's second law was used. Various data types were considered and it was found that the shape factors which are related to mean and standard deviation fit the statistical analysis best. Using the shape factor data type, equation characteristics were identified and reported. It was seen that standard deviation has a greater influence on drug delivery than mean. A prediction expression is presented that can be used to identify the time it takes to get to 60% drug delivery and can be used in a scaled manner.