Modelling and forecasting pharmaceutical lifecycles

We examine the pharmaceutical sales in the context of lifecycle modelling and forecasting using time series analysis. This is accomplished by comparing the lifecycles of 1000 pharmaceutical drugs using an algorithm that determines the most common lifecycles of pharmaceutical drugs. The data regarding these drugs comes from a database known as Jigsaw that contains data associated with 2.57 million scripts written by General Practitioner’s (GP’s). Our research aims to produce these graphs for individual drugs using the number of sales that occurs, while also comparing the lifecycles for each drug in sixteen Regional Health Association’s (RHA’s). The second phase of the study focuses on forecasting the final section of the pharmaceutical drugs’ lifecycles using a number of state of the art methods to determine which accurately fits the data.