Identification and Predictive Analysis of Revenue Determinants in the Pharma Industry: A Longitudinal Analysis of Financial, Regulatory and Pipeline Data

Abstract Purpose Maintaining positive revenue performance and R&D productivity is crucial for the pharma industry, therefore identifying and predicting future revenue determinants is of upmost importance. The aim of the study was to identify factors that determine annual revenue and to use these factors to develop a model that predicts future revenues. Methods IDEA Pharma’s longitudinal Pharmaceutical Innovation and Invention Index data were used to conduct the analyses, looking at the financial, regulatory and pipeline data (2019–2023) of the top 24 pharmaceutical companies. Broader industry trends over the last 5 years were analysed using descriptive statistics. To validate the factors gleaned from the descriptive statistics, a predictive model was constructed. This was done through predictive statistical analysis (stepwise regression), producing a model that can predict future revenue. Results Three factors were determined to be significant determinants of higher future revenues: higher R&D spend, lower R&D spend as a proportion of current revenue, and higher number of Phase III clinical trials. Conclusions The resulting model combined financial, commercial, and strategic metrics from the world’s largest pharmaceutical companies to produce a statistically robust method of predicting revenues, that is critical for every pharma company’s growth and strategic planning.