Purpose <p>Maintaining positive revenue performance and R&amp;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.</p> Methods <p>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&#xa0;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.</p> Results <p>Three factors were determined to be significant determinants of higher future revenues: higher R&amp;D spend, lower R&amp;D spend as a proportion of current revenue, and higher number of Phase III clinical trials.</p> Conclusions <p>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.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

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

  • Rusne Sipelyte,
  • Athina Marina Metaxa

摘要

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.