OBJECTIVES: When predicting the price and health technology assessment (HTA) outcomes of future pharmaceuticals, it is crucial to compare them with already approved similar drugs, also known as analogues. Analogue analysis is highly relevant as payers in many countries use price benchmarking for pharmaceuticals. This analysis also reflects the historical willingness to pay for certain types of drugs. The aim of the present work was to build a tool for rapid pharmaceutical data visualization and identification of analogue drugs.

METHODS: The Analogue Analysis Tool (AAT) was built in Python by using the Bokeh library for data visualization and JavaScript code for callbacks. The tool uses pharmaceutical pricing data from a database built by Access Infinity.

RESULTS: Analogue drugs are identified by filtering entries in the database using intuitive controllers on a user-friendly interface. Drugs are selected in any combination based on their therapeutic area, formulation, target population, orphan designation, population size, number of indications, patient population size, date of market approval, and price in the UK. Users can explore the list of selected pharmaceuticals, as well as visualize bar charts and interactive scatter plots of drug properties, such as country-specific price, patient population size, date of market approval, and the number of indications.

CONCLUSIONS: The large number of variables that can be manipulated intuitively by the user, as well as the output graph flexibility enable the AAT to meet the requirements of any client. It can be used to perform a wide array of analyses, such as price and HTA outcome exploration by therapeutic area and formulation, outcomes of pharmaceuticals with pediatric or orphan designation, and comparison of HTA outcomes and prices in different countries.