VOI News

New Study on Time-to-Peak Sales for US Pharmaceuticals

Drug launch curves in the modern era, a new article in the January 2017 issue of Nature Reviews: Drug Discovery, contains projections of relevance for forecasting pharmaceutical sales in the US market. Relying on unit sales for 61 innovative drugs receiving FDA approval between 2000 and 2002, the authors determined that the median product follows an S-shaped launch-to-peak penetration curve: achieving 11% of peak sales in Year 1, 31% in Year 2, 58% in Year 3, 76% in Year 4, 89% in Year 5, and 100% (i.e. peak sales) in Year 6. On an interquartile basis, time-to-peak (TTP) ranged from 4 to 9 years; the minimum TTP was 2 years and the maximum was 14.

Using data from the Supplemental Materials file we find that the average for TTP for first-in-class drugs is 5.65 years as opposed to 6.93 years for subsequent entrants. Unlike other research on the subject, however, the authors did not that there was a statistically significant relationship between entry order and TTP. But, as they note, TTP is distinct from factors such as market share and revenue potential that may be more indicative of first-mover advantage.

Generic drug sales forecasting published in Journal of Generic Medicines

VOI Consulting is pleased to announce that Probability-based forecasting for U.S. generic drug sales, an original article by VOI’s President, Todd Clark, has been published in the Journal of Generic Medicines: The Business Journal for the Generic Medicines Sector. The article abstract is below:

Probability-based forecasting for U.S. generic drug sales
Todd D Clark, Value of Insight Consulting, Inc.
Journal of Generic Medicines, September 2014

Most sales forecasts, including those in the generic drug industry, are based on an implicit assumption that the market can be represented as a continuous variable, an approach that works only when activity consists of many independent, incremental customer buying decisions, each of which is too small to substantially affect total sales. These conditions are generally true in branded pharmaceutical markets but they do not reflect the reality of the US generic drug industry where decisions regarding which company’s product is dispensed at the pharmacy are primarily a function of a limited number of binary (yes/no) decisions from drug wholesaling companies, the largest of which control access to one-fourth of the market or more. Unfortunately, binary situations are difficult to model in standard spreadsheet forecasts due to the extremely high number of permutations that are possible even with a small number of variables. In this paper, we explore the binary nature of the US multi-source industry from a single, hypothetical, generic company’s perspective and discuss a probability-based sales forecasting technique that offers a more accurate approach to modeling based on the number of wholesaler contracts available and the degree of generic competition present. The forecast is derived from actual wholesaler market share data and, based on extensive industry experience, the parameters used are believed to be reasonably representative of the US generic market, meaning that the results can be scaled to determine approximate probabilities of achieving certain revenue levels in real-world situations.

The article will be published in the September 2014 print version of the Journal of Generic Medicines. It is currently available online.