Pharmaceuticals Examples

Pharmaceuticals Marketing

Ventana has built marketing models for a variety of drug classes (see other examples in our pharmaceuticals category). This video demonstrates a model distilled from several of those implementations, including nonlinearity of the outcome – meaning, for example, that optimal pricing is not independent of marketing effort, and vice versa. The model includes dynamics of

Leveraging Individual Patient Data

In building simulation models of pharmaceutical markets over the last fourteen years, one of the biggest changes has involved the availability of data for very large blinded samples of individual patients. In Europe this trend moved somewhat ahead of the United States. But now, the availability of data from managed care organizations, hospitals and large

Market Impact of Generic Drugs

This topic is to give an example of Ventana technical success in: (a) tackling an important and difficult pharma prediction problem, and (b) suggesting that this success can be replicated because the causal drivers of generic sales growth tend to be same across therapy areas and countries. In 2001, Ventana was asked to predict the

Feedback in Epidemiology for Market Sizing

In early 1995 data showed that the HIV/AIDS population was growing at a terrifying rate in the United States. Moreover, although the so-called AIDS cocktail was in clinical trials, very few people were aware of what its performance would turn out to be. Ventana was engaged by a pharmaceutical company to develop a decision-support tool for

New Product Decision Process

For a research pharmaceutical company, Ventana designed and built a decision-support model to help manage the development of a new drug. When the modeling was started, over $120 million was committed to the development of a new drug to better treat a fatal infectious disease. The drug had been under development for two years, and

Marketing New Pharmaceutical Products

Starting in 1997 and continuing over more than a decade, Ventana built a number of different models for one of the world’s best known pharmaceuticals companies. These models were designed to make contingent predictions of drug sales using inputs such as the attributes of products and the mix of promotion alternatives available. Several of the