Alliance Life Sciences Issues Free Study Supporting Deep Modeling Method for Predicting Price Change Percentages Post-FDA Approval

Alliance Life Sciences Consulting Group (ALSCG), an innovative management and technology consultancy, announces the release of “Predicting Price Changes of Oncology Drugs in the United States,” a study presented by Bruce Wang, director, ALSCG, at the ISPOR 15th Annual European Congress. The study demonstrates how statistical modeling can predict the percentage change in price of prescription drugs post-Food and Drug Administration (FDA) approval, and if the probability of a price change depends upon the timing.

“The ability to determine this type of information is extremely valuable to policy-makers, pharmaceutical companies, and investment firms because it enables more informed insights and decision-making through predictive modeling and analytics on the lifecycle of a drug,” says Mohan Purushothaman, executive vice president, ALSCG. “As a result of our pricing, contracting and market access capabilities, ALSCG is able to offer this level of deep modeling within pharma commercial operations.”

To perform predictions, ALSCG applied Cox Proportional Hazard Models -- a class of survival models in statistics -- to a set of oncology drugs in the US. Survival models relate the time that passes before an event occurs to one or more variables that may be associated with it. In this case, ALSCG observed the events leading up to a price change in order to predict the timing and percentage of that change.

“This model showed that for each additional month since FDA approval, the ‘risk’ of a price raise increased by 0.7 percent,” Purushothaman adds. “Similarly, there was a second order effect showing this risk diminishing over time. This kind of deep modeling capability can significantly benefit the Life Sciences industry in terms of forecasting price change.”