Robust Prediction with Text: Identifying Drivers of Commercial Value of Healthcare Innovations

4/11/19 | 4:15pm | E51-325
Reception to follow.





Dessi Pachamanova

Babson College 

Abstract: This talk will discuss a robust text-based framework for analyzing the commercial value of innovations. Specifically, we show how one can identify key characteristics of patented healthcare innovations that lead to appropriation of value from the patent via licensing. We illustrate the framework using data from a large healthcare provider. Our framework can be useful for organizational forms that not only invest in and commercialize innovations but also act as distributors of intellectual property rights.

Bio: Dessislava Pachamanova is Visiting Professor at the MIT Sloan School of Management and Zwerling Family Endowed Professor at Babson College. Her research and consulting span theory and applications of robust optimization, predictive analytics, financial engineering, and simulation. She holds an A.B. in Mathematics from Princeton University and a Ph.D. in Operations Research from the Sloan School of Management at MIT.

Event Time: 

2019 - 16:15