Pharmaceutical portfolio optimization under cost uncertainty via chance constrained-type method

Project selection for a portfolio is a pivotal decision in the pharmaceutical industry. In this paper, we study a portfolio optimization problem for pharmaceutical companies considering the uncertainty of the cost of each phase of drug development and the specific value of the annual budget. The presented optimization model is suitable to make investment decisions for multi-phase drug development projects and a stochastic approach is applied to handle the uncertainty in the model. Post-optimality analysis for annual budget is studied. An illustrative example is included to demonstrate the presented approach.