Risk Management in Real Options Based Pharmaceutical Portfolio Planning

Recent research efforts in options pricing have shown that real options approaches are more appropriate for R&D project valuation because they account for the value of managerial flexibility to react to arising contingencies during R&D development. This technique allows for strategic decision-making in the context of hedging opportunities present in the financial markets by tracking the uncertainty in the value of a project in development through market-traded securities. In this work, we incorporate a Monte Carlo simulation procedure to a stochastic optimization model (OptFolio) of pharmaceutical R&D portfolio selection. This framework provides for a sensitivity analysis of candidate drug valuations and a risk management analysis for balancing risk versus reward tradeoffs. The resulting valuation method is applied to a case study involving the selection of optimal product portfolios, those that minimize risk for a specified level of return, to begin Phase I clinical testing from a set of candidate drugs.