One of the most critical processes for any R&D organization is project prioritization — deciding which projects will be funded over the next period and which will not. Pharmaceutical companies, in particular, have to make big investment decisions about their drug pipelines. These decisions involve complex assessments of technical, clinical, regulatory, legal, and commercial risk, often projecting conditions 5, 10, or more years in the future. To contend with this challenge, major companies long ago adopted sophisticated techniques — including expected value analysis, and option value analysis — to assess the technical and commercial merits of individual compounds and then rank them based on their risks and potential returns.

Despite the time and resources that are poured into R&D prioritization, the process still tends to be sub-optimized. The fundamental reason for this gap is that the framework that companies generally use in their prioritization decisions is incomplete.

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