R&D Project Valuation in the Pharmaceutical Industry

Ann-Sofie Egeberg Madsen & Mathias Rask Sørensen

Student thesis: Master thesis


The main purpose of this thesis is to evaluate the application of different valuation models in the context of a drug development project in the pharmaceutical industry. This is interesting, as there seems to be a gap between what is recommended by academics and what is applied in practice. Furthermore, this is an important topic as this industry spends several billion USD annually, the development process is rigorous and authorities regularly reject products. To develop a drug the project have to go through several clinical trials from which they have to get approved, and the process can therefore be seen as a staged investment process. To test whether valuation methods are able to capture these characteristics both traditional models and more sophisticated real option approaches have been applied. The results were analyzed and sensitivity analyses were carried out for each model in order to compare the advantages and disadvantages of using the different models for valuation purposes.
The results obtained proved that there were significant differences between the valuation methods. First, it was found that the results varied greatly depending on whether a probability for advancing to the next clinical trial was explicitly included or not. Second, whether the models include multiple decision points or not, makes a great difference to the valuations. Third, the option valuation approaches were originally built for financial options, therefore, many of the assumptions and input parameters do not fit real options perfectly, and the consequences of this are not conclusive.
Consequently, some of the concerns pointed out throughout the thesis were discussed. One of the important topics was how the results could impact managerial decision-making. Here it was discussed that there exists a trade-off between applicability and preciseness. This also raised the question whether managers were willing to utilize the more advanced models due to their complexity.
Finally it was concluded that the optimal model is hard to define, as it is believed that it should include relevant information, as well as being applicable in practice. It was therefore suggested that using several models to shed light on different aspects might be the best approach while still being able to explain the results to decision-makers.

EducationsMSc in Applied Economics and Finance, (Graduate Programme) Final Thesis
Publication date2017
Number of pages134