New Product Development with Discrete Event Simulation: Application to Portfolio Management for the Pharmaceutical Industry

New product development (NPD) constitutes a challenging problem in the pharmaceutical industry. Formally, the NPD problem can be stated as follows: Select a set of R&D projects from a pool of candidate projects to satisfy several criteria (e.g., economic profitability, time to market) while copi...

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Veröffentlicht in:Industrial & engineering chemistry research 2011-09, Vol.50 (18), p.10615-10629
Hauptverfasser: Pérez-Escobedo, J. L, Azzaro-Pantel, C, Pibouleau, L
Format: Artikel
Sprache:eng
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Zusammenfassung:New product development (NPD) constitutes a challenging problem in the pharmaceutical industry. Formally, the NPD problem can be stated as follows: Select a set of R&D projects from a pool of candidate projects to satisfy several criteria (e.g., economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to be developed, together with the order in which they enter the pipeline and the corresponding resource allocation. In this context, this work presents the development and implementation of a discrete event simulator for drug portfolio management based on object-oriented techniques and used as a tool for evaluating each drug or sequence of drugs. Evaluation methods based on bubble charts are used for selecting the best drugs according to the considered evaluation criteria. Imprecision modeling has been tackled in two ways: a classical probability approach and an interval-based one. Both approaches are illustrated by a numerical example, which shows that the tendencies obtained by the interval-based approach can be difficult to interpret for the decision maker, because of the growing uncertainty along the pipeline. In addition, the risk, which is taken into account through failure probability for some stages and which is strongly involved in the NPD process, must be an integral part of the modeling approach. The repetitive use of simulation with representative sampling turns out to be the most efficient strategy.
ISSN:0888-5885
1520-5045
DOI:10.1021/ie200406s