Robust Market Launch Planning for a Multi- Echelon Pharmaceutical Supply Chain

Klaus Reinholdt Nyhuus Hansen; Martin Grunow; Rafiqul Gani

doi:10.1016/B978-0-444-53711-9.50187-5

Robust Market Launch Planning for a Multi- Echelon Pharmaceutical Supply Chain

Klaus Reinholdt Nyhuus Hansen, Martin Grunow, Rafiqul Gani

Department of Chemical and Biochemical Engineering

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

It is well known, that the pharmaceutical industry is struggling with increasing cost and length of R&D projects. Earnings of a drug drop drastically after patent expiration. Thus, the industry spends much effort on reducing Time-to-Market. In the literature, little attention is given to drug launching activities after the drug has been approved. In this paper, we present a recourse-based stochastic model, which allows for time phasing the market entries to balance the fluctuating demand with the fixed and periodic production of the active pharmaceutical ingredient. The two major risk elements during launch are forecasting inaccuracy and the risk of a required label change from local regulatory authorities. Robust solutions are found by implementing the Robust Optimization framework.

Original language	English
Title of host publication	21st European Symposium on Computer Aided Process Engineering
Number of pages	2029
Volume	1
Publisher	Elsevier
Publication date	2011
Pages	935-939
ISBN (Print)	978-0-444-53895-6
DOIs	https://doi.org/10.1016/B978-0-444-53711-9.50187-5
Publication status	Published - 2011
Event	21st European Symposium on Computer Aided Process Engineering - Chalkidiki, Greece Duration: 29 May 2011 → 1 Jun 2011 http://www.escape-21.gr/

Conference

Conference	21st European Symposium on Computer Aided Process Engineering
Country/Territory	Greece
City	Chalkidiki
Period	29/05/2011 → 01/06/2011
Internet address	http://www.escape-21.gr/

Series	Computer Aided Chemical Engineering
Number	29
ISSN	1570-7946

Keywords

Market Launch Planning
Multi-Echelon Pharmaceutical Supply Chain
Robustness Optimization
Recourse-based stochastic programming

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10.1016/B978-0-444-53711-9.50187-5

Robust Market Launch Planning for a Multi-Echelon Pharmaceutical Supply Chain

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title = "Robust Market Launch Planning for a Multi- Echelon Pharmaceutical Supply Chain",

abstract = "It is well known, that the pharmaceutical industry is struggling with increasing cost and length of R&D projects. Earnings of a drug drop drastically after patent expiration. Thus, the industry spends much effort on reducing Time-to-Market. In the literature, little attention is given to drug launching activities after the drug has been approved. In this paper, we present a recourse-based stochastic model, which allows for time phasing the market entries to balance the fluctuating demand with the fixed and periodic production of the active pharmaceutical ingredient. The two major risk elements during launch are forecasting inaccuracy and the risk of a required label change from local regulatory authorities. Robust solutions are found by implementing the Robust Optimization framework.",

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Hansen, KRN, Grunow, M & Gani, R 2011, Robust Market Launch Planning for a Multi- Echelon Pharmaceutical Supply Chain. in 21st European Symposium on Computer Aided Process Engineering. vol. 1, Elsevier, Computer Aided Chemical Engineering, no. 29, pp. 935-939, 21st European Symposium on Computer Aided Process Engineering, Chalkidiki, Greece, 29/05/2011. https://doi.org/10.1016/B978-0-444-53711-9.50187-5

Robust Market Launch Planning for a Multi- Echelon Pharmaceutical Supply Chain. / Hansen, Klaus Reinholdt Nyhuus; Grunow, Martin; Gani, Rafiqul.
21st European Symposium on Computer Aided Process Engineering. Vol. 1 Elsevier, 2011. p. 935-939 (Computer Aided Chemical Engineering; No. 29).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Robust Market Launch Planning for a Multi- Echelon Pharmaceutical Supply Chain

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