IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v161y2015icp129-139.html
   My bibliography  Save this article

Planning operations before market launch for balancing time-to-market and risks in pharmaceutical supply chains

Author

Listed:
  • Hansen, Klaus Reinholdt Nyhuus
  • Grunow, Martin

Abstract

Shorter product life cycles and the resulting increase in new product introductions boost the importance of product launch operations. In the pharmaceutical sector, product launch operations are of particular importance, as companies seek to reduce time-to-market to better exploit patent protection. Large volumes of product need to be ready to fill the downstream supply chain immediately at market launch. Building up the required inventory is, however, connected to several risks. In addition to the risk associated with the lack of demand information for a new product, there are several risks unique to the pharmaceutical sector. After approval by central authorities such as the FDA or EMA, a new drug still needs to receive market authorization, which is in most cases granted by some local authorities – in Europe, for example, by more than 30 national and regional bodies. The duration of these different market authorization processes as well as their outcomes (e.g. price and reimbursement levels, requirements of label or leaflet changes) are highly uncertain. We develop a two-stage stochastic model to support market launch preparation decisions. It trades off the costs of accepting these risks, for example by risk packaging before authorization, against the lost revenue caused by risk-averse operations. The model is applied to a case based on an empirical study. Our approach results in significant savings compared to current practices. We hereby provide an example of how quantitative methodology can provide valuable decision support for product launch operations, even when complex regulatory affairs need to be considered.

Suggested Citation

  • Hansen, Klaus Reinholdt Nyhuus & Grunow, Martin, 2015. "Planning operations before market launch for balancing time-to-market and risks in pharmaceutical supply chains," International Journal of Production Economics, Elsevier, vol. 161(C), pages 129-139.
  • Handle: RePEc:eee:proeco:v:161:y:2015:i:c:p:129-139
    DOI: 10.1016/j.ijpe.2014.10.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527314003247
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2014.10.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Patricia M. Danzon & Y. Richard Wang & Liang Wang, 2005. "The impact of price regulation on the launch delay of new drugs—evidence from twenty‐five major markets in the 1990s," Health Economics, John Wiley & Sons, Ltd., vol. 14(3), pages 269-292, March.
    2. Klaus R.N. Hansen & Martin Grunow, 2015. "Modelling ramp-up curves to reflect learning: improving capacity planning in secondary pharmaceutical production," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5399-5417, September.
    3. Sunil Kumar & Jayashankar M. Swaminathan, 2003. "Diffusion of Innovations Under Supply Constraints," Operations Research, INFORMS, vol. 51(6), pages 866-879, December.
    4. Teck-Hua Ho & Sergei Savin & Christian Terwiesch, 2002. "Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint," Management Science, INFORMS, vol. 48(2), pages 187-206, February.
    5. Hahn, G.J. & Kuhn, H., 2012. "Simultaneous investment, operations, and financial planning in supply chains: A value-based optimization approach," International Journal of Production Economics, Elsevier, vol. 140(2), pages 559-569.
    6. Bauer, Hans H. & Fischer, Marc, 2000. "Product life cycle patterns for pharmaceuticals and their impact on R&D profitability of late mover products," International Business Review, Elsevier, vol. 9(6), pages 703-725, December.
    7. Scott B. Cantor, 2004. "Clinical Applications in the Decision Analysis Literature," Decision Analysis, INFORMS, vol. 1(1), pages 23-25, March.
    8. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    9. Boulaksil, Y. & Grunow, M. & Fransoo, J.C., 2011. "Capacity flexibility allocation in an outsourced supply chain with reservation," International Journal of Production Economics, Elsevier, vol. 129(1), pages 111-118, January.
    10. Jeffrey S. Stonebraker & Donald L. Keefer, 2009. "OR Practice---Modeling Potential Demand for Supply-Constrained Drugs: A New Hemophilia Drug at Bayer Biological Products," Operations Research, INFORMS, vol. 57(1), pages 19-31, February.
    11. Garattini, Livio & Cornago, Dante & De Compadri, Paola, 2007. "Pricing and reimbursement of in-patent drugs in seven European countries: A comparative analysis," Health Policy, Elsevier, vol. 82(3), pages 330-339, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Imran & Muhammad Salman Habib & Amjad Hussain & Naveed Ahmed & Abdulrahman M. Al-Ahmari, 2020. "Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty," Mathematics, MDPI, vol. 8(3), pages 1-29, March.
    2. Brandenburg, Marcus, 2017. "A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects," Omega, Elsevier, vol. 70(C), pages 58-76.
    3. Blossey, Gregor & Hahn, Gerd J. & Koberstein, Achim, 2022. "Planning pharmaceutical manufacturing networks in the light of uncertain production approval times," International Journal of Production Economics, Elsevier, vol. 244(C).
    4. Zahiri, Behzad & Zhuang, Jun & Mohammadi, Mehrdad, 2017. "Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 109-142.
    5. Settanni, Ettore & Thenent, Nils Elias & Newnes, Linda B. & Parry, Glenn & Goh, Yee Mey, 2017. "Mapping a product-service-system delivering defence avionics availability," International Journal of Production Economics, Elsevier, vol. 186(C), pages 21-32.
    6. Farazi, Mohammad Saleh & Chiambaretto, Paul & Fernandez, Anne-Sophie & Gopalakrishnan, Shanthi, 2024. "Unbundling the impact of current and future competition on cooperation in coopetition projects for innovation," Research Policy, Elsevier, vol. 53(6).
    7. Brandão, Luiz E. & Fernandes, Gláucia & Dyer, James S., 2018. "Valuing multistage investment projects in the pharmaceutical industry," European Journal of Operational Research, Elsevier, vol. 271(2), pages 720-732.
    8. Fatemeh Shekoohi Tolgari & Naeme Zarrinpoor, 2024. "A robust reverse pharmaceutical supply chain design considering perishability and sustainable development objectives," Annals of Operations Research, Springer, vol. 340(2), pages 981-1033, September.
    9. Shabnam Rekabi & Ali Ghodratnama & Amir Azaron, 2022. "Designing pharmaceutical supply chain networks with perishable items considering congestion," Operational Research, Springer, vol. 22(4), pages 4159-4219, September.
    10. Carlos Franco & Edgar Alfonso-Lizarazo, 2017. "A Structured Review of Quantitative Models of the Pharmaceutical Supply Chain," Complexity, Hindawi, vol. 2017, pages 1-13, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    2. Kartik Hosanagar & Peng Han & Yong Tan, 2010. "Diffusion Models for Peer-to-Peer (P2P) Media Distribution: On the Impact of Decentralized, Constrained Supply," Information Systems Research, INFORMS, vol. 21(2), pages 271-287, June.
    3. Amini, Mehdi & Li, Haitao, 2011. "Supply chain configuration for diffusion of new products: An integrated optimization approach," Omega, Elsevier, vol. 39(3), pages 313-322, June.
    4. Rachel Lacroix & Anna Timonina-Farkas & Ralf W. Seifert, 2023. "Utilizing additive manufacturing and mass customization under capacity constraints," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 281-301, January.
    5. Ashkan Negahban & Jeffrey S. Smith, 2018. "A joint analysis of production and seeding strategies for new products: an agent-based simulation approach," Annals of Operations Research, Springer, vol. 268(1), pages 41-62, September.
    6. Wenjing Shen & Izak Duenyas & Roman Kapuscinski, 2014. "Optimal Pricing, Production, and Inventory for New Product Diffusion Under Supply Constraints," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 28-45, February.
    7. Bin Hu & Zhankun Sun, 2022. "Managing Self-Replicating Innovative Goods," Management Science, INFORMS, vol. 68(1), pages 399-419, January.
    8. Eryn Juan He & Joel Goh, 2022. "Profit or Growth? Dynamic Order Allocation in a Hybrid Workforce," Management Science, INFORMS, vol. 68(8), pages 5891-5906, August.
    9. Ivan Diaz-Rainey & Dionisia Tzavara, 2011. "Financing Renewable Energy through Household Adoption of Green Electricity Tariffs: A Diffusion Model of an Induced Environmental Market," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2011-03, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    10. Bayrak, Busra & Guray, Busra & Uzunlar, Nilsu & Nadar, Emre, 2024. "Diffusion control in closed-loop supply chains: Successive product generations," International Journal of Production Economics, Elsevier, vol. 268(C).
    11. Apurva Jain & Swapnil Rayal, 2023. "Managing medical equipment capacity with early spread of infection in a region," Production and Operations Management, Production and Operations Management Society, vol. 32(5), pages 1415-1432, May.
    12. Yan, Xiaoming & Liu, Ke, 2009. "Optimal control problems for a new product with word-of-mouth," International Journal of Production Economics, Elsevier, vol. 119(2), pages 402-414, June.
    13. A. Negahban & J.S. Smith, 2016. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3852-3869, July.
    14. Vahideh Manshadi & Sidhant Misra & Scott Rodilitz, 2020. "Diffusion in Random Networks: Impact of Degree Distribution," Operations Research, INFORMS, vol. 68(6), pages 1722-1741, November.
    15. Yunke Mai & Bin Hu, 2023. "Optimizing Free-to-Play Multiplayer Games with Premium Subscription," Management Science, INFORMS, vol. 69(6), pages 3437-3456, June.
    16. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    17. Wenjing Shen & Izak Duenyas & Roman Kapuscinski, 2011. "New Product Diffusion Decisions Under Supply Constraints," Management Science, INFORMS, vol. 57(10), pages 1802-1810, October.
    18. Hongmin Li & Dieter Armbruster & Karl G. Kempf, 2013. "A Population-Growth Model for Multiple Generations of Technology Products," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 343-360, July.
    19. Il-Horn Hann & JooHee Oh, 2017. "Combating Prerelease Piracy: Modeling the Effects of Antipiracy Measures in P2P Networks," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 92-107, February.
    20. Shun-Chen Niu, 2006. "A Piecewise-Diffusion Model of New-Product Demands," Operations Research, INFORMS, vol. 54(4), pages 678-695, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:161:y:2015:i:c:p:129-139. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.