IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v66y2018i1p18-41.html
   My bibliography  Save this article

Performance Guarantees and Optimal Purification Decisions for Engineered Proteins

Author

Listed:
  • Tugce Martagan

    (School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, 5612 AZ Netherlands)

  • Ananth Krishnamurthy

    (Department of Industrial and Systems Engineering, University of Wisconsin Madison, Madison, Wisconsin 53706)

  • Peter A. Leland

    (Aldevron, Madison, Wisconsin 53719)

  • Christos T. Maravelias

    (Department of Chemical and Biological Engineering, University of Wisconsin Madison, Madison, Wisconsin 53706)

Abstract

We investigate protein purification operations conducted by biomanufacturers and pharmaceutical companies as part of their research and development efforts. Purification of these proteins involves unique challenges such as balancing the yield and purity trade-offs, dealing with uncertainty in the starting material, and estimating the impact of several interlinked decisions. We develop a Markov decision model and partition the state space into decision zones that provide managerial insights to optimize purification operations. We develop practical guidelines to quantify financial risks, and we characterize the optimal operating decisions based on specific production requirements. The optimization framework has been implemented at Aldevron, a contract biomanufacturer specializing in proteins, and has resulted in 25% reduction in the total lead times and 20% reduction in the costs of protein purification operations on average.

Suggested Citation

  • Tugce Martagan & Ananth Krishnamurthy & Peter A. Leland & Christos T. Maravelias, 2018. "Performance Guarantees and Optimal Purification Decisions for Engineered Proteins," Operations Research, INFORMS, vol. 66(1), pages 18-41, 1-2.
    • Handle: RePEc:inm:oropre:v:66:y:2018:i:1:p:18-41
    DOI: 10.1287/opre.2017.1661
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/opre.2017.1661
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.2017.1661?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
    ---><---

    References listed on IDEAS

    as
    1. Tugce Martagan & Ananth Krishnamurthy & Christos T. Maravelias, 2016. "Optimal condition-based harvesting policies for biomanufacturing operations with failure risks," IISE Transactions, Taylor & Francis Journals, vol. 48(5), pages 440-461, May.
    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. Hua Zheng & Wei Xie & Ilya O. Ryzhov & Dongming Xie, 2023. "Policy Optimization in Dynamic Bayesian Network Hybrid Models of Biomanufacturing Processes," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 66-82, January.
    2. Tugce Martagan & Ananth Krishnamurthy & Peter A. Leland, 2020. "Managing Trade-offs in Protein Manufacturing: How Much to Waste?," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 330-345, March.
    3. Tugce Martagan & Ivo Adan & Marc Baaijens & Coen Dirckx & Oscar Repping & Bram van Ravenstein & PK Yegneswaran, 2023. "Merck Animal Health Uses Operations Research Methods to Transform Biomanufacturing Productivity for Lifesaving Medicines," Interfaces, INFORMS, vol. 53(1), pages 85-95, January.
    4. Tugce Martagan & Yasemin Limon & Ananth Krishnamurthy & Tom Foti & Peter Leland, 2019. "Aldevron Accelerates Growth Using Operations Research in Biomanufacturing," Interfaces, INFORMS, vol. 49(2), pages 137-153, March.
    5. Stockinger, Quirin, 2020. "Stochastic Optimization of Bioreactor Control Policies Using a Markov Decision Process Model," Junior Management Science (JUMS), Junior Management Science e. V., vol. 5(1), pages 50-80.
    6. Boute, Robert N. & Gijsbrechts, Joren & van Jaarsveld, Willem & Vanvuchelen, Nathalie, 2022. "Deep reinforcement learning for inventory control: A roadmap," European Journal of Operational Research, Elsevier, vol. 298(2), pages 401-412.

    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. Tugce Martagan & Ananth Krishnamurthy & Peter A. Leland, 2020. "Managing Trade-offs in Protein Manufacturing: How Much to Waste?," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 330-345, March.
    2. Hua Zheng & Wei Xie & Ilya O. Ryzhov & Dongming Xie, 2023. "Policy Optimization in Dynamic Bayesian Network Hybrid Models of Biomanufacturing Processes," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 66-82, January.
    3. Stockinger, Quirin, 2020. "Stochastic Optimization of Bioreactor Control Policies Using a Markov Decision Process Model," Junior Management Science (JUMS), Junior Management Science e. V., vol. 5(1), pages 50-80.
    4. Mabel C. Chou & Mahmut Parlar & Yun Zhou, 2017. "Optimal Timing to Initiate Medical Treatment for a Disease Evolving as a Semi-Markov Process," Journal of Optimization Theory and Applications, Springer, vol. 175(1), pages 194-217, October.

    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:inm:oropre:v:66:y:2018:i:1:p:18-41. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.