Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

Operations Research Improves Biomanufacturing Efficiency at MSD Animal Health

Published: 01 March 2021 Publication History

Abstract

Biomanufacturing methods use living organisms (i.e., viruses and bacteria) to generate active ingredients, and this leads to challenges that are different from those incurred by other industries. For example, biomanufacturers often deal with high levels of uncertainty and batch-to-batch variability in production yield, lead times, and costs. Biosafety requirements impose constraints, such as a no-wait requirement throughout the production process. In addition, biomanufacturing operations are cost and labor intensive and involve high risks of failure. To address these challenges, a multidisciplinary team of researchers collaborated over three years to develop a portfolio of optimization models and decision support tools. These tools were aimed at improving biomanufacturing efficiency using a variety of operations research methodologies, including stochastic optimization, Bayesian design of experiments, and simulation optimization. The developed models link the underlying biology and chemistry of biomanufacturing processes with financial trade-offs and business risks. The research has been conducted in close collaboration with MSD Animal Health in Boxmeer, Netherlands. Industry implementation at MSD AH had a significant impact, with up to 50% increase in batch yield and an additional revenue of €50 million per year. The application of operations research is very new to the biomanufacturing industry. As more companies such as MSD AH embrace operations research, we believe that this will significantly help the industry provide faster and more affordable access to new treatments.

References

[1]
Doran PM (1995) Bioprocess Engineering Principles (Elsevier, Waltham, MA).
[2]
Food and Agriculture Organization of the United Nations (2018) Livestock production. Accessed June 20, 2019, http://www.fao.org/3/y4252e/y4252e07.htm.
[3]
Frazier PI (2014) Optimal learning: An overview. Accessed April 10, 2019, https://people.orie.cornell.edu/pfrazier/Presentations/2014.06.TsinghuaIE_GuestLecture.pdf.
[4]
Frazier PI (2018) A tutorial on Bayesian optimization. Preprint, submitted July 8, https://arxiv.org/abs/1807.02811.
[5]
Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2013) Bayesian Data Analysis (Chapman and Hall/CRC, Boca Raton, FL).
[6]
Grand View Research (2018) Animal health market size, share and trends analysis report. Accessed June 20, 2019, https://www.grandviewresearch.com/industry-analysis/animal-health-market.
[7]
Koca Y, Martagan T, Adan I, van Ravenstein B, Maillart L (2020) Optimal bleed-feed strategies in biomanufacturing. Working paper, Eindhoven University of Technology, Eindhoven, Netherlands.
[8]
Leachman RC, Johnston L, Li S, Shen ZJ (2014) An automated planning engine for biopharmaceutical production. Eur. J. Oper. Res. 238(1):327–338.
[9]
Limon Y, Krishnamurthy A (2020) Resource allocation strategies for protein purification operations. IISE Trans. 52(9):945–960.
[10]
Martagan T, Krishnamurthy A, Maravelias CT (2016) Optimal condition-based harvesting policies for biomanufacturing operations with failure risks. IIE Trans. 48(5):440–461.
[11]
McKinsey & Company (2014) Rapid growth in biopharma: Challenges and opportunities. Accessed June 22, 2019, https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/rapid-growth-in-biopharma.
[12]
Monod J (1949) The growth of bacterial cultures. Annual Rev. Microbiology 3(1):371–394.
[13]
MSD (2019) Operations research improves biomanufacturing efficiency. Accessed June 25, 2019, https://www.youtube.com/watch?v=79B7OBuvRkY&feature=youtu.be.
[14]
Murphy J (2012) Machine Learning: A Probabilistic Perspective (The MIT Press, Cambridge, MA).
[15]
Nederlandse Biotechnologische Vereniging (2018) Computers and bioprocess development. Accessed March 28, 2018, https://nbv.kncv.nl/en/activities/nbv-detail-page/411/computers-bioprocess-development/about.
[16]
Petrides D, Siletti C (2004) The role of process simulation and scheduling tools in the development and manufacturing of biopharmaceuticals. Ingalls RG, Rossetti MD, Smith JS, Peters BA, eds. Proc. 2004 Winter Simulation Conf. (Washington, DC), 2046–2051.
[17]
Powell WB (2010) The Knowledge Gradient for Optimal Learning. Accessed June 12, 2019, https://castlelab.princeton.edu/html/Papers/Powell-EORMS-OptimalLearningFebruary172010.pdf.
[18]
Powell WB, Ryzhov IO (2012) Optimal Learning , vol. 841 (John Wiley & Sons, Hoboken, NJ).
[19]
World Health Organization (2019) Neglected zoonotic diseases. Accessed June 12, 2019, https://www.who.int/neglected_diseases/diseases/zoonoses/en/.
[20]
Xie W, Wang B, Li C, Auclair J, Baker P (2020) Bayesian network based risk and sensitivity analysis for production process stability control. Preprint, submitted September 10, 2019, https://arxiv.org/abs/1909.04261.

Index Terms

  1. Operations Research Improves Biomanufacturing Efficiency at MSD Animal Health
      Index terms have been assigned to the content through auto-classification.

      Recommendations

      Comments

      Please enable JavaScript to view thecomments powered by Disqus.

      Information & Contributors

      Information

      Published In

      cover image Interfaces
      Interfaces  Volume 51, Issue 2
      March-April 2021
      77 pages
      ISSN:0092-2102
      EISSN:1526-551X
      DOI:10.1287/inte.2021.51.issue-2
      Issue’s Table of Contents

      Publisher

      INFORMS

      Linthicum, MD, United States

      Publication History

      Published: 01 March 2021
      Accepted: 26 June 2020
      Received: 31 December 2019

      Author Tags

      1. biomanufacturing
      2. fermentation
      3. optimization
      4. simulation
      5. renewal theory
      6. cost reduction

      Qualifiers

      • Research-article

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • 0
        Total Citations
      • 0
        Total Downloads
      • Downloads (Last 12 months)0
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 14 Nov 2024

      Other Metrics

      Citations

      View Options

      View options

      Get Access

      Login options

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media