Skip to main content

Advertisement

Log in

Systematic Framework for Design of Environmentally Sustainable Pharmaceutical Supply Chain Network

  • Original Article
  • Published:
Journal of Pharmaceutical Innovation Aims and scope Submit manuscript

Abstract

Purpose

The current push towards sustainability has pressurized pharmaceutical companies to reduce greenhouse gas (GHG) emissions in their manufacturing supply chains (SCs). However, the heavily regulated nature of the pharmaceutical industry has necessitated decisions such as sourcing of raw materials including names and addresses of suppliers and siting of plants to be locked early during the registration of a new drug. This could result in SC inefficiencies during the drug commercial life leading to higher than necessary GHG emissions. This paper presents a systematic framework for design of a more sustainable pharmaceutical SC network at the commercial stage that can be performed during the early stages of drug development.

Methods

The framework comprises the following steps. First, basic SC information including process chemistries, outsourcing strategies, and potential supplier and manufacturer sites is consolidated. Next, an analytic hierarchy process (AHP) is performed to identify the most suitable supplier and manufacturer sites followed by mapping the entire SC network by connecting all the sites that have been identified as high priority. Subsequently, a set of indicator metrics—namely, cost, lead time, and GHG emissions—is calculated to evaluate the economic and environmental performances of the network.

Results

The framework has been applied to an industrially motivated case study. Two network alternatives were proposed and analyzed based on their metrics together with synergies and trade-offs highlighted.

Conclusions

The findings demonstrate the efficacy of the framework in generating different network alternatives and identifying the most sustainable one on the basis of economic and environmental benefits. As such, the framework is applicable to the early stages of drug development where information is very limited.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. World Commission on Environment and Development. Our common future. Oxford: Oxford University Press; 1987.

    Google Scholar 

  2. Lowell Center for Sustainable Production. What is sustainable production?. 2016. http://www.sustainableproduction.org/abou.what.php. Accessed 21 March 2016.

  3. Banini S. The business of sustainability. 2012. http://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/sustainability/pdfs/mck%20on%20srp/srp_11_biz%20sustainability.ashx. Accessed 21 March 2016.

  4. Adhitya A, Halim I, Srinivasan R. Decision support for green supply chain operations by integrating dynamic simulation and LCA indicators: diaper case study. Environ Sci Technol. 2011;45:10178–85.

    Article  CAS  PubMed  Google Scholar 

  5. GlaxoSmithKline. Our planet, our commitments. 2016. http://www.gsk.com/en-gb/responsibility/our-planet/our-commitments/. Accessed 21 March 2016.

  6. Pfizer. Pfizer annual review 2013. 2014. http://www.pfizer.com/files/investors/financial_reports/annual_reports/2013/assets/pdfs/pfizer_13ar_responsible_business.pdf. Accessed 21 March 2016.

  7. Rees H. Supply chain management in the drug industry: delivering patient value for pharmaceuticals and biologics. Hoboken: John Wiley & Sons, Inc.; 2011.

    Book  Google Scholar 

  8. Sousa RT, Liu S, Papageorgiou LG, Shah N. Global supply chain planning for pharmaceuticals. Chem Eng Res Des. 2011;89(11):2396–409.

    Article  CAS  Google Scholar 

  9. Niziolek L, Chiam TC, Yih Y. A simulation-based study of distribution strategies for pharmaceutical supply chains. IIE Trans Healthcare Syst Eng. 2012;2(3):181–9.

    Article  Google Scholar 

  10. Uthayakumar R, Priyan S. Pharmaceutical supply chain and inventory management strategies: optimization for a pharmaceutical company and a hospital. Oper Res Health Care. 2013;2:52–64.

    Article  Google Scholar 

  11. Staudacher AP, Bush A. Analyzing the impact of lean approach in pharmaceutical supply chain. In: Matta A, Li J, Sahin E, Lanzarone E, Fowler J, editors. Springer Proceedings in Mathematics & Statistics: Proceedings of the International Conference on Health Care Systems Engineering. London: Springer; 2014. p. 253–65.

    Chapter  Google Scholar 

  12. Kirytopoulos K, Leopoulos V, Voulgaridou D. Supplier selection in pharmaceutical industry, an analytic network process approach. Benchmark: Int J. 2008;15(4):494–516.

    Article  Google Scholar 

  13. Enyinda CI, Dunu E, Bell-Hanyes J. A model for quantifying strategic supplier selection: evidence from a generic pharmaceutical firm supply chain. Int J Bus, Market Decis Sci. 2010;3(2):25–44.

    Google Scholar 

  14. Zhang M, Pawar KS, Shah J, Mehta P. Evaluating outsourcing partners’ capability: a case study from the pharmaceutical supply chain. J Manuf Technol Manag. 2013;24(8):1080–101.

    Article  Google Scholar 

  15. Nagurney A, Li D, Nagurney LS. Pharmaceutical supply chain networks with outsourcing under price and quality competition. Int Trans Oper Res. 2013;20:859–88.

    Google Scholar 

  16. Chatterjee B. Case study: applying a risk-based decision making framework for outsourcing. Pharm Eng. 2014;34:1–6.

    Google Scholar 

  17. Srinivasan R, Venkatasubramanian V. Automating HAZOP analysis of batch chemical plants: part I. The knowledge representation framework. Comput Chem Eng. 1998;22(9):1345–55.

    Article  CAS  Google Scholar 

  18. Srinivasan R, Venkatasubramanian V. Automating HAZOP analysis of batch chemical plants: part II. Algorithms and application. Comput Chem Eng. 1998;22(9):1357–70.

    Article  CAS  Google Scholar 

  19. Mahulkar AV, Gogate PR, Pandit AB. Matching chemistry with chemical engineering for optimum design and performance of pharmaceutical processing. In: Shioiri T, Izawa K, Konoike T, editors. Pharmaceutical process chemistry. Weinheim: Wiley; 2011. p. 443–67.

    Google Scholar 

  20. Zhang J. New global pharmaceutical outsourcing trends. In: Pharmaceutical Online. 2011. http://www.pharmaceuticalonline.com/doc/new-global-pharmaceutical-outsourcing-trends-0001. Accessed 21 March 2016.

  21. Boom M. Outsourcing in the pharmaceuticals sector: the pros and cons. 2015. http://www.sourcingfocus.com/site/opinionscomments/outsourcing_in_the_pharmaceuticals_sector_the_pros_and_cons/. Accessed 21 March 2016.

  22. Ehrhardt M, Hutchens R, Higgins S. Five steps toward a revitalized pharmaceutical supply chain. 2012. http://www.strategy-business.com/article/00094?gko=982c0. Accessed 21 March 2016.

  23. Boulaksil Y, Fransoo JC. Strategic and operational outsourcing—decisions in the pharmaceutical industry. 2008. http://cms.ieis.tue.nl/Beta/Files/WorkingPapers/Beta_wp242.pdf. Accessed 21 March 2016.

  24. Kuhrt K. The pharmaceutical supply chain. 2012. http://www.chemanager-online.com/en/topics/chemicals-distribution/pharmaceutical-supply-chain. Accessed 21 March 2016.

  25. The Guardian. What are CO2e and global warming potential (GWP)? 2011. http://www.theguardian.com/environment/2011/apr/27/co2e-global-warming-potential. Accessed 21 March 2016.

  26. EcoDesk. GSK case study: embedding sustainability into the business with Ecodesk. 2014. https://www.ecodesk.com/media/blog/2014/09/30/gsk-case-study-embedding-sustainability-into-the-business-with-ecodesk/. Accessed 21 March 2016.

  27. Google Maps. https://www.google.com.sg/maps. Accessed 21 March 2016.

  28. Lamberti MJ, Costello M, Getz K. Trends and novel approaches to clinical supply outsourcing. 2012. http://www.contractpharma.com/issues/2012-01/view_features/trends-and-novel-approaches-to-clinical-supply-outsourcing. Accessed 21 March 2016.

  29. Saaty TL. The analytic hierarchy process. New York: McGraw Hill International; 1980.

    Google Scholar 

  30. Bhushan N, Rai K. Strategic decision making: applying the analytic hierarachy process. London: Springer-Verlag; 2004.

    Google Scholar 

  31. Wang X, Triantaphyllou E. Ranking irregularities when evaluating alternatives by using some multi-criteria decision analysis methods. In: Badiru AB, editor. Handbook of industrial and systems engineering. Boca Raton: CRC Press; 2005. p. 27.1–27.12.

    Google Scholar 

  32. Gould AL, Krishna R, Khan A, Saltzman J. Incorporating preclinical and clinical knowledge and experience to evaluate drug development projects using the analytic hierarchy process. 2014. http://www.isahp.org/uploads/p739851.pdf. Accessed 21 March 2016.

  33. Rothman CJ. Objective assessment of manufacturing technology investments. Cambridge: Massachusetts Institute of Technology; 2012.

    Google Scholar 

  34. Hernández CT, Marins FAS, Rocha PMD, Duran JAR. Using AHP and ANP to evaluate the relation between reverse logistics and corporate performance in brazilian industry. Braz J Oper Prod Manag. 2010;7(2):47–62.

    Google Scholar 

  35. Shanley A. 2014 Outsourcing Survey: Contract Pharma. 2014. http://beta.rodpub.com/uploads/OutsourcingSurvey0514.pdf. Accessed 21 March 2016

  36. Levy SG. Effective outsourcing of small molecule chemistry R&D and API manufacturing for emerging pharmaceutical companies—a stepwise approach to risk management. Pharmaceutial Outsourcing. 2014. http://www.pharmoutsourcing.com/Featured-Articles/153810-Effective-Outsourcing-of-Small-Molecule-Chemistry-R-D-and-API-Manufacturing-for-Emerging-Pharmaceutical-Companies-A-Stepwise-Approach-to-Risk-Management/. Accessed 21 March 2016.

  37. Parry M. Selecting a contract manufacturer, choosing a supplier that will satisfy your expectations. Contract Pharma. 2008. http://www.contractpharma.com/issues/2008-09/view_features/selecting-a-contract-manufacturer/. Accessed 21 March 2016.

  38. Connell B. Pharma manufacturing on the move. 2012. http://www.pharmamanufacturing.com/articles/2012/091/. Accessed 21 March 2016.

  39. Bello MJS. A case study approach to the supplier selection process. Puerto Rico: University of Puerto Rico; 2003.

    Google Scholar 

  40. Adamcsek E. The analytic hierarchy process and its generalizations. Budapest: Eotvos Lorand University; 2008.

    Google Scholar 

  41. Verisk Maplecroft. Environmental risk analytics. 2016. https://www.maplecroft.com/themes/cc/. Accessed 21 March 2016.

  42. World Resources Institute. Measuring, mapping and understanding water risks around the globe. 2016. http://www.wri.org/our-work/project/aqueduct. Accessed 21 March 2016.

  43. World Wide Fund for Nature. The water risk filter. 2016. http://waterriskfilter.panda.org/. Accessed 21 March 2016.

  44. Saaty TL, Vargas LG. Comparison of eigenvalue, logarithmic least squares and least squares methods in estimating ratios. Math Model. 1984;5:309–24.

    Article  Google Scholar 

  45. Mocenni C. The analytic hierarchy process. 2014. http://www.dii.unisi.it/~mocenni/Note_AHP.pdf. Accessed 21 March 2016.

  46. Shapiro JF. Modeling the supply chain. Pacific Grove: Duxbury Press; 2001.

    Google Scholar 

  47. United States Department of Transportation. Table 3–21: average freight revenue per ton-mile. 2015. http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_03_21.html. Accessed 21 March 2016.

  48. PE International. GaBi 5: Software system and databases for life cycle engineering. 2011.

  49. van Elzakker MAH , Maia LKK, Zondervan E, Raikar NB, Hoogland H, Grossmann IE. Considering both environmental impact and economic costs in the optimization of the tactical planning for the fast moving consumer goods industry. 2014. http://repository.cmu.edu/cgi/viewcontent.cgi?article=1265&context=cheme. Accessed 20 April 2016.

Download references

Acknowledgments

The authors would like to thank GSK-EDB Trust Fund for financial support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Iskandar Halim.

Additional information

Highlights

• Supply chain design framework during early stages of drug development.

• AHP technique for sites selection and network mapping.

• Compare networks in terms of cost, lead time, and carbon footprint.

Summary

The issue of supply chain (SC) sustainability has become an important business factor for today’s pharmaceutical companies. This paper proposes a framework for design of a more sustainable pharmaceutical SC that can be performed at the early stages of drug development. The framework has been developed by integrating different methodologies—analytic hierarchy process for identifying the most suitable supplier and manufacturer sites, SC network mapping, and indicator metrics calculation—to evaluate both the economic and environmental impacts of different SC configurations. The application and benefits of the proposed framework are demonstrated using an industrially motivated study.

Electronic Supplementary Material

ESM 1

(DOCX 47 kb)

ESM 2

(DOCX 47 kb)

ESM 3

(DOCX 41 kb)

ESM 4

(DOCX 41 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Low, Y.S., Halim, I., Adhitya, A. et al. Systematic Framework for Design of Environmentally Sustainable Pharmaceutical Supply Chain Network. J Pharm Innov 11, 250–263 (2016). https://doi.org/10.1007/s12247-016-9255-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12247-016-9255-8

Keywords

Navigation