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System Dynamics Model for an Agile Pharmaceutical Supply Chain During COVID‑19 Pandemic in Iran

Mohammad Hamzehlou 

Abstract

Unpredictable changes in the current business environment have made organizations pay attention to the concept of agility. This concept is a key feature to survive and compete in turbulent markets while considering customers’ fluctuating needs. An organization’s agility is a function of its supply chain’s agility. The present study offers a System Dynamics (SD) model for Iran’s Pharmaceutical Supply Chain (PSC). The model is presented in three steps. First, the Supply Chain (SC) indicators were extracted based on theoretical foundations and literature review results. Second, an SD model of the PSC was extracted in the context of the COVID‑19 pandemic with the necessary analyses. Finally, the desired outputs and strategies were obtained by conducting a case study. The results indicated that the PSC’s highest agility could be guaranteed by the simultaneous implementation of three strategies: investment, Human Capital Development (HCD), and accelerated completion of ongoing projects on a priority basis. According to these results, the organization had better determine the amount of capital and workforce required for ongoing projects, then design funding solutions to implement these projects and implement them according to the projects’ priority.

Introduction

Nowadays, competition is essential in developing industries [1, 2]. Due to the intense competitiveness in the pharmaceutical industries, governments try to balance competition and economic growth [3, 4]. The high and continuously increasing drug costs are global concerns that require a PSC management system to manage [5, 6]. The supply, storage, and distribution of drugs are critical issues as most healthcare service receivers are outlying rural areas deprived of medical services due to large distances and extra. Thus, many of the population no longer needs to unreasonably visit specialized centers. Interruptions in supply chains can occur due to natural catastrophes or failures. In the same aspect, numerous outbreaks of very contagious diseases such as the COVID‑19 have caused a global catastrophe for humans and economies [11, 12]. The pandemic has greatly affected activities such as SC, manufacturing operations, logistics, and several other sectors [13–15]. Consequently, the epidemic has nevertheless affected the global economy. Many countries have decided to execute a complete lockdown to control the spreading of the infection. Moreover, various governments have invested many resources to stop and control the spread of the coronavirus. However, the transmission of the coronavirus has made the struggles of the governments almost ineffective. While the authorities have attempted to contain the coronavirus outbreak, various organizations have also cooperated in this matter. 

Materials and methods

System dynamics is the method utilized in this study to analyze and manage complicated feedback systems, such as those seen in the world of business and other social systems. This technique may be used to many different types of input [75]. The dynamics of the system cannot be utilized to investigate any system since feedback is the key characteristic of a system that has been studied in this way. Creating feedback loops provides information on a strategy’s performance and potential consequences in the system dynamics method [76, 77]. The conclusion drawn from the causal loop diagram’s positive and negative loops is that changes in one element in a cycle may be identified as having an impact on another factor, leading to a greater knowledge of the system’s performance and feedback. The outcomes of policy implementation in the future on the indicators are examined, and changes are assessed, once the model is complete, the conditions of a policy are applied, and the policy is put into effect [78, 79].

Results

This section contains three subsections related to the simulation results. 1) scenario making, 2) policies, and 3) analyzing scenarios and policies are presented in this section:

4.1. Scenario making
After analyzing different variables and their impact on the desired periods’ main variable, significant and decisive indicators on creating an agile SC in the Iran Pharmaceutical Group have been identified. The decision-maker enables us to choose different policies that include indicators to achieve effective strategies that affect the country’s future (3 defined scenarios). In this research, three scenarios have been considered and implemented for each stock variable. One of the possible conditions for significant indicators is considered using the opinion of the experts. Accordingly, Fig 12(A)–12(D) shows the model’s status at the time of these scenarios. 

Conclusions

The dynamic nature of a modern SCN has led to a great deal of uncertainty in many network parameters. Ignoring such uncertainties may pose several threats to the entire SCN. Organizations should carefully plan to control uncertainty to overcome these risks. An organization will face significant consequences if it fails to meet customer demand. These issues include declined customer satisfaction, pessimism, inflation, and higher lead time. Hence, an SCN must be designed and planned to maintain its agility against any disruption. Moreover, the PSC is considered a major national category due to the pharmaceutical industry’s role in macroeconomic variables (e.g., employment, economic growth, and non-oil exports). Most SCs are threatened by a variety of risks, leading to disruption. This issue is of specific sensitivity in supplying drugs. This study considered the risk of sanctions and an immediate increase in demand for COVID-19 as possible scenarios in the next five years. Section 4 shows that SC agility will decrease over time if these scenarios occur and there are no new policies, and the status quo is maintained. According to different policies, implementing policy 4, apart from maintaining agility, will ensure the highest SC agility level (33%) and lead to an agile system. These results show that to maintain and achieve the highest level of SC agility. The best decision is to simultaneously implement four policies: increasing cooperation and intra-group partnerships, investment, HCD, and accelerating ongoing projects based on organizational priorities. 

Acknowledgments

The author has done all the parts of this paper alone and has used the opinions of experts only in parts of the paper that are referred to in the text of the manuscript. Also, the author sincerely thanks the opinions of all the people who help in improving this scientific work.

Citation: Hamzehlou M (2024) System dynamics model for an agile pharmaceutical supply chain during COVID‑19 pandemic in Iran. PLoS ONE 19(1): e0290789. https://doi.org/10.1371/journal.pone.0290789

Editor: Saad Ahmed Javed, Nanjing University of Information Science and Technology, CHINA

Received: February 9, 2023; Accepted: August 15, 2023; Published: January 11, 2024

Copyright: © 2024 Mohammad Hamzehlou. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and Supporting Information files.

Competing interests: The authors have declared that no competing interests exist.

 

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0290789#abstract0

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