Elucidating Production Bottlenecks in the Indian Pharmaceutical Industry for Enhanced Pandemic Preparedness Using a Combined Theory of Constraints and Six Sigma Approach

ABSTRACT

Aim/Background: Early in the COVID-19 epidemic, the dire need for effective and readily available outpatient therapies became apparent as healthcare systems worldwide faced unprecedented strain. This study addressed the initial focus on medications with anecdotal evidence against COVID-19 and the emergence of Hydroxychloroquine (HCQ) as a potential therapeutic option due to its demonstrated in vitro activity and established safety record in treating autoimmune conditions. However, the surge in prescriptions and panic buying led to a significant imbalance in the supply and demand for HCQ, affecting pharmaceutical companies. Focusing on the Pharmaceutical Supply Chain (PSC), the primary objective was to present a new methodology for investigating production processes to identify potential improvements and mitigate the impact of bottlenecks on productivity. Materials and Methods: The study employed an integrated Theory of Constraints (TOC)-Six Sigma (SS) approach to pinpoint constraints within the PSC and proposed strategies to mitigate their effects. The case study presented in this research focused on the Indian pharmaceutical industry. Results: The results revealed that inventory status and production capacity were critical bottlenecks/constraints in the system. The integrated approach successfully identified these constraints and provided insights into potential improvement scenarios. Conclusion: This study presented a unique roadmap for industry practitioners to alleviate production bottlenecks and enhance the resilience of the PSC, especially in the face of pandemics. Implementing these findings could help pharmaceutical companies better navigate future disruptions and contribute to the development of robust therapeutic supply chains.

KEYWORDS

• COVID-19
• Pharmaceutical supply chain
• Production bottlenecks
• Six sigma
• Theory of
• constraints

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• DOI10.5530/ijper.20255228Copy

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