Closing the Cold-Chain Gap: A Data Governance & CAPA Playbook for Pharmacy FEFO Compliance and Excursion Response

References

[1] Adebiyi, O., Adeoti, M. and Mupa, M.N. (2025). The use of employee ownership structures as strategies for the resilience of smaller entities in the US. International Journal of Science and Research Archive, 14(1), pp.1002–1018. doi: https://doi.org/10.30574/ijsra.2025.14.1.0039.

[2] Adebiyi, O., Lawrence, S.A., Adeoti, M., Nwokedi, A.O. and Mupa, M.N. (2025). Unlocking the potential: Sustainability finance as the catalyst for ESG innovations in Nigeria. World Journal of Advanced Research and Reviews, 25(1), pp.1616–1628. doi: https://doi.org/10.30574/wjarr.2025.25.1.0108.

[3] Amengual, M. and Distelhorst, G. (2025). Cooperation and punishment in managing social performance: Labor standards in the Gap Inc. supply chain. Strategic Management Journal. doi: https://doi.org/10.1002/smj.3733.

[4] Aror, T. and Mupa, M.N. (2025a). WorldCom and the collapse of ethics: A case study in accounting fraud and corporate governance failure. World Journal of Advanced Research and Reviews, 26(2), pp.3773–3785. doi: https://doi.org/10.30574/wjarr.2025.26.2.1632.

[5] Aror, T.A. and Mupa, M.N. (2025b). Risk and compliance paper what role does Artificial Intelligence (AI) play in enhancing risk management practices in corporations? World Journal of Advanced Research and Reviews, 27(1), pp.1072–1080. doi: https://doi.org/10.30574/wjarr.2025.27.1.2607.

[6] Baquero, P.M., Amariles, D.R., Amyot, D., Anda, A.A. and Roveri, M. (2025). The compliance gap in data supply chains: contract specification languages and smart contracts as compliance technologies. Artificial Intelligence and Law, [online] pp.1–50. doi: https://doi.org/10.1007/s10506-025-09464-8.

[7] Benabbes, M., Yachi, L., Aliat, Z. and El Cadi, M.A. (2025). 5PSQ-145 The use of mean kinetic temperature to manage temperature excursion in hospital pharmacy. European Journal of Hospital Pharmacy, [online] 32(Suppl 1), pp. A217.2-A218. doi: https://doi.org/10.1136/ejhpharm-2025-eahp.438.

[8] Chakraborty, T. (2025). DI Compliance Assessment Sheet (Data Integrity Master Plan Attachment 1) Check Items. ResearchGate. [online] doi: https://doi.org/10.13140/RG.2.2.28690.77764.

[9] Chukwu, O.A. and Adibe, M. (2021). Quality assessment of cold chain storage facilities for regulatory and quality management compliance in a developing country context. The International Journal of Health Planning and Management, 37(2), pp.930–943. doi: https://doi.org/10.1002/hpm.3385.

[10] Dib, C.C. (2024). Bioethics-CSR Divide. Voices in bioethics, 10. doi: https://doi.org/10.52214/vib.v10i.12376.

[11] Elghomri, B., Messaoudi, F. and Touti, N. (2025). The Role of AI in Driving Accountability and Transparency in Global Supply Chains: The Fragmented Bridge Between Research and Practice. Operations and Supply Chain Management An International Journal, [online] pp.275–287. doi: https://doi.org/10.31387/oscm0610472.

[12] Ferlito, C. and Kabir, M. (2025). An Innovation Policy Agenda for Bangladesh. [online] (8). Available at: https://www.researchgate.net/publication/395307333_An_Innovation_Policy_Agenda_for_Bangladesh.

[13] Filipova, D. and Grigorov, E. (2024). Pharmaceutical Cold Chain Management— Regulatory Framework and Practical Approaches. Scripta Scientifica Pharmaceutica, [online] 11(Supplement 1), p.48. doi: https://doi.org/10.14748/ssp.v11i1.10075.

[14] Hlahla, V., Mupa, M.N. and Danda, C. (2025). Donor-funded project financial management: Lessons from global development initiatives for U.S. community-based programs. World Journal of Advanced Research and Reviews, [online] 27(2), pp.1812–1821. doi: https://doi.org/10.30574/wjarr.2025.27.2.3047.

[15] Kalu-Mba, N., Mupa, M.N. and Tafirenyika, S. (2025a). Artificial Intelligence as a Catalyst for Innovation in the Public Sector: Opportunities, Risks, and Policy Imperatives. [online] 8(11), pp.716–724. Available at: https://www.researchgate.net/publication/391736874_Artificial_Intelligence_as_a_Catalyst_for_Innovation_in_the_Public_Sector_Opportunities_Risks_and_Policy_Imperatives.

[16] Kalu-Mba, N., Mupa, M.N. and Tafirenyika, S. (2025b). The Role of Machine Learning in Post-Disaster Humanitarian Operations: Case Studies and Strategic Implications. [online] 8(11), pp.725–734. Available at: https://www.researchgate.net/publication/391737365_The_Role_of_Machine_Learning_in_Post-Disaster_Humanitarian_Operations_Case_Studies_and_Strategic_Implications.

[17] Khanna, A., Jain, S., Sah, A., Dangi, S., Sharma, A., Tiang, S.S., Wong, C.H. and Lim, W.H. (2025). Generative AI and Blockchain-Integrated Multi-Agent Framework for Resilient and Sustainable Fruit Cold-Chain Logistics. Foods, 14(17), p.3004. doi: https://doi.org/10.3390/foods14173004.

[18] Li, M. (2024). The Negative Impact of ESG on the Australian Minerals Supply Chain. Advances in Economics Management and Political Sciences, 72(1), pp.265–272. doi: https://doi.org/10.54254/2754-1169/72/20240702.

[19] Matsebula, N.C., Toledo, C.P., Saungweme, J., Masunungure, M. and Mupa, N. (2025). Agile-Predictive Convergence: A New Paradigm for Smart Investment and Risk Management Platforms. [online] 9(1), pp.1247–1257. Available at: https://www.researchgate.net/publication/394102571_Agile-Predictive_Convergence_A_New_Paradigm_for_Smart_Investment_and_Risk_Management_Platforms.

[20] Mayake, V.G. and Base, R. (2025). Closing the Accountability Gap: Equity, Training, and Institutional Legitimacy in Urban School Governance. International Journal of Social Science and Human Research, [online] 08(08). doi: https://doi.org/10.47191/ijsshr/v8-i8-91.

[21] Melón, Á. and Campo, A.B. (2024). Closing the gender wage gap in the boardroom: the role of compliance with governance codes. Gender in management. doi: https://doi.org/10.1108/gm-05-2023-0180.

[22] Mgugu, M., Chitemerere, Z.B., Agartha, T., Zireva, K. and Mupa, N. (2025). The Role of Global Marketing Professionals in Advancing Inclusive Trade and Cross-Cultural Consumer Engagement in the US. [online] 9(2), pp.862–872. Available at: https://www.researchgate.net/publication/395027150_The_Role_of_Global_Marketing_Professionals_in_Advancing_Inclusive_Trade_and_Cross-Cultural_Consumer_Engagement_in_the_US.

[23] Mohammed, S., Jibo, A.I., Aliyu, S., Grys, P. and Umar, N. (2017). Regulation of medicines storage for health system resilience in Nigeria. Tropical Medicine & International Health, [online] 22(1), p.296. Available at: https://www.researchgate.net/publication/323302132_Regulation_of_medicines_storage_for_health_system_resilience_in_Nigeria.

[24] Mupa, M.N., Tafirenyika, S., Nyajeka, M. and Moyo, T.M. (2025a). Actuarial Implications of Data-Driven ESG Risk Assessment. [online] ResearchGate. Available at: https://www.researchgate.net/publication/389131851_Actuarial_Implications_of_Data-Driven_ESG_Risk_Assessment [Accessed 6 Sep. 2025].

[25] Mupa, M.N., Tafirenyika, S., Nyajeka, M.R., Moyo, T.M. and Zhuwankinyu, K. (2025b). Machine Learning in Actuarial Science: Enhancing Predictive Models for Insurance Risk Management. [online] 8(8), pp.493–504. Available at: https://www.researchgate.net/publication/389132064_Machine_Learning_in_Actuarial_Science_Enhancing_Predictive_Models_for_Insurance_Risk_Management.

[26] Musemwa, O.B., Mukudzeishe, W.M., Mupa, M.N. and Tsambatar, T.E. (2025). Digital Transformation in STEM Education: Leveraging Telecommunications Infrastructure to Enhance Engineering Readiness in Developing Economies. [online] 9(2), pp.1014–1023. Available at: https://www.researchgate.net/publication/395027066_Digital_Transformation_in_STEM_Education_Leveraging_Telecommunications_Infrastructure_to_Enhance_Engineering_Readiness_in_Developing_Economies.

[27] Patil, S. (2025). Artificial Intelligence in Pharmacy: Applications, Challenges, and Future Directions in Drug Discovery, Development, and Healthcare. [online] doi: https://doi.org/10.70593/978-93-7185-204-3.

[28] Rajagopal, P., Selvam, M., Jayamani, U., Ibrahim, I. and Sundram, V.P.K. (2025). Supply Chain Karma Score (SCKS): A Conceptual Framework for Measuring Ethical Footprint in Global Supply Chains. Information Management and Business Review, [online] 17(2(I)S), pp.453–465. doi: https://doi.org/10.22610/imbr.v17i2(I)S.4622.

[29] Shiraishi, R. and Mupa, M.N. (2025). Cross-Border Tax Structuring and Valuation Optimization in Energy-Sector M&A: A U.S.-Japan Perspective. [online] 8(11), pp.126–135. Available at: https://www.researchgate.net/publication/391485061_Cross-Border_Tax_Structuring_and_Valuation_Optimization_in_Energy-Sector_MA_A_US-Japan_Perspective.

[30] Sienkiewicz, H. (2025). Article Closing the Gap Supply Chain Risk Management United States Cybersecurity Magazine Winter 2018. [online] Volume 6, Number 19(Winter 2018). Available at: https://www.researchgate.net/publication/393802849_Article_Closing_the_Gap_Supply_Chain_Risk_Management_United_States_Cybersecurity_Magazine_Winter_2018.

[31] Singh, P., Thakur, A. and Yadav, D. (2025). AI driven Innovations in Pharmaceuticals: Optimizing Drug Discovery and Industry Operations. RSC Pharmaceutics. doi: https://doi.org/10.1039/d4pm00323c.

[32] Toledo, C.P., Saungweme, J., Matsebula, N.C., Masunungure, M. and Mupa, N. (2025). Leveraging Big Data and AI for Liquidity Risk Management in Financial Services. [online] 9(2), pp.522–530. Available at: https://www.researchgate.net/publication/394758573_Leveraging_Big_Data_and_AI_for_Liquidity_Risk_Management_in_Financial_Services.

[33] Wichianrat, K., Chamchang, P. and Fan, Y. (2025). Risk Identification and Assessment in Cold Chain Logistics for Durian Exports from Thailand to China: Insights from Packing House Perspectives. ABAC Journal, [online] 45(3), pp.182–199. doi: https://doi.org/10.59865/abacj.2025.22.

[34] Yingngam, B., Navabhatra, A. and Sillapapibool, P. (2024). AI-Driven Decision-Making Applications in Pharmaceutical Sciences. Advances in Media, Entertainment, and the Arts, pp.1–63. doi:https://doi.org/10.4018/979-8-3693-0639-0.ch001.

[35] Zhuwankinyu, E.K., Mupa, M.N. and Moyo, T.M. (2025). Leveraging Generative AI for an Ethical and Adaptive Cybersecurity Framework in Enterprise Environments. [online] 8(6), p.675. Available at: https://www.researchgate.net/publication/387906108_Leveraging_Generative_AI_for_an_Ethical_and_Adaptive_Cybersecurity_Framework_in_Enterprise_Environments.

[36] Zhuwankinyu, E.K., Mupa, M.N. and Tafirenyika, S. (2025). Graph-based security models for AI-driven data storage: A novel approach to protecting classified documents. World Journal of Advanced Research and Reviews, 26(2), pp.1108–1124. doi: https://doi.org/10.30574/wjarr.2025.26.2.1631.

@article{1710656,
      author = {Omega Muchabaiwa, Munashe Naphtali Mupa, Rudorwashe Tsitsi Karuma},
      title = {Closing the Cold-Chain Gap: A Data Governance & CAPA Playbook for Pharmacy FEFO Compliance and Excursion Response},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {3},
      pages = {802-812},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710656.pdf},
      abstract = {Cold chain management for pharmaceuticals will have an extremely important role in ensuring product protection, regulatory compliance, and cost-effectiveness. The present paper provides a data governance and CAPA playbook to identify and close compliance gaps in First Expired, First Out (FEFO) operations and excursion response. Based on GDP/GxP guidance, peer-reviewed scientific publications, and industry excursion case studies, the framework includes four tiers: governance, excursion management, KPI control, and training. The playbook standardizes excursion documentation and root-cause templates, as well as a suite of KPIs, including MAPE demand forecasting, excursions per 1,000 shipments, and expiry-at-risk percentages, integrated into digital dashboards with predictive alerts for excursions. The results emphasize less spoilage with better compliance traceability and quantifiable cost savings, as well as scalability among providers and wholesalers. Moreover, the research is in line with ESG priorities of reducing waste and transparency. The research findings provide regulators, pharmacies, and logistics providers with a realistic roadmap, and future studies should investigate the integration of the IoT and advanced AI into predictive cold chain resiliency.},
      month = {September},
  }