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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM32808

Pharmaceutical Supply Chain Management

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM32808

Volume:

8 |

4 |

Apr 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM32808

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MG

Manvi Gour

AT

Abhishek Thorat

AS

Arnav Singhal

JA

Jayesh Ageawal

AV

Ajinkya Valanjoo

KK

Kusum Kardam

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Abstract

Supply chain management (SCM) refers to the coordination and oversight of all activities involved in the production, procurement, transformation, and delivery of goods or services from the point of origin to the point of consumption. It encompasses the planning, execution, and control of various processes involved in the flow of materials, information, and finances across the entire supply chain. In this paper, the authors have done a detailed analysis of the pharmaceutical dataset and predicted useful metrics that can be used in the shipping industry. This paper aims to demonstrate the application of machine learning models on the prediction of shipping mode. The model is trained on various features of the pharmaceutical supply chain dataset such as unit price, first-line designation, and delivery dates. Data cleaning and feature engineering were done and multiple models were trained. Out of the models tested, XGboost was found to give the best results for the prediction of weight, shipment modes and delivery date.

KEYWORDS

Supply chain management Machine Learning models Shipping Industry XG Boost

Cite This Article

Manvi Gour, Abhishek Thorat, Arnav Singhal, Jayesh Ageawal, Ajinkya Valanjoo, Kusum Kardam, "Pharmaceutical Supply Chain Management," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 4, Apr 2024. https://doi.org/10.55041/IJSREM32808

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Publication Date

12/31/45413

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Double-Blind Peer Review

Review Rounds: 2

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3

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5

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The authors declare no conflict of interest related to this research work.

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