A Framework for Assessing Disruptions in a Clinical Supply Chain Using Bayesian Belief Networks
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Authors
Rodgers, Mark
Singham, Dashi I.
Subjects
Bayesian belief networks
Clinical trials
Disruption
Risk analysis
Supply chain management
Probabilistic elicitation
Clinical trials
Disruption
Risk analysis
Supply chain management
Probabilistic elicitation
Advisors
Date of Issue
2019-05
Date
2019-05
Publisher
Language
en_US
Abstract
Purpose: Clinical trial study failures cause significant disruptions to supply chain operations, which lead to operational ineffi- ciencies and financial losses. Methods: In this paper, a framework to construct a Bayesian belief network (BBN) by leveraging subject matter expertise and probabilistic elicitation methods to quantify the probability of a disruption to a clinical supply chain is presented. Results: The effect of varying input factors on a disruption probability is studied, and new metrics are developed to evaluate the significance of a disruption. Conclusions: This framework allows practitioners to assess the probability of disruptions to their network, thus enabling targeted strategies to be developed and implemented.
Type
Article
Description
The article of record may be found at https://doi.org/10.1007/s12247-019-09396-2
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Rodgers, Mark, and Dashi Singham. "A Framework for Assessing Disruptions in a Clinical Supply Chain Using Bayesian Belief Networks." Journal of Pharmaceutical Innovation (2019): 1-15.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.