A Framework for Assessing Disruptions in a Clinical Supply Chain Using Bayesian Belief Networks

Mark Rodgers, Dashi Singham

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: Clinical trial study failures cause significant disruptions to supply chain operations, which lead to operational inefficiencies 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.

Original languageEnglish (US)
Pages (from-to)467-481
Number of pages15
JournalJournal of Pharmaceutical Innovation
Volume15
Issue number3
DOIs
StatePublished - Sep 1 2020

All Science Journal Classification (ASJC) codes

  • Pharmaceutical Science
  • Drug Discovery

Keywords

  • Bayesian belief networks
  • Clinical trials
  • Disruption
  • Probabilistic elicitation
  • Risk analysis
  • Supply chain management

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