(479g) Enabling Data Integration in Pharmaceutical Digital Supply Chains Using Ontologies

Enabling Data Integration in Pharmaceutical Digital
Supply Chains Using Ontologies

Nikolaos
Trokanas, Jagjit Singh Srai

Centre
for International Manufacturing, Institute for Manufacturing (IfM), University of Cambridge, 17 Charles Babbage Road,
Cambridge, CB3 0FS, UK

Pharmaceutical supply chains are
becoming progressively complex and increasingly vital for all actors of the
supply chain [1]. From suppliers and pharmaceutical companies to healthcare
providers and patients, the benefits stemming from an integrated supply chain
are numerous [2].

The ability to query all different
systems involved in a supply chain network using a common ontology model would
enable integration and also facilitate the utilisation of many diverse sources
of information while improving visibility and traceability of information [3].  This approach would enable a single point
access for querying all the systems while offering a common vocabulary
therefore eliminating the heterogeneity between different sources [4].

The unceasing digitisation of
firm’s operations has profoundly affected supply chains, leading to increased
information flows, therefore creating an urgent need for efficient and holistic
data integration across the supply chain.

In this work, we propose an
ontological approach towards enabling data integration across different stages
and levels of the supply chain ( REF _Ref450114776 \h  \* MERGEFORMAT Figure 1 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003400350030003100310034003700370036000000
).

Figure
 SEQ Figure \* ARABIC 1 Semantic Integration Architecture

The proposed ontological
architecture consists of four levels:

              
i.         
Supply chain level: the physical supply chain enhanced
by the use of digital technologies such as RFID, smart technologies, tracking
devices etc.

            
ii.          
Information level: the legacy systems currently used
across the pharmaceutical supply chain including databases, ERPs etc.

           
iii.         
Domain level: the level where different domains are
represented using ontologies (local), offering common vocabularies hence
eliminating any heterogeneity

           
iv.         
Top-level: the level that integrates the local
ontologies from the domain level, offering a single point query that enhances
visibility of the supply chain

This work is part of REMEDIES (RE-configuring
MEDIcines End-to-end Supply) project and the proposed architecture is validated via a
number of case studies in the pharmaceutical and healthcare industry.

References

[1] Rui
T. Sousa, Songsong Liu, Lazaros
G. Papageorgiou, Nilay
Shah, Global supply chain planning for pharmaceuticals, Chemical Engineering
Research and Design, Volume 89, Issue 11, November 2011, Pages 2396-2409, ISSN
0263-8762, http://dx.doi.org/10.1016/j.cherd.2011.04.005.

[2] Kefah Hjaila, José M. Laínez-Aguirre, Miguel Zamarripa, Luis Puigjaner, Antonio Espuña, Optimal integration of third-parties in a coordinated supply chain management environment, Computers & Chemical Engineering, Volume 86, 4 March 2016, Pages 48-61, ISSN 0098-1354, http://dx.doi.org/10.1016/j.compchemeng.2015.12.002.

[3] Edrisi Muñoz, Elisabet Capón-García, José M. Laínez-Aguirre, Antonio Espuña, Luis Puigjaner, Knowledge Management to Support the Integration of Scheduling and Supply Chain Planning using Lagrangean Decomposition, In: Krist V. Gernaey, Jakob K. Huusom and Rafiqul Gani, Editor(s), Computer Aided Chemical Engineering, Elsevier, 2015, Volume 37, Pages 989-994, ISSN 1570-7946, ISBN 9780444634290, http://dx.doi.org/10.1016/B978-0-444-63577-8.50010-3.

[4] Stef Lemmens, Catherine Decouttere, Nico Vandaele, Mauro Bernuzzi, A review of integrated supply chain network design models: Key issues for vaccine supply chains, Chemical Engineering Research and Design, Volume 109, May 2016, Pages 366-384, ISSN 0263-8762, http://dx.doi.org/10.1016/j.cherd.2016.02.015.