ERP and CCMS systems should be integrated with a PIM system that acts as the “backbone” of product information. The PIM system importance has increased due to technical sophistication of products, their need of internal management or external publishment. The proposed approach has been implemented in a proof-of-concept prototype and validated with real world pharma manufacturing data, supporting the combined execution of SWRL rules and SQWRL queries with the aim to support the ALCOA compliance assessment and calculate non-compliance percentages per each ALCOA principle. We further show that semantic annotations can be used to represent the required ALCOA compliance information, and that semantic reasoning combined with SQWRL queries can be used to evaluate ALCOA compliance. To this purpose, in the context of a pharma manufacturing environment, a data integrity ontology (DIOnt) is proposed to be utilized as the basis for the semantic representation of pharma production data and the associated regulatory compliance management processes. In this paper, we propose a method which exploits semantic web technologies to represent pharma manufacturing data in a unified manner and evaluate in a systematic manner their ALCOA compliance.
Nowadays, data integrity has become a critical issue in the pharmaceutical regulatory landscape, one that requires data to be compliant to ALCOA principles (i.e., data must be Attributable, Legible, Contemporaneous, Original, and Accurate).
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