4.6 Article

An SQWRL-Based Method for Assessing Regulatory Compliance in the Pharmaceutical Industry

Journal

APPLIED SCIENCES-BASEL
Volume 12, Issue 21, Pages -

Publisher

MDPI
DOI: 10.3390/app122110923

Keywords

ALCOA; data integrity; regulatory compliance; ontology technology; pharmaceutical industry; SWRL; SQWRL

Funding

  1. CHIST-ERA
  2. Horizon 2020 Future and Emerging Technologies programme of the European Union through the ERA-NET Cofund funding scheme (CHIST-ERA BDSI Call 2017)
  3. General Secretariat for Research and Innovation (GSRI) of Ministry of Development and Investments of the Hellenic Republic, Greece

Ask authors/readers for more resources

This paper proposes a method that utilizes semantic web technologies to represent pharmaceutical manufacturing data in a unified manner and evaluate their ALCOA compliance systematically. The method uses semantic annotations and reasoning to assess 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). 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. 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. 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. 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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available