Abstract：
The objective of this study is to describe how OCRx (Canadian Drug Ontology) has been built to address the dual need for local drug information integration in Canada and alignment with international standards requirements.
This paper delves into (i) the implementation efforts to meet the Identification of Medicinal Product (IDMP) requirements in OCRx, alongside the ontology update strategy, (ii) the structure of the ontology itself, (iii) the alignment approach with several reference Knowledge Organization Systems, including SNOMED CT, RxNorm, and the list of \"Code Identifiant de Spécialité\" (CIS-Code), and (iv) the look-up services developed to facilitate its access and utilization.
Each OCRx release contains two distinct versions: the full and the up-to-date version. The full version encompasses all drugs with a DIN code sanctioned by Health Canada, while the up-to-date version is limited to drugs currently marketed in Canada. In the last release of OCRx, the full version comprises 162,400 classes; meanwhile, the up-to-date version consists of 36,909 classes. In terms of mappings with OCRx, substances in RxNorm and SNOMED CT fall below 40%, registering at 37% and 22% respectively. Meanwhile, mappings for CIS-Code achieve coverage of 61%. The strength mappings are notably low for RxNorm at 40% and for CIS-code at 28%. This affects the mapping of clinical drugs, which are predominantly alignable through post-coordinated expressions: 56% for RxNorm, 80% for SNOMED CT, and 35% for CIS-Code. The main support service of OCRx is a look-up service known as PaperRx that displays OCRx\'s entities based on description logic queries (DL-queries) performed through the classified structure of OCRx. The look-up services also contain a SPARQL endpoint, an OCRx OWL file downloader, and a RESTful API.
The OCRx ontology demonstrates a significant effort towards integrating Canadian drug information with international standards. However, there are areas for improvement. In the future, our focus will be on refining the structure of OCRx for better classification capability and improvement of dosage conversion. Additionally, we aim to harness OCRx in constructing an ontology-based annotator, setting our sights on its deployment in real-world data integration scenarios.
This paper delves into (i) the implementation efforts to meet the Identification of Medicinal Product (IDMP) requirements in OCRx, alongside the ontology update strategy, (ii) the structure of the ontology itself, (iii) the alignment approach with several reference Knowledge Organization Systems, including SNOMED CT, RxNorm, and the list of \"Code Identifiant de Spécialité\" (CIS-Code), and (iv) the look-up services developed to facilitate its access and utilization.
Each OCRx release contains two distinct versions: the full and the up-to-date version. The full version encompasses all drugs with a DIN code sanctioned by Health Canada, while the up-to-date version is limited to drugs currently marketed in Canada. In the last release of OCRx, the full version comprises 162,400 classes; meanwhile, the up-to-date version consists of 36,909 classes. In terms of mappings with OCRx, substances in RxNorm and SNOMED CT fall below 40%, registering at 37% and 22% respectively. Meanwhile, mappings for CIS-Code achieve coverage of 61%. The strength mappings are notably low for RxNorm at 40% and for CIS-code at 28%. This affects the mapping of clinical drugs, which are predominantly alignable through post-coordinated expressions: 56% for RxNorm, 80% for SNOMED CT, and 35% for CIS-Code. The main support service of OCRx is a look-up service known as PaperRx that displays OCRx\'s entities based on description logic queries (DL-queries) performed through the classified structure of OCRx. The look-up services also contain a SPARQL endpoint, an OCRx OWL file downloader, and a RESTful API.
The OCRx ontology demonstrates a significant effort towards integrating Canadian drug information with international standards. However, there are areas for improvement. In the future, our focus will be on refining the structure of OCRx for better classification capability and improvement of dosage conversion. Additionally, we aim to harness OCRx in constructing an ontology-based annotator, setting our sights on its deployment in real-world data integration scenarios.
摘要：
目的：本研究的目的是描述如何建立OCRx（加拿大药物本体论）以满足加拿大本地药物信息整合和与国际标准要求保持一致的双重需求。
方法：本文深入研究了（i）为满足OCRx中的药品识别（IDMP）要求而进行的实施工作，除了本体更新策略之外，(二)本体论本身的结构，(三)与几种参考知识组织系统的一致性方法，包括SNOMEDCT,RxNorm,和“代码标识符”(CIS代码)的列表，以及(iv)为便利其访问和利用而开发的查找服务。
结果：每个OCRx版本包含两个不同的版本：完整版本和最新版本。完整版本包含所有由加拿大卫生部批准的DIN代码的药物，而最新版本仅限于目前在加拿大销售的药物。在OCRx的最后一个版本中，完整版本包括162,400个类；同时，最新版本由36,909类组成。就与OCRx的映射而言，RxNorm和SNOMEDCT中的物质降至40%以下，分别为37%和22%。同时,CIS代码的映射覆盖率达到61%。RxNorm的强度映射明显较低，为40％，而CIS代码的强度映射为28％。这影响了临床药物的定位,它们主要是通过协调后的表达式对齐的：56%的RxNorm，SNOMEDCT为80%,和35%的CIS代码。OCRx的主要支持服务是一种称为PaperRx的查找服务，该服务基于通过OCRx的分类结构执行的描述逻辑查询（DL查询）显示OCRx的实体。查找服务还包含一个SPARQL端点，OCRxOWL文件下载器，一个RESTfulAPI。
结论：OCRx本体论证明了将加拿大药物信息与国际标准相结合的巨大努力。然而,还有需要改进的地方。在未来,我们的重点将是完善OCRx的结构，以获得更好的分类能力和改善剂量转换。此外,我们的目标是利用OCRx构建一个基于本体的注释器，将目光投向其在实际数据集成场景中的部署。
方法：本文深入研究了（i）为满足OCRx中的药品识别（IDMP）要求而进行的实施工作，除了本体更新策略之外，(二)本体论本身的结构，(三)与几种参考知识组织系统的一致性方法，包括SNOMEDCT,RxNorm,和“代码标识符”(CIS代码)的列表，以及(iv)为便利其访问和利用而开发的查找服务。
结果：每个OCRx版本包含两个不同的版本：完整版本和最新版本。完整版本包含所有由加拿大卫生部批准的DIN代码的药物，而最新版本仅限于目前在加拿大销售的药物。在OCRx的最后一个版本中，完整版本包括162,400个类；同时，最新版本由36,909类组成。就与OCRx的映射而言，RxNorm和SNOMEDCT中的物质降至40%以下，分别为37%和22%。同时,CIS代码的映射覆盖率达到61%。RxNorm的强度映射明显较低，为40％，而CIS代码的强度映射为28％。这影响了临床药物的定位,它们主要是通过协调后的表达式对齐的：56%的RxNorm，SNOMEDCT为80%,和35%的CIS代码。OCRx的主要支持服务是一种称为PaperRx的查找服务，该服务基于通过OCRx的分类结构执行的描述逻辑查询（DL查询）显示OCRx的实体。查找服务还包含一个SPARQL端点，OCRxOWL文件下载器，一个RESTfulAPI。
结论：OCRx本体论证明了将加拿大药物信息与国际标准相结合的巨大努力。然而,还有需要改进的地方。在未来,我们的重点将是完善OCRx的结构，以获得更好的分类能力和改善剂量转换。此外,我们的目标是利用OCRx构建一个基于本体的注释器，将目光投向其在实际数据集成场景中的部署。
