An Ontology For Formal Representation Of Medication Adherence-Related Knowledge: Case Study In Breast Cancer Sawesi Suhila 1 , Josette F. Jones 1 , William D. Duncan 2 1 School of Informatics and Computing – Indianapolis, Department of BioHealth Informatics, IUPUI, Indianapolis, IN, United States 2 Roswell Park Comprehensive Cancer Center, Buffalo, NY, United States Keywords—ontology, adherence to adjuvant endocrine therapy, adherence to adjuvant hormonal therapy, adherence to aromatase inhibitors, adherence to tamoxifen I. INTRODUCTION Medication non-adherence is a major healthcare problem that negatively impacts the health and productivity of individuals and society as a whole. Reasons for medication non-adherence are multi-faced, with no clear-cut solution [1]. Adherence to medication remains a difficult area to study, due to inconsistencies in representing medication-adherence behavior data that poses a challenge to humans and today’s computer technology related to interpreting and synthesizing such complex information. Medication adherence among breast cancer patients exemplifies the challenges mentioned above. Two types of hormone-based therapies, tamoxifen (TAM) and aromatase inhibitors (AIs), have been shown to slow down disease recurrence and mortality rates among women with breast cancer if the regimens are adhered to for a minimum of five years[1]. However, studies show that around 50% of breast cancer patients did not adhere to hormone treatment, thus risking clinical responses below the expected standards[1]. Developing a consistent conceptual framework to medication adherence is needed to facilitate domain understanding, sharing, and communicating, as well as enabling researchers to formally compare the findings of studies in systematic reviews. The goal of this research is to create common language that bridges human and computer technology by developing a controlled structured vocabulary of medication adherence behavior—“Medication Adherence Behavior Ontology” (MAB-Ontology) using breast cancer as a case study to inform and evaluate the proposed ontology and demonstrating its application to real-world situation. II. METHODS The design process for MAB-ontology carried out using the METHONTOLOGY method [2] incorporated with the Basic Formal Ontology (BFO) principles of best practice [3] as shown in figure 1. This approach introduces a novel knowledge acquisition step that guides capturing medication- adherence-related data from different knowledge sources, as shown in table 1. These sources were analyzed using a systematic approach that involved some questions applied to all source types to guide data extraction and inform domain conceptualization. A set of intermediate representations involving tables and graphs was used to allow for domain evaluation before implementation. Figure1.MAB Ontology Methodology Overview III. RESULT A. Domain Specification MAB-Ontology is a reference ontology that comprehensively represents the domain of medication adherence using breast cancer as a case study. This ontology includes factors that impact medication adherence, the methods used to assess adherence, and the interventions used to improve adherence. B. Knowledge Acquisition Table 1 shows the category of knowledge source types, resources description, and the number included under each category, use of each source type, and examples of the source extracted under the mentioned category. Table 1: Knowledge acquisition Knowledge Source Type Resources & Number Use Source Example Medication Adherence Assessment Literature Journal articles (51) Terms, definitions, components, interventions Sawesi et al. (2016) [4] Proceedings of the 9th International Conference on Biological Ontology (ICBO 2018), Corvallis, Oregon, USA 1 ICBO 2018 August 7-10, 2018 1