Search

The aim of this short paper or extended abstract is develop an intelligent lifelong learning cancer care framework that will be adapted by the King Hussein Cancer Center in Jordan. Cancer Care is defined as "Comprehensive care for the cancer patient as a whole including all their needs - not just the medical and physical ones - using the services of many professionals working together" [3] . Lifelong learning is about continuous development throughout a life time. Our lives, as humans, span many decades in which the environment we grew up in is in a continuous state of change. Therefore, we need to be empowered to deal with emerging challenges and thrive in a continuously changing environment. Clearly, there are multiple interactions that take place between an individual human and the surrounding environment. The Oxford dictionary defines "interaction" as "Communication or direct involvement with someone or something". Another definition: "A particular way in which matter, fields, and atomic and subatomic particles affect one another, e.g., through gravitation or electromagnetism" [4] . Therefore, communication though interactions takes place and in certain times for precious causes and purposes. On the one hand, such communication is didactic with complex interactions between an individual and the environment, and on the other hand between an individual and other members of the community - who themselves are continuously changing.

A new method for deriving informational entities based on business process models in a cancer care setting is presented in this research. This method may lead to develop system models in early stages. We have used an example of business process in Blood and Marrow Transplant (BMT) process, to illustrate the hypothesis (argument), and to show the application of this method. The process of BMT shows its ease and timeliness. Finally, further work is planned to validate and evaluate the proposed method using several cases with different domains.

Analysis of raw data generated from Next Generation Sequencing (NGS) equipments is critical in detection of pathogenic and non-pathogenic variants. Illumina MiSeq for instance has a software called Miseq-Reporter [1] which performs the analysis of the sequencing raw data. Miseq-Reporter was built to handle several workflows along with amplicon workflow such as assembly and enrichment workflows. Moreover, many procedures, such as removing non-unique alignments and remov-ing reads with N bases, need to be applicable for the analysis. There are also other pipelines available but none meets all the following features: oriented to the analysis of NGS amplicon data, uses a range of flexible procedures, and is academically free. In this paper, we report the development and implementation of an in-house pipeline which is oriented to the analysis of NGS amplicon data, applies a range of parameterized procedures that are needed to be applicable in the variant-calling analysis using amplicon data, and is academically free.

Business Process Modelling has been widely used to understand, document, and improve organizational processes in an attempt to semi- or fully- automate these processes. This paper is an attempt to better understand and model organizational processes, in a Cancer Care organization, and in particular, the processes of Cell Therapy and Applied Genomics and to improve current practice and workflow by the stakeholders, using a standardized business process modelling language, namely the Business Process Modelling Notation (BPMN). This research has highlighted the significance of using role-based business process modelling languages, in discovering gaps and to improve adhering to some internal policies, procedures and protocols.

The aim of this study is to explore the usefulness of a reverse-engineering approach compared to a conventionally used, forward-engineering Riva approach, to identify Essential Business Entities (EBEs) that can be converted to Units of Work (UOWs). The conventional approach uses 14 Riva heuristics, whereas, the reverse engineering approach uses selected, role-based business process models and workflows, linked to organisational policies and protocols, to develop object-based Business Process Architectures (BPAs). The reverse engineering approach requires limited input from the concerned stakeholders, and saves considerable time and effort in identifying candidate EBEs and calculating subsequent UOWS. This approach has demonstrated usefulness in application at a Cancer Care organisation where readiness of validated process models (of the Cell Therapy and Applied Genomics (CTAG)) and also the limited time busy key stakeholders have to conduct brainstorming sessions. Additionally, this paper has demonstrated that domain representative BPAs can be developed bottom-up from business process models that have been utilised to inform adherence to organisational policies and protocols. Finally, the linkages between the CTAG detailed business process models with the respective BPA processes provided a magnifying lens over what can be in-sourced, outsourced, semi or fully-automated processes as observed through the BPA case study and feedback obtained through concerned stakeholders.

Cancer Care systems have increasingly evolved into Systems-of-Systems (SoS) arrangements. However, these emerging arrangements bring about increased levels of complexity; mainly due to the different characteristics of the constituent systems and their nature of participation in the respective Cancer Care SoS arrangement. Consequently, achieving effective traceability of changes related implications, maintaining a high-level of Business-IT Alignment (BIA), and achieving effective coordination and communications processes are considered key challenges when applying change management in a large-scale context such as the Cancer Care SoS context. To address these challenges in such a context, novel frameworks are needed. This paper introduces the development of a key constituent of such a framework, namely a ‘Business Process Architecture (BPA)-driven Linkages and Interactions component’ based on adopting a Design Science Research Methodology (DSRM) approach. This component integrates between BPA-driven change management elements and BPA-driven SoS context elements in order to guide the application of the change management processes in the cancer care SoS context. The integration also focuses on achieving a high-level of Business-IT alignment, holistic forward and backward traceability of change related candidate implications, and facilitating the coordination and communication processes while applying change management in SoS context. A case study has been conducted at the King Hussein Cancer Center (KHCC) to demonstrate, evaluate, and further mature the developed component.

The Riva method identifies an organisation’s business process architecture. Unfortunately, the research literature does not contain evidence that the heuristics used in the method’s key steps have been validated. To begin to address this shortcoming, the co-researchers have applied Riva to aspects of the cancer care domain at the King Hussein Cancer Center (KHCC) in Amman, Jordan. A subset of the results was presented to KHCC domain experts, who were invited to evaluate the validity and completeness of the heuristics used in each of the method’s steps. Their evaluation indicates that the large majority of the heuristics associated to the various steps of the method was seen as valid; with the exception that there was a perceived lack of specific guidance by means of heuristics related to Case Strategy Processes.

Cancer care centers aim at automating the carried out procedures in their labs in order to reduce staff effort and increase test accuracy. This has motivated the researchers undertaking Ig/TCR clonality testing at a cancer care organisation to derive a requirements model for a process-based and service-oriented intelligent framework in diagnosing malignant lymphoproliferative neoplasms. However, eliciting the requirements for such a framework has been challenged by the incomplete specifications of the Ig/TCR testing in the cancer care lab protocols. Workflow models using Business Process Modelling Notation (BPMN) has been developed to deliver a validated set of Ig/TCR workflow models. These BPMN workflow models constituted the base for deriving functional and service requirements for Ig/TCR testing linked with related quality requirements. The triangulation between Ig/TCR process models, the functional/service-oriented requirements and quality requirement formed the foundations to propose an intelligent framework for Ig/TCR clonality testing with process mining and data analytics driven by current and historical Ig/TCR events in a particular lab of a cancer care centre.

Cancer Care Informatics (CCI) and its impacts are assessed using the United Nations Sustainable Development Goals (SDGs). The positive and negative impacts of CCI on the SDGs are considered through a literature review and expert assessment. There has not been a prior publication of such an assessment and this could contribute to more holistic governance of CCI. The paper reviews the individual SDGs along with consideration of the 17 SDGs as a whole. Whilst the relationship of CCI with the achievement of SDG3 (Good Health and Well-Being) is the obvious impact, CCI also has impacts on other underpinning targets or indicators within the SDG framework. For example, the Greenhouse Gas emissions from the electricity consumed by CCI computer systems will have a negative effect on SDG13 Climate Change. Using the SDG lens helps us to identify the other direct and indirect impacts of CCI on Sustainable Development and affords the opportunity to manage deliberately such impacts as improving equality of access, elimination of modern slavery and delivering CCI education.

Metastatic neuroblastoma (NB) is the leading cause of cancer death in children under the age of 5. Interestingly, infants develop a special pattern of metastasis to skin, liver and bone marrow (stage 4s) and typically undergo spontaneous remission with very low mortality. There is accumulating evidence that patients with intermediate risk group, e.g. infants with bone metastasis, have the same natural history of spontaneous regression and they do not require intensive therapy [1]. This highlights the importance of characterizing this group of patients at molecular level. We searched open repositories for quantitative gene expression data and identified GSE49711 as a suitable data source. This series includes data on 498 patients with NB including extensive phenotypic data and RNA-seq counts generated by Illumina Hiseq 2000 platform. First, we applied exploratory analysis to check the quality of data and the need for normalization before further analysis. Also, patients were categorized into 3 groups: Very low risk (VLR, N= 45), very high risk (VHR, N=92) and others (N= 361). The first 2 groups were further analyzed for differential gene expression (DGE) to identify genes responsible for their contrasting outcome. The edgeR package was used to define the top 100 differentially expressed genes with lowest adjusted p-values. These genes were applied to segregate samples using principal component analysis (PC). Interestingly, PC2 identified a special subset of patients who belong the VLR but have a unique gene expression pattern. Indeed, a small subset of VLR patients (N=6) clustered away from the main group and at extreme PC2 values. When the rotation of PC2 was analyzed, a group of 20 genes were found to have contributed to its values. The selected top 100 genes were then used to build a model of hierarchal clustering and constructing a heatmap. The same subset of samples appeared on a distinct limp of the dendogram with remarkable increased expression in the same exact group of 20 genes mentioned above. Gene ontology (GO) enrichment analysis of these specific genes was performed using an online tool developed by the GO Consortium [2], [3] revealed involvement of the following processes: Acute inflammatory response, regulation of blood coagulation, regulation of hydrolase activity and platelet degranulation. These processes indicate the role of immune system in the process, possibly combined by platelet activation. Interestingly, recent literature is highlighting the role of platelets in initiating inflammatory processes in neural tissue [4]. The model (top 100 genes selected by previous analysis) was used to test the original dataset (N=498) and segregated patients into 3 groups of patients based on outcome. Differential expression of MYCN, NME2(C-Myc transcription factor) and NCAN (neuronal adhesion) were most significantly associated with variable mortality. In conclusion, when 2 extreme groups of NB patients were defined and DGE was applied, a model was developed that showed similarity between the groups with categorization of a small subset of VLR with unique pattern of gene expression. The model worked well in defining risk of mortality and identified certain genes that can serve for prognostication.

Early cancer diagnoses, combined with treatment, enhance survival and cure rates. In Jordan, more than 20% of breast cancer patients present with advance stage disease, where cure rates are low and cost of treatment is increased. Cancer diagnosis requires both clinical and psychological counseling for compliance and successful treatment. Referrals for cancer genetic counseling should be offered for individuals with hereditary or familial cancer history. During counseling, high-risk patients undergo a designated risk assessment and management processes through reviewing their prospective risks, and the undertaking risk reduction strategies such as regular screening with the designated treatment that is geared towards reducing morbidity and mortality. Furthermore, the patient who is educated in the genetic counseling process, is a key a partner in the decision making process while being psychologically supported. Advancement in technology is reshaping the way we practice medicine, and genetic counseling is no exception. Herein, we present our genetic counseling experience for Breast and Ovarian cancers as the main genetic counseling function at King Hussein cancer Center, and discuss the potential role of technology in making this practice more efficient and robust.

Since the post genome era nearly two decades ago, genomic sciences had enormously progressed at two interdepen- dent dimensions, the experimental and computational genomics. This was aided by the advanced technical (instrumental) side, combined with sequencing and high density genotyping technolo- gies. Not only mega size data had accumulated as one expects, but this was paralleled with the development of an endless list of computational genomics algorithms that are needed for genome assembly, alignment, variants annotation, imputation, network analysis, that are all together are opening the way for the implementation of a realistic personalized medicine. All these advancements also resulted in the establishment of many genomic databases that represent most of the global citizens across the continents. Unfortunately, the Arabs were underrepresented in these democratized genomic efforts, and left a major gap to be filled. Fortunately, few Arab countries including Saudi Arabia, Kuwait, UAE and Qatar had begun to embark on the Arabian genomics quest. However much is needed, and that calls for an efficient complementary steps to put the Arabian genetics on the global map of genomics. Furthermore, disease genomics is also needing the appropriate attention. Genomics of complex and non- communicable disorders such as diabetes and cancer, should be a priority, and both of which are heavily dependent on cancer care informatics. The challenge is not little, the tools are many, much of the required resources are publically available, but needing an efficient guidance, at high level, to make the Arabian genomics visible, accessible and transnational, to bring about the Arabian genomic medicine for real. Gaps and opportunities are presented next.

Specimen tracking at cancer centers is done to inform the physicians, nurses, patients and donors, as well as other lab staff, about the current status of ordered test or procedure. At present, specimen states are identified manually by the stakeholders in labs and by accounting department, responsible to charge for the services. This means that the lab specimen states are identified in the tracking system without taking into consideration the lab business process. This creates a gap between the current identified states and the lab’s business process. Moreover, the detailed tracking of a specimen is manually carried out using lab sheets attached into the patient file. The absence of an automated, end-to-end states tracking at labs, may diminish the quality control of lab data. This paper presents the work of deriving specimen states from lab business processes. The work applies the case study of the Cell Therapy and Blood and Marrow Transplant (BMT) lab at a cancer center in Jordan. The work contributes in bridging the gap between manually identified specimen states and the lab business processes. Also, it contributes in enhancing the quality control of lab data and accordingly to cancer center data.

Quality Governance of Systems of Systems (SoS) is a very complex challenge, given that participating systems in the arrangement are often not under direct control and they have different life cycles; yet one has to ensure that the required level of quality be achieved over time. In an SoS environment, one of the biggest issues is achieving the required inter-operation among multiple, heterogeneous systems. This paper introduces a quality governance framework namely the OntoSoS.QM.Gov framework, which aims to resolve this challenge. This framework consists of four integrated quality governance components: SoS standards, SoS processes, SoS policies and SoS quality requirements. This framework was applied to a case study in the cancer care domain to demonstrate and evaluate the framework components. The early results of the case study enable identifying initial conflicts between some of the constituent systems of the SoS arrangement.