Addressing the clinical unmet needs in primary Sjögren's Syndrome through the sharing, harmonization and federated analysis of 21 European cohorts.

For many decades, the clinical unmet needs of primary Sjögren's Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-art data analytics services to address the pSS clinical unmet needs, including the development of lymphoma classification models and the identification of biomarkers for lymphomagenesis. The users of the platform have been able to successfully interlink, curate, and harmonize 21 regional, national, and international European cohorts of 7,551 pSS patients with respect to the ethical and legal issues for data sharing. Federated AI algorithms were trained across the harmonized databases, with reduced execution time complexity, yielding robust lymphoma classification models with 85% accuracy, 81.25% sensitivity, 85.4% specificity along with 5 biomarkers for lymphoma development. To our knowledge, this is the first GDPR compliant platform that provides federated AI services to address the pSS clinical unmet needs.

Towards the Establishment of a Biomedical Ontology for the Primary Sjögren's Syndrome.

Primary Sjögren's Syndrome (pSS) has been characterized as a hypersensitivity reaction type II systemic autoimmune chronic disease causing exocrine gland dysfunction mainly affecting women near the menopausal age. pSS patients exhibit dryness of the main mucosal surfaces and are highly prone to lymphoma development. This paper presents a first biomedical ontology for pSS based on a reference model which was determined by pSS clinical experts. The ensuing ontology constitutes the fundamental basis for mapping pSS-related ontologies from international cohorts to a common ontology. The ontology mapping (i.e., schematic interlinking) procedure is, in fact, a preliminary step to harmonize heterogeneous medical data obtained from various cohorts.

A novel semantic representation for eligibility criteria in clinical trials.

Eligibility Criteria (EC) comprise an important part of a clinical study, being determinant of its cost, duration and overall success. Their formal, computer-processable description can significantly improve clinical trial design and conduction by enabling their intelligent processing, replicability and linkability with other data. For EC representation purposes, related standards were investigated, along with published literature. Moreover, a considerable number of clinicaltrials.gov studies was analyzed in collaboration with clinical experts for the determination and classification of parameters of clinical research importance. The outcome of this process was the EC Representation; a CDISC-compliant schema for organizing criteria along with a patient-centric model for their formal expression, properly linked with international classifications and codifications. Its evaluation against 200 randomly selected EC indicated that it can adequately serve its purpose, while it can be also combined with existing tools and components developed for both EC specification and especially application to Electronic Health Records.

PAT: an intelligent authoring tool for facilitating clinical trial design.

Great investments are made by both private and public funds and a wealth of research findings is published, the research and development pipeline phases quite low productivity and tremendous delays. In this paper, we present a novel authoring tool which has been designed and developed for facilitating study design. Its underlying models are based on a thorough analysis of existing clinical trial protocols (CTPs) and eligibility criteria (EC) published in clinicaltrials.gov by domain experts. Moreover, its integration with intelligent decision support services and mechanisms linking the study design process with healthcare patient data as well as its direct access to literature designate it as a powerful tool offering great support to researchers during clinical trial design.