Clinical Genome Data Model (cGDM) provides Interactive Clinical Decision Support for Precision Medicine

Abstract

in light of recent developments in genomic technology and the rapid accumulation of genomic information, a major transition toward precision medicine is anticipated. However, the clinical applications of genomic information remain limited. This lag can be attributed to several complex factors, including the knowledge gap between medical experts and bioinformaticians, the distance between bioinformatics workflows and clinical practice, and the unique characteristics of genomic data, which can make interpretation difficult. Here we present a novel genomic data model that allows for more interactive support in clinical decision-making. Informational modelling was used as a basis to design a communication scheme between sophisticated bioinformatics predictions and the representative data relevant to a clinical decision. This study was conducted by a multidisciplinary working group who carried out clinico-genomic workflow analysis and attribute extraction, through Failure Mode and Effects Analysis (FMEA). Based on those results, a clinical genome data model (cGDM) was developed with 8 entities and 46 attributes. The cGDM integrates reliability-related factors that enable clinicians to access the reliability problem of each individual genetic test result as clinical evidence. The proposed cGDM provides a data-layer infrastructure supporting the intellectual interplay between medical experts and informed decision-making.

Precision Medicine of Autoimmune Diseases

“…The information provided by the Genomics data is an indispensable component of precision medicine as it holds the key to the explanation in individual variability and evolution [54]. But, the clinical use of genomic data still needs to be improved on to overcome challenges stated by Kim et al [55] like: a. The incongruity between the form of genomic and clinical information: as a result of extensive (several tens of gigabytes of sequence) data in the genomic data, clinical data cannot be processed in the clinical practice without additional processing [55,56].…”

AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease

“…There is an ongoing active community discussion of how to model and organize data in medical genomics [28], [47]. Rather than proposing a concrete data model, AnFiSA defines basic principles of organization with an ability to accommodate specific data models by provisioning the metadata used for configuration.…”

Um Modelo para Predição Individualizada da Deterioração da Saúde de Pacientes no âmbito da Internet das Coisas

“…As abordagens médicas modernas visam personalizar diagnósticos e terapias para cada paciente [Barbour 2019] visando fornecer o "tratamento certo para o paciente certo na hora certa" [Mills 2017]. Emerge a chamada medicina de precisão (personalizada ou individualizada) queé fortemente norteada por dados e tecnologia emáreas que incluem informação médica e engenharia da computação [Kim et al 2020]. Assim o cuidado com a saúde baseado unicamente na experiência está mudando para a terapia de precisão baseada em big data para pacientes individuais [Shen 2020].…”