Benchmark Genome Study Demonstrates Accuracy of Artificial Intelligence in Rapidly Diagnosing Rare Diseases in Critically Ill Patients


2021-10-14 22:00:08 BioSpace


Pivotal study led by Fabric Genomics and Rady Children's Institute for Genomic Medicine demonstrates that artificial intelligence can enable the accurate and rapid clinical diagnosis of rare diseases in critically ill newborns based on whole-genome or whole-exome analyses OAKLAND, Calif. & SAN DIEGO, Calif.--(BUSINESS WIRE)-- Fabric Genomics (Formerly Known As Omicia, Inc.) and Rady Children's Institute for Genomic Medicine® today announced the publication of a retrospective study in Genome Medicine showing that across six leading genomic centers and hospitals, researchers were able to detect more than 90% of disease-causing variants in infants with rare diseases using the Fabric GEM AI algorithm and whole-genome and whole-exome data from previously diagnosed newborns and rare disease patients at Rady Children’s Hospital - San Diego and other clinical sites. This press release features multimedia. View the full release here: Despite differences in case collection, sequencing methods, and bioinformatics pipelines across all sites, Fabric GEM’s performance demonstrated a new standard of accuracy, ranking the causative variant first or second more than 90% of the time. In addition, Fabric GEM ranked specific diseases and conditions associated with these genes to assist clinicians in the ultimate diagnosis of each case. These findings demonstrate how artificial intelligence (AI) can successfully reduce the burden of gene variant review by clinical geneticists. “Fast and definitive genetic diagnosis is essential to providing the right treatment in a timely manner for critically ill newborns,” said Stephen Kingsmore, MD, DSc, a co-author of the study and the President and CEO of Rady Children's Institute for Genomic Medicine. “Fabric GEM has successfully demonstrated that it can automatically and quickly suggest a very short list of candidate genes for interpretation through whole-genome or whole-exome sequencing.” Additional centers that participated in the study include the University of Utah, Boston Children’s Hospital, Christian-Albrechts University of Kiel & University Hospital Schleswig-Holstein, HudsonAlpha Institute of Biotechnology, Tartu University Hospital, and the Translational Genomics Research Institute (TGen). “This study is an exciting milestone demonstrating how AI-powered decision support technologies can empower clinicians. It has the potential to significantly improve patient care with rapid insights distilled from clinical notes, medical databases, and genome sequences. Human review of these critical, but ever-expanding data is becoming infeasible due to their size and complexity. Hence GEM,” said Mark Yandell, PhD, Professor of Human Genetics and Edna Benning Presidential Endowed Chair at the University of Utah, a founding scientific advisor to Fabric and a co-author on the paper. This study also demonstrated the use of Clinithink’s CLiX focus, a natural language processing (NLP) technology applied to medical notes recorded in electronic medical records. When compared to manual abstraction, this automated approach, which couples Clinithink’s NLP technology with the Human Phenotype Ontology and Fabric GEM, can rival the results achieved through time-intensive, expert-driven curation. “Finally, clinicians do not have to sacrifice accuracy for speed when faced with a possible rare disease diagnosis in a critical setting like the NICU where time is of the essence,” said Martin Reese, PhD, CEO of Fabric Genomics and a co-author on the paper. “This study provides the rigorous benchmark validation required for its use in the clinic, showcasing how any hospital can bring informed genomics to their patients.” The complete study, titled “Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases,” can be accessed on the Genome Medicine website. About Fabric Genomics Fabric Genomics is making genomics-driven precision medicine a reality. The company provides clinical decision-support software that enables clinical labs, hospital systems, and country-sequencing programs to gain actionable genomic insights, improved diagnostic yields, and reduced turnaround time. Fabric’s Enterprise Platform for end-to-end genomic analysis incorporates proven AI-algorithms and natural language processing and has applications in both hereditary disease and oncology. Headquartered in Oakland, California, Fabric Genomics was founded by industry veterans and innovators with a deep understanding of bioinformatics, large-scale genomics, and clinical diagnostics. To learn more, visit and follow us on Twitter and LinkedIn. Rady Children’s Institute for Genomic Medicine Rady Children’s Institute for Genomic Medicine is transforming neonatal and pediatric health care by harnessing the power of Rapid Precision Medicine™ to improve the lives of children and families facing rare genetic disease. Founded by Rady Children’s Hospital and Health Center, the Institute offers the fastest delivery of rapid Whole Genome Sequencing™ to enable prompt diagnosis and targeted treatment of critically ill newborns and children in intensive care. The Institute now provides clinical genomic diagnostic services for a growing network of more than 70 children’s hospitals. The vision is for this life-changing technology to become standard of care and enable clinicians nationwide to provide rapid, personalized care. Learn more about the non-profit Institute at Follow us on Twitter and LinkedIn. View source version on For Fabric Genomics Tim Ingersoll +1 (619) 871-3769 For Rady Children’s Institute for Genomic Medicine Michael Sullivan +1 (503) 799-7520 Source: Fabric Genomics View this news release online at:
Fabric Genomics和Rady儿童基因组医学研究所领导的一项关键研究表明,基于全基因组或全外显体分析,人工智能可以实现对危重新生儿罕见疾病的准确和快速的临床诊断 加州奥克兰。加州圣地亚哥--(商业网)--织物基因组(以前被称为Omicia,Inc.)和®Rady儿童基因组医学研究所今天宣布在基因组医学上发表一项回顾性研究,该研究表明,在六个领先的基因组中心和医院,研究人员能够使用织物宝石AI算法和圣地亚哥Rady儿童医院和其他临床地点以前诊断的新生儿和罕见病患者的全基因组和全外显体数据,检测出患有罕见病婴儿中90%以上的致病变异体。 本新闻稿以多媒体为特色。在这里查看完整版本: 尽管在病例收集、测序方法和生物信息学管道方面存在差异,但Fabric Gem的性能展示了一个新的准确性标准,在90%以上的时间里,将致病变异体排在第一或第二位。此外,Fabric GEM对与这些基因相关的特定疾病和条件进行了排名,以帮助临床医生对每个病例进行最终诊断。这些发现展示了人工智能(AI)如何成功减轻临床遗传学家的基因变异审查负担。 “快速明确的基因诊断对于及时为危重新生儿提供正确的治疗至关重要,”该研究的合著者、拉迪儿童基因组医学研究所主席兼首席执行官斯蒂芬·金斯莫尔医学博士说。“Fabric GEM已经成功证明,它可以通过全基因组或全外显体测序,自动快速地建议非常短的候选基因列表进行解释。” 参与这项研究的其他中心包括犹他大学、波士顿儿童医院、基尔克里斯蒂安-阿尔布雷希茨大学和石勒苏益格-荷尔斯泰因大学医院、哈德逊阿尔法生物技术研究所、塔尔图大学医院和翻译基因组学研究所(TGen)。 “这项研究是一个激动人心的里程碑,展示了人工智能支持的决策支持技术如何增强临床医生的能力。它有可能通过从临床笔记、医学数据库和基因组序列中提取快速洞察来显著改善患者护理。由于其规模和复杂性,人类对这些关键但不断扩大的数据的审查变得不可行。因此是宝石,“马克·延德尔博士说,他是犹他大学人类遗传学教授和埃德娜·本宁总统授权主席,也是织物的创始科学顾问和论文的合著者。 这项研究还展示了ClinithInk的CLiX focus的使用,这是一种应用于电子病历中记录的医疗笔记的自然语言处理(NLP)技术。与手工抽象相比,这种将Clinithink的NLP技术与人类表型本体和织物宝石相结合的自动化方法可以与通过时间密集、专家驱动的策展取得的结果相媲美。 “最后,在像NICU这样时间至关重要的关键环境中,当面临可能的罕见疾病诊断时,临床医生不必为了速度而牺牲准确性,”织物基因组首席执行官、论文合著者马丁·里斯博士说。“这项研究提供了临床使用所需的严格基准验证,展示了任何医院如何将知情的基因组学带给患者。” 这项名为“人工智能能够对罕见遗传病进行全面的基因组解释和候选诊断提名”的完整研究可以在基因组医学网站上访问。 关于织物基因组学 织物基因组学正在使基因组学驱动的精准医学成为现实。该公司提供临床决策支持软件,使临床实验室、医院系统和国家测序程序能够获得可操作的基因组洞察,提高诊断产量,并缩短周转时间。Fabric用于端到端基因组分析的企业平台结合了经过验证的人工智能算法和自然语言处理,并在遗传病和肿瘤学中都有应用。Fabric Genomics总部位于加利福尼亚州奥克兰,由对生物信息学、大规模基因组学和临床诊断有深刻理解的行业资深人士和创新者创建。要了解更多信息,请访问,并在Twitter和LinkedIn上关注我们。 Rady儿童基因组医学研究所 Rady儿童基因组医学研究所正在通过利用快速精准医学™的力量来改善面临罕见遗传病的儿童和家庭的生活,从而改变新生儿和儿科保健。该研究所由Rady儿童医院和健康中心创建,提供最快的快速全基因组测序™,使危重新生儿和重症监护儿童能够及时诊断和针对性治疗。该研究所现在为70多家儿童医院的日益增长的网络提供临床基因组诊断服务。我们的愿景是让这项改变生活的技术成为标准的护理,并使全国的临床医生能够提供快速、个性化的护理。在radygenomics.org了解更多关于非营利机构的信息。在Twitter和LinkedIn上关注我们。 在businesswire.com查看源代码版本: 用于织物基因组学 蒂姆·英格索尔 +1(619)871-3769 为Rady儿童基因组医学研究所 迈克尔·沙利文 +1(503)799-7520 来源:织物基因组 在网上查看此新闻稿: