Mike Hollan

The study used technology developed by a variety of companies, including RYLTI.
AI digital twins are here.
A group of researchers presented the first study to use digital twins created using AI. According to a press release,1 the group consisted of researchers from Genzeva, LumeGene, RYLTI, Brigham & Women’s Hospital of Harvard University, and QIAGEN Digital Insights worked together to bring the digital creations into a study on the molecular mechanisms of endometrial-related disorders.
Dr. William G. Kearns, co-founder, CEO, and chief scientific officer at Genzeva and LumaGene, led the study. In a press release, he said, “This landmark study demonstrated a way to combine omics and a digital twin ecosystem to understand the molecular mechanism of disease better. By incorporating Genzeva's multiomics platform, QIAGEN's Digital Insight, and RYLTI's pioneering biomimetic AI platform for genomic analyses we uncovered hidden dark data with insights that may never have been achievable before.”
He continued, “The possibility to redefine this scientific approach promises a new horizon in many fields of research, and the biotech industry eagerly anticipates the impact of these innovative techniques on future discoveries and therapeutic interventions.”
Dr. Ray Anchan, assistant professor at Harvard Medical School and co-director at Brigham and Women's Hospital Center for Endometriosis, also said, "The computational capacity of knowledge engineering using a biomimetic digital twin ecosystem provides a unique opportunity to efficiently identify novel and unique DNA variants in various disease processes that could prove useful for developing new targeted therapies."
The use of digital twins in the study allowed researchers to analyze what they refer to as “dark data” (data that is normally hidden when using traditional methods). As a result, the study seems to have identified eight mutation and four variants connected with the disorder.
The digital twins were created using RYLTI’s Knowledge Engineering (RKE) Biomimetic AI Platform and Digital Twin Ecosystem.
Joseph Glick, co-founder and chief innovation officer at RYLTI, said, “The NAS has described the importance of using digital twins in biomedical research, which requires a toolset without limitations or bias for effective discovery and validation. This new innovative omics method incorporating phenotype ranking algorithms with digital twins demonstrates the potential to enhance the drug discovery process with the inclusion of data, enabling improved decision making, expedited development timelines, refined target identification, and reduced risks."
RYLTI’s co-founder and CEO Peter Fiorillo added, “This exciting breakthrough with use of the first biomimetic digital twins comes at a very exciting time for us, not only in advanced genomic research, but across biopharma and in other sectors.”
The results of the study are published in a paper titled “The Application of Knowledge Engineering via the Use of Biomimetic Digital Twin Ecosystem, Phenotype Driven Variant Analysis, and Exome Sequencing to Understand the Molecular Mechanisms of Disease,” which has been published in The Journal of Molecular Diagnostics.