By Diagnostics World Staff
May 16, 2017 | The Rady Children’s Institute for Genomic Medicine (RCIGM) and Alexion have announced a strategic partnership to accelerate the diagnosis of critically-ill newborns with rare genetic disorders. The collaboration combines the Institute’s genomic research expertise with Alexion data science and bioinformatics capabilities to advance precision medicine for infants in an intensive care setting.
“Diagnosing acutely ill babies is a race against the clock, so it’s essential for physicians to have access to solutions that will provide answers faster and help set the course of treatment,” wrote Stephen Kingsmore, President and CEO of the Institute. “Winning this race will require collaborative effort, which is why we are delighted to work with the people at Alexion who share our vision for unraveling the mysteries of genetic disease and giving hope to families with critically sick newborns.”
There is great need for employing such technology in medicine. As many as 15% of babies born in the United States are admitted to neonatal or pediatric intensive care units (NICU/PICU). Among these infants, up to one-third are likely to be affected by genetic diseases or congenital anomalies which are also the leading cause of death among babies in the NICU.
Rapid diagnosis through genome sequencing can provide definitive answers, allowing physicians to provide timely, targeted treatment that can help prevent a needless diagnostic odyssey and improve medical outcomes. The rapidly falling cost of whole-genome sequencing increases the feasibility for clinical testing for rare genetic diseases. However, the amount and complexity of data continues to grow.
Under the partnership, Alexion will share, research, and further refine the SmartPanel, a platform developed by Alexion that personalizes and prioritizes suspected rare-disease genes from a patient's next-generation sequenced genome and specific clinical presentation. The Rady Children’s Institute for Genomic Medicine is evaluating the SmartPanel in research to establish positive predictive value, enable electronic medical record (EMR) integration for rapid phenotypic extraction, and assess overall patient outcomes via earlier diagnosis. Both organizations will collaborate on patient and disease characterization, algorithmic modules and scalability with a shared goal of contributing core capabilities to the open source community to accelerate research in the challenging area of pediatric rare-disease diagnosis.