"We built a software device to increase access to care and a machine learning technology to identify the disease patterns not immediately obvious to the human eye or intuition, and to help physicians non-specialized in genetics," said Marius George Linguraru, D. Phil., M.A., M.Sc., principal investigator in the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children's National Hospital and senior author of the study.
This machine learning technology indicates the presence of a genetic syndrome from a facial photograph captured at the point-of-care, such as in pediatrician offices, maternity wards and general practitioner clinics. "Unlike other technologies, the strength of this program is distinguishing ‘normal’ from ‘not-normal,’ which makes it an effective screening tool in the hands of community caregivers," said Marshall L. Summar, M.D., director of the Rare Disease Institute at Children’s National.
Every year, millions of children are born with genetic disorders. Most children with genetic syndromes live in regions with limited resources and access to genetic services. The genetic screening may come with a hefty price tag. There are also insufficient specialists to help identify genetic syndromes early in life when preventive care can save lives, especially in areas of low income, limited resources and isolated communities.
The researchers trained the technology using 2,800 retrospective facial photographs of children, with or without a genetic syndrome, from 28 countries, such as Argentina, Australia, Brazil, China, France, Morocco, Nigeria, Paraguay, Thailand and the U.S. The deep learning architecture was designed to account for the normal variations in the face appearance among populations from diverse demographic groups.
"Facial appearance is influenced by the race and ethnicity of the patients. The large variety of conditions and the diversity of populations are impacting the early identification of these conditions due to the lack of data that can serve as a point of reference," said Linguraru.
The researchers expect that as more data from underrepresented groups becomes available, they will adapt the model to localize phenotypical variations within more specific demographic groups. In addition to being an accessible tool that could be used in telehealth services to assess genetic risk, there are other potentials for this technology.
Children’s National as well recently announced that it has entered into a licensing agreement with MGeneRx Inc. for its patented pediatric medical device technology. MGeneRx is a spinoff from BreakThrough BioAssets LLC, a life sciences technology operating company focused on accelerating and commercializing new innovations, such as this technology, with an emphasis on positive social impact.
"We are excited about this licensing agreement with Children’s National Hospital and the opportunity to enhance this technology and expand its application to populations where precision medicine and the earliest possible interventions are sorely needed in order to save and improve children’s lives", said Nasser Hassan, acting chief executive officer of MGeneRx Inc.
MEDICA-tradefair.com; Source: Children’s National Hospital
