PeriGen, a provider of AI-powered perinatal software solutions, has received FDA clearance for Patterns 3.0, extending its fetal heart rate pattern recognition technology to pregnancies from 32 weeks of gestational age, down from the previous threshold of 36 weeks. This expansion allows for monitoring of high-risk pregnancies at an earlier stage.
The advancement is particularly significant as approximately 8% of US babies are born between 32 and 36 weeks gestation. The technology’s earlier availability provides clinicians with additional tools to support these high-risk pregnancies.
“FDA clearance of Patterns 3.0 marks a major milestone in PeriGen’s mission to enhance maternal and perinatal care through AI-powered solutions,” said Matthew Sappern, CEO of PeriGen. “By expanding the reach of our fetal monitoring technology, we provide much greater utility to our users to leverage decision support within clinical workflow, especially as health systems contend with a shortage of nurses.”
The expansion addresses a critical need in maternal care, as many high-risk pregnancies require increased monitoring beginning at 32 weeks. Previously, PeriGen’s fetal heart rate analytics were only available from 36 weeks, which limited their use for certain preterm patients.
“With this clearance, clinicians can now utilize PeriGen’s analytics earlier in pregnancy, providing immediate benefits in clinical practice,” said John Parker, MD, Chief Medical Officer at PeriGen. “Extending our AI-driven fetal monitoring to 32 weeks allows providers to benefit from early warning of indeterminate and abnormal fetal heart rate patterns in preterm patients, supporting timely interventions for these high-risk pregnancies.”
The clearance sets the stage for future developments in fetal monitoring, including potential expansions into remote technologies and advanced analytics. PeriGen’s PeriWatch platform aims to provide consistent analysis and efficient display of complex data to enhance recognition and communication about potential problems during labor, allowing clinicians to focus more on direct patient care and less on manual calculations.
