Predicting postpartem depression | Eli Lilly invests $1B in North Carolina

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  • LOUISVILLE, KY—For the last 15 years, Julia Regan has worked with industry pharmacy benefit managers, manufacturers, and EHRs in the health technology industry. Frustrated by the manual, paper-based process of the specialty medication enrollment process, she and her co-founder Brad Allen launched their own company in 2020—RxLightning. We talked with Julia about RxLighting and the Louisville innovation ecosystem in Louisville Future, click here to read the interview.
  • GRAND RAPIDS, MI—According to Health IT Analytics, around one in five new mothers experience severe depression during or after pregnancy, with an estimated 14 percent having suicidal thoughts. Michigan researchers believe the ability to predict pregnancy-related depression will be a game-changer for protecting the health of mothers and their infants. A team from the Van Andel Institute and Pine Rest Christian Mental Health Services has identified a set of 15 biomarkers found in blood that can predict if a pregnant woman will experience significant depressive symptoms with 83 percent accuracy.
  • CONCORD, NC—Eli Lilly and Co. will invest more than $1 billion in a new manufacturing plant in North Carolina that will create nearly 600 jobs there. The drugmaker said the plant will make injectable products and devices and increase its manufacturing capacity. The North Carolina Department of Commerce said it would reimburse Lilly up to $12.1 million over 12 years.
  • BLOOMINGTON, IN—PCD is a genetic condition that impacts the protective function of the respiratory system, leading to chronic health issues, such as chronic coughing and congestion, recurring respiratory and ear infections, and severe lung damage. Researchers at the Indiana University School of Medicine have screened the genetic sequences of 180,000 individuals for disease-causing variants of 29 genes linked to autosomal recessive PCD, proving the condition is more prevalent than previously thought. The research is part of a growing approach in scientific discovery to identify disease prevalence.