PerkinElmer Collaborates on Preterm Birth Biomarkers

(Wellesley, MA, USA) has announced a multi-year license-and-research agreement with the University of Leicester (Leicester, United Kingdom) under which the two organizations will begin to lay the groundwork for the clinical investigation and discovery of biomarkers that predict preterm birth (PTB). The collaboration will be financed by PerkinElmer.

PerkinElmer will support the expansion of the University of Leicester's maternal health research capabilities and provide advanced tools, technology, and expertise. Professor J. C. Konje, M.D., and colleagues of Leicester University's reproductive sciences section of the department of cancer studies and molecular medicine are dedicated to the study and prediction of preterm birth. The team is conducting research in the field of preterm labor diagnosis.

The partnership will give PerkinElmer broader access within Professor Konje's research group to clinical samples, methodology, and clinical consultancy support in the field of maternal health. The University of Leicester and PerkinElmer will work towards validating any new PTB biomarkers that will complement PerkinElmer's maternal health portfolio. PerkinElmer and the University of Leicester will share access to licensed intellectual property from new PTB biomarkers that result from this research.

It is estimated that preterm labor complicates 6-10% of all pregnancies and is the most common cause of neonatal morbidity and mortality. Worldwide statistics reflect that there may be as many as 13 million preterm births annually, and this figure is predicted to increase. In the United States alone, an estimated U.S.$820 million is spent on preterm hospitalization subsequently shown to have been unnecessary. These hospitalizations tax both the mother's health and healthcare resources.

Currently, there are no rapid or accurate tests that positively predict preterm labor. The aim of the collaboration between PerkinElmer and the University of Leicester is to effectively address this need and eventually design and supply an effective preterm labor test predictor.



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