In order to decrease the rate and impact of preterm birth, we first need to better understand, predict, and detect early labor onset. The WISH project aims to do these three things. Through a series of studies across two leading research hospitals, we will learn about the physiological differences between normal labor and preterm labor, provide a reliable and accurate tool for labor detection, and embed these tools into clinical workflow to improve birth outcomes.
The biological triggers of labor onset are still unknown, and identification of the early stages of labor are often difficult to interpret. This project will develop and validate a novel tool for remote labor detection to ensure each mom gets the care she needs when she needs it. — Dr. Frederic Chantraine, MD Ph.D., and Principal Investigator at CHR Citadelle in Liege (Belgium).
September 29, 2018
We presented our vision for the future of prenatal health and the WISH project at the Supernova exhibition in Antwerp. We received an incredible amount of positive feedback from visitors, reminding us that the challenge we are tackling is a critical issue to address. Special thanks to our moms models!
September 1, 2018
The first 10 WISH study moms gave birth! With our dataset coming together we can now start early analysis.
May 16, 2018
Featured at Tech Startup Days in Brussels, we had the opportunity to demonstrate our technology, discuss future of prenatal health and demonstrate how we plan to help reduce the burden of preterm birth.
May 7, 2018
We received the formal approval from the Belgian’s Agency for drugs and medical devices (Agence Federale des Medicaments et des Produits de Santé) for the first WISH study. Patient inclusion can start!
April 24, 2018
We made the finals for the Ideas from Europe competition! We had the honor to advocate for better maternal and prenatal health across the European Union to an audience that included European commissioners, key opinion leaders and other successful entrepreneurs in the historical Knight’s Hall in The Hague.
November 22, 2017
We were selected to represent Belgium at the Ideas from Europe semi-finals in Tallinn. This opportunity allows us to share our vision for the future of prenatal health which the WISH project is an integral part of.
Tackling Preterm Birth and Why It Matters
Over 15 million babies are born preterm each year, and over 1 million children die each year due to complications of preterm birth (PTB). Complications that result from premature births are the leading cause of neonatal and infant mortality. In Europe, about 75% of all neonatal deaths and 60% of all infant deaths occur to infants born preterm. Additionally, premature babies are prone to serious long-term illnesses, lifelong disabilities (e.g. cerebral palsy, respiratory illnesses) and poor quality of life. As a result of this, PTB causes great suffering, concern and psychological stress to parents. Preterm birth is a global health problem with significant social and economic impact and one of the priority areas in the health policies of the EU, as is women and children health. PTB occurs across all countries and income levels and has a significant global economic impact, with an average preterm birth rate in the EU between 6% and 12%. Recent studies in the UK and the US estimate the yearly societal cost of PTB in each country at £2.946 billion and $26 billion, respectively. Both studies provide similar results for the overall cost per preterm birth at approximately €60,000, which translates into a total cost €30 billion for the EU healthcare system. The cost for the private sector is high as well: A recent study found that employers pay an average of 12 times more for a PTB than for a full-term birth.
Currently, regular medical check-ups and clinical examinations in a hospital setting are the only available solution for expectant women to detect preterm labor. Expecting couples may go several times to the hospital with suspicion of preterm labor as a result of experiencing non-labor contractions (also called Braxton Hicks contractions) that are a normal component of a healthy pregnancy. Clinical studies reveal that false alarms for a women thinking she is in labor when she subsequently shows no clinical signs of labor represents 40% of all labor-related admissions. We were able to confirm this statistic during recent interviews with specialists from different European hospitals, resulting in a consensus to situate the rate of false positives at almost 50%. These false alarms lead to an un-optimized use of healthcare resources and add to the overall cost burden.
 WHO – Recommendations on interventions to improve preterm birth outcomes – http://apps.who.int/iris/bitstream/10665/183037/1/9789241508988_eng.pdf  DelnordM, Blondel B, Zeitlin J. What contributes to disparities in the preterm birth rate in European countries? Current Opinion in Obstetrics &Gynecology  S.Beck et al. The worldwide incidence of preterm birth : a systematic review of maternal mortality and morbidity.Bulletin of the World Health Organization  Jan-Marc Hodek, Measuring economic consequences of preterm birth – https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3395039/#B10  Mangham, L.J., The Cost of Preterm Birth Throughout Childhood in England and Wales. Pediatrics 2009;123;e312  Beck, S. The worldwide incidence of preterm birth: a systematic review of maternal mortality and morbidity. Bulletin of the World Health Organization.  March of Dimes – http://www.marchofdimes.org/mission/the-economic-and-societal-costs.aspx  Jay D. Iams, MD – Prediction and Early Detection of Preterm Labor – https://pdfs.semanticscholar.org/de8f/06b54da1887de55b997a24b2c5212ffc7060.pdf
Gather data to better understand labor physiology
The Bloomlife sensor has the ability to capture a range of parameters from mom and baby including uterine muscle contractions and contraction properties. In addition, we can capture data from expecting moms while they rest comfortably at home since application of our sensor does not require a medical professional. These elements — powerful physiological data from a mom unaffected by a clinical setting — will allow us to analyze the most comprehensive dataset ever collected in the latter half of pregnancy. WISH project studies will first capture recordings starting as early as 20 weeks and extending to labor onset and through labor. This longitudinal dataset will provide a glimpse inside the human body never seen before, a way to understand the physiological differences between normal labor and preterm labor.
Improve our models to provide a reliable and accurate tool for labor detection
Prior to launching the WISH project, we investigated our capacity to predict birth using consumer generated data. That ongoing study employed data collected with our current technology, using similar physiological factors. Models based on those datasets demonstrated birth prediction with an accuracy of over 87%. The initial stages of the WISH project will hone these prediction tools with the new dataset specifically focused on detecting preterm labor. The goal: develop a complete solution to offer to clinicians to predict, prevent, and/or treat preterm labor and birth.
Apply the technology enabled solution to improve birth outcomes by adapting tools into clinical workflow.
We recognize that a solution must have value in theory and in practice. While we strongly believe that we can impact birth outcomes, we will need to see how the solutions we provide adapt to the toolkit of the clinicians working directly with patients. In this last phase of the project, we will work directly with medical professionals to design and implement adaptation of our findings into clinical workflow.
The Work Plan for the project is segmented into technical, clinical and commercial tasks along 7 different Work Packages. The work is streamlined towards our ultimate objective to develop a solution to accurately predict preterm labor, and validate its clinical and health economics outcomes. First we will improve our sensor and patch (WP1) to measure additional data to extract predictive markers, enhance our artefact filtering capability and, in turn, improve our machine learning algorithms. Then, we will apply the corresponding signal processing (WP2) and analytics (WP3) improvements and perform a first set of studies to evaluate the performance and accuracy of our labor prediction system and analytics. We will then finish the development of the end-user front-end systems, app and web portal, and deploy the entire service at our early adopter hospitals (WP4) for full clinical validation studies (WP5).
The Work Package structure is represented in the PERT chart below.
This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 778503.
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