Predicting when a birth at term will occur within one week to benefit mothers, families, and care providers

Program Type (Grant): Innovation Grant
Applicant Name: Olson, David
Competition Cycle: 2023-05
Start Date: 2023-10-01
End Date: 2026-09-30
Institutional Sponsor: Medicine & Dentistry-Obstetrics & Gynecology
WCHRI Funder: RAHF/SCHF
Total WCHRI Funding Commitment: $60,000.00

Knowing when a baby will be born is important information. Mothers living near to the hospital they will deliver in need to know so that they can plan for the baby's arrival, they can finish work and take time off, they can make final purchases, or they can schedule relatives to fly in to help out. Mothers who live in rural and remote locations who either need to drive long distances or be flown into a centre where they can deliver are often transported several weeks before their actual due dates. Their careproviders also need to know when they will deliver if transport is necessary or the mother or baby have complications. However, this adds extra stress to the mother and expense to the family and the health care system. For these reasons, it would be very helpful to have a test that could predict birth within one week with precision. Unfortunately, the best available methods, the last menstrual period or an ultrasound scan during mid pregnancy, are not very precise. We have developed an innovative and novel test based on white blood cells that are obtained from a simple arm blood draw. As a normal part of labour and delivery, these cells invade the uterus starting about one week before delivery. Our test mimics this invasion by studying the migration of the cells. It is very precise and predicts delivery within 7days. The test is complicated and time consuming in its current form. The purpose of this project, therefore, is to find a way to make the test simple and rapid. We will break the migration test down into three of its components and compare each them separately or in combination against the migration assay. We will use artificial intelligence - machine learning to analyze the results to select the assay that best predicts term delivery. That technology will be developed in a future project to create a simple and rapid test to predict delivery within 7 days.