I-Corps: Blood analyzer to detect Bovine Respiratory Disease by using blood cell counts and morphology

Award ID: 2143132

The broader impact/commercial potential of this I-Corps project is the development of a portable automated white blood cell (WBC) analysis system for cattle. By scanning bovine blood smears, the proposed technology analyzes the health status of cattle in feedlots, which allows veterinarians and producers to make more informed decisions to reduce the death rate and antibiotic use. The technology primarily is aimed at detecting Bovine Respiratory Disease (BRD), commonly known as the shipping fever, which is the most common and costly disease affecting beef cattle worldwide. Current disease detection methods can identify sick cattle, but only after theyve shown symptoms, which is sometimes too late to recover fully. The proposed technology may offer quick and accurate cattle health assessment through blood analysis to achieve early detection of disease in cattle for selective treatment even before symptoms appear. This proposed diagnostic may decrease the administration of antibiotics in feedlots and significantly reduce labor hours for daily inspection, ultimately leading to reduced costs due to cattle death and illness. It also may provide a healthier product for consumers. This I-Corps project is based on the development of a blood analyzer using an AI recognition model and software tool on bovine blood smear images. The proposed technology is aimed at detecting Bovine Respiratory Disease (BRD). Currently, there are antibiotics, vaccines, and other medication to treat BRD, however, knowing when to use these treatments can improve the treatment effectiveness and cost efficiency. Other disease detection instruments employ biomarkers based on the symptoms related to Bovine Respiratory Disease while the proposed technology analyzes the immune system strength directly from the blood cell levels. By automatically measuring the differential white blood cell counts from blood smear microscopic images using AI, the system calculates the ratio of white blood cells as a marker for diagnosing sick cattle with high confidence. Blood cell statistics such as Eosinophil Lymphocyte Ratio (ELR) are good indicators of immune system strength and may be employed to predict BRD infection. This solution may detect compromise in the immune system before any visual symptoms develop and allow more time for treatment in order to use antibiotics in a controlled manner with small dosage while keeping the cattle healthy before BRD produces permanent damage. The plan is to develop benchtop systems as well as mobile systems on smartphones to satisfy various needs and to meet the speed required. The principles and biometrics may be translated to other animals and human medicine. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ruth Shuman