RapiPath follow-on: Rapid mastitis testing through automated protocols

Clinical mastitis is one of the major causes for antimicrobial use on dairy cattle farms. There is evidence to demonstrate that on-farm tests help motivate and engage farm staff with the control of mastitis, but continuous monitoring of farm protocols and procedures is required by the herd's vet. There are now many options for on-farm mastitis diagnostics available, helping to decide which antimicrobial to use. However, the mastitis treatment protocols integrating on-farm diagnostics are rapidly changing with some data now available to demonstrate that gram-negative infections are likely to result in self-cure. Therefore, appropriate quality assurance should be considered for a successful on-farm diagnostic test.

The use of diagnostics is widely recognised as a powerful tool for improving animal health, with a wide variety of diagnostic tests available using a variety of biochemical and physical techniques. However, a common challenge to most diagnostics tools used in agriculture/veterinary medicine is a lack system integration and a slow pace of diagnosis. As a result, massive inefficiencies in logistics, increased wastage, and a lack of evidence for key policy making, especially for the dairy industry exist.

In this project, the consortium will build upon work completed in IUK project 105144 for the rapid target identification of mastitis pathogens capable of identifying 16 different pathogens, facilitating specific diagnosis. Delivering fast (~1hr), low-cost testing whilst maintaining excellent sensitivity/specificity. A specific innovation focuses on the combination species panel of target microorganisms included in the diagnostic, enabling the discrimination of contaminated samples and identifies the pathogens present in each sample, informing treatment decisions.

By developing a novel hardware and software solution to collate and share diagnostic results, it is hoped that animal health and welfare will be improved and protected, farm productivity maximised through disease reduction and logistical barriers relating to expression of expected milk yield can be overcome.