Pronova develops non-invasive biosensors, known as Kora Strips, that analyze biomarkers in pet saliva to provide real-time health insights for proactive care. This technology enables early detection of health issues, allowing pet owners to monitor their pets' well-being and facilitate timely interventions.
Funding
Funding not disclosed
Founders
Product
Problem
Current methods of monitoring pet health often rely on invasive procedures like blood draws, causing stress for pets and potentially delaying early detection of health issues. Traditional veterinary checkups may not provide continuous insights into a pet's well-being between appointments.
Solution
Pronova is developing Kora Strips, non-invasive biosensors that analyze biomarkers in pet saliva to provide real-time health insights. The Kora Strips use screen-printed electrodes to detect biological signals in a pet's saliva, tracking changes in their health at the molecular level. The accompanying app combines biomarker data with key characteristics like age, weight, breed, and sex, using machine learning to compare this information with similar animals and their health trends. This enables pet owners to proactively monitor their pet's health and detect potential issues early on, facilitating timely interventions and personalized care. The technology aims to offer a stress-free alternative to traditional methods, providing continuous, data-driven insights for proactive pet care.
Target Audience
Pronova's primary customers are pet owners who want to proactively monitor their pet's health and well-being through non-invasive, data-driven insights.
Features
- Non-invasive saliva-based testing using Kora Strips
- Real-time biomarker analysis for early detection of health issues
- Screen-printed electrodes for detecting biological signals in saliva
- Electrochemical processing techniques to measure biomarker concentrations
- Mobile app that combines biomarker data with pet characteristics
- Machine learning algorithms for personalized health insights and trend analysis