We are partnering with clients to develop a suite of medical device algorithms to find the right treatment for every patient. We simplify complex data integration for deeper insights, IP growth, value, and clinical support.
With our expert team and cutting-edge technology, we help you create AI algorithms for image and data analysis faster. Reduce the need for costly and time-consuming pathologist involvement and free them up to focus on more important tasks.
Join forces with us to create clinical-grade AI models that can accurately identify features in images and quantify biomarkers. These models can be used to store, retrieve, and analyze large amounts of data, making your research and analysis more efficient and effective for your medical device development.
Sonrai empowers you to maximize the potential of your imaging and omic data in discovering and analyzing diverse biomarkers across various modalities. This integration of data allows you to fully utilize the valuable information obtained from your projects, and brings together insights from various aspects of pathology, including H&E-stained tissue, molecular data, and NGS data.
Collaborate with Pathologists
Everything you need in one place
Create multiple algorithms
We aim for perfection for our clients. We listen to their goals, quickly grasp their challenges, consider the needs of all stakeholders and deliver technical solutions. Below are just some of our client case studies to view.
PDL-1 AI Algorithm
Challenge
The current manual process of PD-L1 scoring by pathologists is time-consuming and challenging.
How We Helped
Sonrai is implementing an AI algorithm to assist pathologists, simplify the process with potential savings for the NHS of up to £3.2m each year. reduce the cost of the pathologists and patient time.
Molecular Test Algorithm
Challenge
For an accurate and efficient method to estimate the DNA content of tumor tissue used in molecular tests.
How We Helped
Our AI algorithm estimates tumor DNA content in macrodissected tissue for molecular tests by analyzing H&E-stained images. It serves as quality control and aids sample suitability for analysis.
AI MSI Status Prediction
Challenge
For a more efficient and accurate method to identify patients who require further testing for Lynch Syndrome.
How We Helped
We're creating a clinical app to predict MSI status from H&E-stained slides of colorectal cancer, augmenting wet-lab identification of Lynch Syndrome patients for further testing.
High Content Screening
Challenge
HCS projects typically involve numerous fluorescent images that require image analysis before further analysis.
How We Helped
AI's unsupervised learning algorithms can extract features from images to reveal mechanisms of action and in vitro responses across different experimental conditions, enabling efficient HCS data analysis.
NHS AI Lab
AI-powered Pathology Algorithms
Sonrai's breakthrough technology has the potential to revolutionize clinical pathways and add immense value to your research and discovery projects. By optimizing image analysis and increasing accuracy, the positive impact on patient care and scientific advancements will be substantial.
