Cancer Management Solutions Powered By Deep Learning Technologies
About The Company
Curatio.DL provides cancer management solutions by delivering accurate diagnosis & prognosis, allowing personalized treatment for cancer patient based on Deep Learning-powered pathology analysis. This innovative pre-processing segmentation technology will allow pathologists, and in particular, pathologists who are not necessarily experts in a specific field, to obtain expert-level decision support diagnosis and prognosis.
The company has an exclusive groundbreaking
To provide personalized medicine for each cancer patient by delivering accurate diagnosis & prognosis, based on DL-powered technology analysis
Our platform and services
CuratioDL’s solution is to provide Accurate diagnosis and treatment matching based on Deep Learning analysis of histopathologic biopsies. We are using neural networks combined with an innovative pre-processing segmentation technology to process dozens of thousands of images of histopathology slides. Providing us with all the information needed for the decision :
- Cancer subtypes
- Genetic profiling
- Survival period estimation
- Treatment suggestion
The advantages are clear
The process relies on big data – enabling analysis of much bigger areas of samples at once providing accurate and fast diagnosis and in low cost.
It can discover novel clinically relevant patterns objectively, as the system teaches itself to identify new patterns. And therefore, the procedure can be copy paste to other tumor types or diseases.
On top the features just mentioned – the system can also highlight regions of interest for the pathologists with unique coloring. As the examination samples are huge, this feature can save time for the pathologists and draw his attention to the areas which have clinical significance, by than save a lot of diagnostic errors.
On top of diagnosis and sub type classification our models were able to also provide estimation of the patients’ survival period. This has a huge impact on the disease management both for physicians and for patients.
The Unmet Needs
The Cancer Management Solution
More accurate diagnosis & prognosis
- Shows regions in image of most significance to the resulting interpretations of histopathology slides
- Allow general pathologists, even not experts pathologists, to obtain expert-level decision support for cancer diagnosis and treatment recommendations
- Further differentiates subtypes where a diagnosis of cancer has already been determined
Personalized treatment for patient
- Predicts mutation burden for more suitable selection of immuno-therapeutic treatment
- Contains previously unrecognized signals indicative of disease progression and treatment response
- Match between patient and his cancer subtype to the right drug
- First to develop digital pathology on kidney cancer or RCC
- First to classify subtypes of lung cancer
- First to demonstrated results on 10 different types of cancer with >90% accuracy using the DL Model, including kidney, lung, leukemia, brain, breast, ovarian, colon, rectal, stomach cancer and liver hepatocellular carcinoma, while competitors in the market which focus only on 1-2 types of cancer
- Able to successfully test the technology on a new type of cancer with a small number of samples without the need to change algorithm, while competitors in the market need numerous samples to test their technology on a new type of cancer
Market potential for Curatio’s DL Model
The global pathology market has reached US$33 billion in 2020 and is growing at a CAGR of 7% to US$50 billion in 2026
The immunotherapy drugs market has reached US$163 billion in 2020 and is growing at a CAGR of 11% to US$274 billion in 2025
The Leading Team
Rafi Heumann - CEO
Over the last 15 years top executive positions running Digital health companies from a concept idea as start-up, to hundreds of millions of dollars in sales and successful IPOs.
Prof. Yuval Shahar, MD, PhD
Head, medical informatics research center and the Josef Erteschik Chair in information systems engineering at Ben Gurion University
Prof. Jack Baniel, MD - CMO
Head of the Urology Department, Deputy Director of the Cancer Institute Davidof, Rabin Medical Center (Beilinson)
Gal Aviram - CTO
B.Sc biomedical engineer, experienced in algorithm developments in the medical devices field with hands-on data implementation analysis and training of deep learning models
Dr. Irit Arbel - Executive Manager
Medical expert with significant senior biopharma and medical device experience. Co-Founder and served as CEO of several companies
Ass. Prof. Kun-Hsing Yu, MD, PhD - Inventor
Assistant Professor of Biomedical Informatics, Harvard Medical School and assistant Professor of Pathology at Brigham and Women's Hospital