About Dysplasia
Cancer evolves through several stages of transformations. Dysplasia defines a key stage in this transformative process, when clinical interventions are necessary and likely more effective.
Dysplasia Diagnostics Limited is a UK-based company developing AI-based solutions for profiling molecular events in the blood that are associated with changes in the early stages of cancer. Our models accurately detect distributional differences of specific molecular events in blood samples of patients with various cancers.
​
Our mission is to expand cancer screening by providing non-invasive, low cost diagnostic tests through our DiNanoQ™ blood test and a suite of data products available on our diagnostic dashboard. We currently have a multi-disciplinary team comprised of Cancer Biologists, Molecular Biologists, Computational Biologists, Statisticians and Developers. Furthermore, in our drive to develop better solutions, we are supported by other scientists and consultants, who are experts in their fields.
​
​
Our Approach
Profiling rare molecular events in the blood with Artificial intelligence to detect cancers early, when treatment options are available and effective.
Screen.
We provide non-invasive, affordable and scalable methods to expand cancer screening.
Detect.
Profiling rare molecular events in the blood with high performing AI-based system deployable in low income countries.
Treat.
Many cancers are treatable if detected early. We provide a suite of data products that aid clinicians in their treatment decisions.
Our Method
We have identified rare post-transcriptional events, the frequencies of which deviate from distributions observed in normal individuals. Some of these deviations are only detectable using our high performing pattern recognition algorithms. In addition to detecting the likelihood of cancer, our models report on the primary tissue of origin, potential cancer stage and similarity to other cancer samples via our diagnostic dashboard provided to clinicians.
Non-invasive
Inexpensive
Fast Results
Science
Cancer cells release messages in the form of exosomes and biomolecules that can affect other cells, like platelets, before and after tumor formation. Approximately 2.5-fold more microvesicles are released into the extracellular space by cancer cells relative to normal cells. Tracking some of these messages is the primary objective of recent efforts to detect cancer early, as scalable methods for early cancer detection that are noninvasive and only profile biomolecules in bio fluids have emerged. Although some of these methods have shown clinical relevance in detecting late stage cancers, when tumor mutation burdens are relatively higher and easily detectable in the blood, additional research efforts are required to identify molecular events that denote early stages of cancer before liquid biopsy approaches become widely adopted.
To address some of the weaknesses of other approaches, we are developing an AI-based diagnostic system that profiles platelets RNA for rare molecular events indicative of the carcinogenic process and provides information about the diseased tissue and stage. Our statistical models rely on features engineered from properties of specific circular RNAs and distinguishing RNA editing events found in platelets preparations from cancer patients. We have developed models that accurately separate cancer samples from healthy controls and for detecting various cancers, with prediction accuracy out-performing other efforts in this space.
