Apologies for my enthusiastic interruption. I am deeply intrigued by this ctDNA work using electrical signal detection. However, I see two challenges with current early detection liquid biopsy methods. Firstly, they target signals that are inherently rare in blood (less than 1% of any blood volume). Secondly, they focus on either cfDNA or ctDNA, indicating that cancer has already progressed significantly or spread to other areas.
In this context, I strongly believe that our approach positions us as one of the most captivating players in this field. We aim to leverage the immune response as an indicator of the body's cancer status. By harnessing the highly effective detectors within the immune system, we actively pursue cancer detection. Additionally, relying solely on specific biomarkers seems reminiscent of manually curating features, akin to the early days of NLP when compared to modern transformers.
We are eager to share some of our methodologies and eagerly seek collaboration with professionals from diverse backgrounds, including genomics, wet lab scientists, bioinformatics experts, as well as AI and full stack engineers. Although we are currently in stealth mode and cannot divulge extensive details, we would be thrilled to engage with inquisitive and enthusiastic scientists. In some ways, we believe that our approach may also enable us to validate the efforts of the prominent players in the field of multi-cancer early detection.
For further discussions, please feel free to reach us at [email protected].
In this context, I strongly believe that our approach positions us as one of the most captivating players in this field. We aim to leverage the immune response as an indicator of the body's cancer status. By harnessing the highly effective detectors within the immune system, we actively pursue cancer detection. Additionally, relying solely on specific biomarkers seems reminiscent of manually curating features, akin to the early days of NLP when compared to modern transformers.
We are eager to share some of our methodologies and eagerly seek collaboration with professionals from diverse backgrounds, including genomics, wet lab scientists, bioinformatics experts, as well as AI and full stack engineers. Although we are currently in stealth mode and cannot divulge extensive details, we would be thrilled to engage with inquisitive and enthusiastic scientists. In some ways, we believe that our approach may also enable us to validate the efforts of the prominent players in the field of multi-cancer early detection.
For further discussions, please feel free to reach us at [email protected].