Difference between revisions of "Team:UC San Diego"

Line 52: Line 52:
 
             <div id="myBar"></div>
 
             <div id="myBar"></div>
 
           </div>
 
           </div>
−
           <h2 style="margin-top:4vh; margin-bottom:4vh;">Use Synthetic Biology to Enhance Liquid Biopsy</h2>
+
           <h2 style="">Use Synthetic Biology to Enhance Liquid Biopsy</h2>
 
         </center>
 
         </center>
 
       </div>
 
       </div>

Revision as of 23:25, 17 October 2018

Use Synthetic Biology to Enhance Liquid Biopsy

Challenges in Cancer Diagnostics Today

needle

Ivasiveness

Traditional tissue biopsies are often extremely invasive and can lead to further complications, including incorrect diagnoses or spreading the cancer.

graph

Lack of Accuracy

The predictive value of many imaging algorithms and morphology-based technologies is often too low.

vial

Chemical Treatment

Treatment of samples with chemicals such as sodium bisulfite impacts the results by lowering accuracy and inducing random breaks in DNA fragments.

cancerID

Thinking About Cancer Differently

A New Approach

Instead of thinking about cancer as a disease based on alterations to the genetic code that are perpetuated through the central dogma, our team sought to identify a more consistent diagnostic metric. For that, we turned to promoter methylation as an epigenetic determinant of cancer.

dnaMod

Introducing a Simple and Convenient System

ai

Unlock the Power of AI

Using our unique algorithm, we’ve determined the key indicators of cancer that serve as early detection signals.

cloud

Use the Power of the Cloud

Use technology to improve your healthcare experience. Use our app to get quick results and share that data with your doctor and loved ones.

drop

With Just a Drop of Blood

We’ve developed a noninvasive blood test that you can perform on a single microfluidic platform. To leverage all the information encoded in a single drop of blood.

dna

With the Power of Proteins

Compared to other liquid biopsy tests, our team is using a novel protein-based method to detect specific markers in your blood.

“The Epinoma team clearly believes the ability to detect and assess a person’s cancer must continue to be improved. Their focus on epigenetics coupled with machine learning represents a novel approach in cancer diagnostics and may yield important advances for patient care. I commend the team for going well beyond a basic focus on technology development to understanding their stakeholders' needs and crafting their patient-centric vision accordingly. If they achieve this vision, Epinoma could have a meaningful impact on the patient care journey, from early screening to post-therapy response. Epinoma's long-term potential is enhanced by their push to develop a complementary digital health platform, which will be crucial in establishing broad based commercial adoption, direct patient engagement, and a point-of-care opportunity down the road. I am truly impressed with what they have accomplished thus far in their young careers."

Data Driven

The foundation of our approach lies in our idea to use unsupervised machine learning to analyze massive sets of data from The Cancer Genome Atlas and other clinical datasets. From this, we use special methods to find optimal gene panels for biomarker analysis. Want to get even more insight into our methodology?

Expert Insight

From the beginning of our idea’s conception, we have always had a vision of setting an extremely high standard, with our practices and our design. To this end, we have consulted over 20 experts across a variety of domains, including healthcare, public health policy, micro-fluidics, and social entrepreneurship.

Precision Designed

Our Epinoma device uses a novel, capillary flow microfluidic platform that integrates your blood sample with state-of-the-art design of a smartphone-enabled apparatus that helps give you results. In addition to traditional CAD prototyping, we did extensive modeling of kinetics and dynamics to streamline our device’s design.

Thank You to Our Sponsers!