Difference between revisions of "Team:UC San Diego/Human Practices Silver"

Human Practices Silver

Putting the larger questions into context

As a team, we realized that too often, scientists end up doing “science in a vacuum”, where their technological innovations don’t translate because of real world parameters. To avoid that, our team set out to answer some central questions that our team faced throughout our journey. In particular, our team wanted to rigorously test the design of our project when faced with real world constraints. Through our interactions, we got to explore some of the more salient issues related to social innovation, intellectual property, sustainable, user-centered design, and scalability. Rather than just be passive learners in each of these domains, we took deliberate action in each realm to make a more cohesive project, even including education as a key cornerstone of our activities.

How can we gather a holistic perspective about the fundamentals of cancer diagnostics?

Our team took a stakeholder-focused approach for our project from the beginning, getting clinicians’ perspectives on addressing the root of an important issue in cancer diagnostics. We took the unusual step of using epigenetic determinants as a primary indicator of cancer. To gain a better sense of the overall space and get advice from industry professionals, we talked to several individuals at some of the world’s biggest biotechnology companies such as Roche, Illumina, and Genentech. We also talked to individuals in academia to understand some of the crucial variables that we had to consider when designing and optimizing our genetic circuits. From talking to angel investors and venture capitalists, we also came to realize the importance of the However, it was important to realize that there was a broader picture here, namely the deployment of our innovation in the real world.

How can we maximize our impact in the communities that we are trying to help?

Because we were working with hepatocellular carcinoma, we wanted to get a better understanding of the communities that were most impacted by the disease. Literature research showed us that within the United States, Hispanic individuals and individuals of lower socio-economic research were disproportionately impacted by this disease. By reaching out to the Social Innovation Program at UC San Diego and meeting with Ms. Naila Chowdhury, we were able to get a better sense of the challenges in the social innovation sector. Her advice helped us realize that a big challenge of our idea was getting people to put aside their fear of genetically modified organisms and embrace this new treatment method. Especially in the medical world, clinicians often resist change and are slow to adopt new technologies for fear of disruption to the status quo. To gain an understanding of how this plays out on an international stage, we also met with one of the main figures at the world’s largest philanthropic groups, the TATA Board in India to discuss how we could further our impact. They also suggested that (1) education and (2) access to better resources would be the key going forward. As a result, we have done meticulous research to compile a policy brief on improving healthcare in low-resource communities. We also participated in the Global Empowerment Summit where we shared our vision for using synthetic biology to advance cancer diagnostics.

In addition, our team focused on building a modular workflow for cancer diagnostics. To this end, the first part of our vision was an unsupervised machine learning algorithm that aids in biomarker discovery. Although our approach was tailored for hepatocellular carcinoma based on the input data, our algorithm is applicable for any disease with documented methylome data. We then harness this in silico tool to guide our design in the wetlab as we can design probes that are complementary to the regions of hypermethylation that we are examining. From there, the digital health platform can be integrated across existing platforms, allowing ease of access and convenience to potential users.

What factors do we have to consider when implementing our vision in different settings?

In talking to TIGS, they also pointed us to consider the different use cases: the environment for implementation is very different when it is a clinical researcher in a large, centralized government laboratory compared to a low-resource clinic in a remote region. As a result, they introduced us to the ASSURED criteria, a set of guiding principles that should be considered for clinical implementation of point-of-care devices. This means that they should be affordable, specific and sensitive (both indicators of diagnostic accuracy), user-friendly, robust (rigorously tested in a variety of settings), equipment-free, and deliverable.

In designing our microfluidic system, we were able to meet most of these criteria as the rigor of our assay and machine learning system had already been validated. The one factor that we were unable to meet was equipment-free as the methodology and the amplification strategies that we wanted to use required standard laboratory equipment. One of our goals going forward will be to further miniaturize our technology and meet this requirement.

How do we ensure the safety of our system? Are there any other ethical considerations?

Paramount to the success of any clinical test is its diagnostic accuracy and its safety. No clinician will endorse a test that has potential harm, and no patient will want to try such a test. When we also considered the fact that there was a general stigma around GMOs, a faster timeline for wide scale implementation would be possible if we used a cell-free system. Some of the inherent advantages of a cell-free system are that the protein production can be optimized more easily, and it is also easier to control.

Another part of our workflow also posed an interesting conundrum. Our team thought there was great promise for the digital health component in our workflow; however, it soon became apparent that data privacy and patient confidentiality is a significant concern in today’s world that hinders early adoption of our workflow. To address these issues, our team did an in-depth analysis of HIPAA regulations and current data standards to make sure that our functional prototype would adhere to these specific standards.

How can we be better scientists?

Our team wanted to perform an introspective analysis of our iGEM journey. We realized that in addition to coming up with an amazing project and interacting with such a diverse group of stakeholders, it was important to consider our team’s activities. It was important to foster an inclusive environment; although we all come from different backgrounds with different strengths and weaknesses, it was crucial that we respect one another and try to learn from each other. As several of our team members came from traditionally under-represented groups, we became more aware of the issues of women and LGBTQ+ empowerment in the sciences and came up with a four point engagement plan that we hope future iGEM teams and the iGEM foundation will incorporate into their practices.

How can we use education to further advance synthetic biology?

Lastly, our team knew that large spikes of change are very rare: it is only through incremental improvement and learning from the past that we are able to move forward. As a result, our team designed a very strong platform for education and empowerment of students of all ages and backgrounds, including a cohesive textbook that covers relevant, appealing topics in biology as well as a condensed periodic table of synthetic biology elements as a primer for students who are curious about core elements and principles. Our entire public engagement and outreach initiative can be found on the Public Engagement section of our wiki.