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

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<h2>Incorporating a Novel Communication Paradigm for iGEM Teams</h2>
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        <h2>Putting the larger questions into context</h2>
<p> As a new team, we looked to past teams who had engaged in stakeholder interactions and Integrated Human Practices to guide our own intuition. Our team quickly realized that often times, other teams simply spoke to other domain experts or end users without having a fully thought-out approach that would allow for integration of advice into project design and deployment. It was also important to realize that a lot of the narratives that teams put forward were extremely linear: the interactions did not invite the team to consider the impact of their decisions or help them optimize their overall design. </p>
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        <p>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. </p>
<p> In our day-to-day operations, we also experienced the struggles of cross-team discussion. It was quite difficult for people in the wetlab to keep track of what the drylab team was doing, or to keep track of what the entrepreneurship group was trying to deploy. It was also sometimes difficult to ascertain the broad-scale impact of our interactions with certain experts or stakeholders. We were also sure that our team was not the only one to experience such difficulties. To resolve these issues, our team came up with a novel paradigm that we believe will help streamline project issues for future teams. </p>
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        <h2>How can we gather a holistic perspective about the fundamentals of cancer diagnostics?</h2>
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        <p>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.</p>
<p> Similar to the design-build-test cycle that Imperial College introduced in 2006, our team believes that although there is a continuous flow of information and need for integration into the project, we can create three phases for the project with the following methodology.  </p>
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        <h2>How can we maximize our impact in the communities that we are trying to help?</h2>
<h3>Recognize</h3>
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        <p>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. </p>
<p> From the scientific method, something that every elementary school student has learned, it is important to use observations (personal and those of others) to identify problems and then seek solutions</p>
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<p>Recognize can be split into two cyclical elements:</p>
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        <p>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.</p>
<h4>Problem Definition </h4>
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        <h2>What factors do we have to consider when implementing our vision in different settings?</h2>
<p> Identify the particular space that you are interested in/ the area that the problem resides and begin to use foundational literature to understand core elements of the problem: Why does it exist? Does the problem differ across different settings? Why is this? </p>
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        <p>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.</p>
<h4> Constraint determination</h4>
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        <p>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.</p>
<p> Although knowing about the problem you are trying to solve is important, it is important to realize that the problem does not exist in a vacuum; it exists because the real world imposes some sort of constraint (technical, environmental, social, etc.) that prevents the solution from being implemented in the ideal manner.</p>
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        <h2>How do we ensure the safety of our system? Are there any other ethical considerations? </h2>
<p> Although there are several different types of constraints, as mentioned above, we encouraged ourselves and future teams to first nail down the specific technical constraints that exist. There are several different approaches to constraint determination. Focusing on the values that are important to you as an individual and to your entire time can help guide your decision-making process. </p>
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        <p>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.</p>
<p> Stakeholder identification can also dictate who you should talk and about the topic of discussion; a stakeholder is defined as anyone who may be impacted by your activity or may be impacted by someone who is directly impacted by your activity. As a diagnostics team, our challenge was to bridge the gap in communication between engineers and medical professionals: to address this, we spoke with healthcare professionals, synthetic biologists, academia, industry professionals and executives over the course of our project. Our initial interactions focused on the technical challenges of designing our methodology, especially the need for a non-invasive cancer detection technology that did not rely on chemical treatment. </p>
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        <p>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.</p>
<h3> Develop</h3>
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        <h2>How can we be better scientists?</h2>
<p> After defining the technical parameters of the project, it is important to consider to see how this actually impacts the solution development aspect of one’s project. Often times, teams already have a pre-conceived notion for the problem space they are trying to address. In order to clear the barriers for innovation, it is of utmost importance that the team begin to shape this unrefined idea <b>after</b> each of the initial stakeholder interactions rather than prior.  </p>
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        <p>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. </p>
<p> Development can also be split into two cyclic elements:  </p>
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<h4> Modeling and Visualizations </h4>
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<p><object width="100%" height="600px" data="https://static.igem.org/mediawiki/2018/0/08/T--UC_San_Diego--diversityr.pdf"></object></p>
<p> Modeling is everyone’s best friend, especially an iGEM team’s because it allows for further characterization of a part, device, or a system before actually using resources to build it. For us, it was important to be able to visualize the development of our solution to make sure it fit into the technical parameters that we had determined beforehand. Diagnostics teams can use modeling to check for the validity of their project via a bottom-top approach: protein modeling and an understanding of Michaelis - Menten kinetics can help provide validity of genetic circuit design; further modeling can characterize an entire system (i.e. if a team is developing components for a microfluidic device), and also provide an ecosystem overview that demonstrates the impact of disease monitoring. </p>
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<h4> Genetic Circuit Design </h4>
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        <h2>How can we use education to further advance synthetic biology?</h2>
<p> Although people often think that this step is all about the wetlab scientists and benchwork, it is actually a collaborative endeavor: feedback from earlier modeling and visualization can lead to tweaks or optimizations in the circuit design itself. </p>
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        <p>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.</p>
<h3> Deploy </h3>
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<h4> Strategy Development  </h4>
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<p> After the validation of the genetic circuit, the next step, especially for teams in Diagnostics, Environment, Food and Energy, and Manufacturing tracks is to develop a strategy for implementation in the real-world. Here, teams should consider the other category of constraints (social, resource-based, financial, etc.). We call these dimensional considerations . By thinking about entrepreneurial considerations or what it will take to implement your solution with minimal resources, teams will help guide the evolution of their project in a more pragmatic direction.  </p>
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<p> One thing to keep in mind is that sometimes talking to these stakeholders may uncover information that changes a foundational assumption and sends you back to the drawing board. 
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It can be disheartening at first, but it is important to use this as a learning lesson and as a pivot for the direction of your project. </p>
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<h4> Communication </h4>
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<p> Scientists are notoriously bad communicators, and this extends to iGEM teams as well. To help resolve this, it is important to identify your audience and determine what their most crucial needs are. Why are you presenting this information to them and what are they hoping to get out of it? The goal of effective communication is to make sure that each party gets something out of it: it is important to make sure that the information given is clearly described without logical missteps and is effectively delivered. </p>
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<p> This brings us to our second sub-component of communication: communication through design. Especially as iGEM members, our most effective platform for communicating our results is through the wiki, and too often, too much technical depth and information is provided. After identifying your target audience(s), it can be difficult to tailor the information specifically through them, but that is where information design can be a very powerful tool. Make sure that your graphics are clean and communicate a single concept at a time; much like good writing, it’s important to allow your reader/viewer the opportunity to digest the information at their own pace and to communicate just what is necessary, nothing more, nothing less. </p>
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<p> The beauty of our approach is that all parts are ongoing at all times! We encourage teams to use this paradigm and take a non-linear approach to stakeholder interactions, and we hope that it will be of great benefit to teams going forward.  </p>
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<h2> Reflecting on the Key Outcomes of this Paradigm </h2>
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<h3> Development of a biomarker discovery tool  </h3>
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<p> As a result of this paradigm, we uncovered a critical lag in the development of commercially available liquid biopsy tests. One of the reasons was that scientists and clinicians did not have a centralized methodology for determining biomarkers of interest for specific diseases. Instead, labs would independently identify these markers and then publish papers to communicate their results. Our team believed that because our idea approached cancer diagnostics from a completely new angle and with the development of an uncommon diagnostic metric, it would be important to create a modular biomarker discovery tool that can analyze any existing methylome data and can also integrate existing datasets from The Cancer Genome Atlas. </p>
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<h3> Expansion of our workflow to integrate a digital health platform </h3>
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<p> In addition to addressing a core issue in cancer diagnostics, our team’s exploration of the patient care journey led us to identify another significant economic burden on our healthcare system: doctors are unable to ascertain if a treatment has been effective or not long enough because of poor doctor-patient communication. To address this issue, our team developed a functional prototype of a digital health platform. </p>
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<h3> Development of novel use cases </h3>
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<p> Although clinicians cautioned us that using promoter methylation as a diagnostic indicator could impact the overall accuracy of our test, implementation of novel signal amplification strategies helped address many of these concerns. In addition to implementing our idea as a early screening tool, our interactions with industry professionals and social innovators led us to the realize the value of hypermethylation’s continuous nature. As such, we were able to develop a novel use case centered around post-therapy response. </p>
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<center><h2>IHP Flowchart</h2></center>
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<center><h2>Expert Interviews</h2></center>
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<h3> UCSD Health System </h3>
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<p> We were fortunate enough to be active in the clinical immersion process. Although the names of the patients are covered for confidentiality purposes, we were able to gain an in-depth perspective of a cancer patient’s journey throughout the diagnostics journey. We understood that patient normally goes through the following stages: prognosis, diagnosis, verification through companion diagnostics, and post-therapeutic monitoring. The most common method of identifying cancer would be to take a tissue biopsy, and there were a number of issues here for patients: <b>namely the invasiveness and the price point</b>. They also talked about the <b>significant emotional cost</b> that a patient and their family face during this journey. A secondary concern was that a <b>long turnaround time</b> may impede treatment . After talking to several clinicians, they also mentioned that tissue biopsies are not always the best option, as they can <b>spread cancers</b> in certain instances or they might <b>cause further complications</b>. In addition, often times, the first biopsy may result in inconclusive diagnosis, and attempting a second biopsy may present risks. </p>
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<h4>Takeaway:</h4>
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<p> At this point, our team was able to see that the gold standard or “status quo” was clearly not enough in the cancer diagnostics space. There was an issue of invasiveness, price point, and overall accuracy. </p>
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<h3> Poorya Sabounchi, internal affiliate with Illumina Accelerator  </h3>
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<p> Dr. Cashin currently serves as the head of the Illumina Accelerator and Dr. Sabounchi is a startup advocate. Dr. Sabounchi helped answer some of our key questions about next-generation sequencing technology. In addition to describing the mechanisms of NGS, he also talked about some of the key diagnostic metrics that Illumina and GRAIL, a liquid biopsy startup by Illumina, are currently focusing on. He explained that <b>NGS uses deep sequencing runs in order to identify mutations, perform whole-genome sequencing</b>, and believes that they can identify mutations at a better rate than existing practices. He also walked us through some of the companies in the Illumina accelerator and how they were able to harness the power of NGS for improving genomics. </p>
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<h4>Takeaway:</h4>
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<p> Our conversation with Dr. Sabounchi helped us understand the promise of next-generation sequencing. Although NGS could resolve the price point, it did not address one of the key patient concerns, namely the invasiveness. We felt that we could somehow engineer the CRISPR protein to detect mutations and then give us a readout that we could quantify. </p>
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<h3> Pranav Singh, Bioinformatics Team, GRAIL </h3>
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<p> After speaking with the Illumina Accelerator, we felt that it would be important to understand some of the current alternatives. We reached out to some members of the bioinformatics team at GRAIL to get a better sense of what they do. They first introduced the idea of liquid biopsy, which is given to the collective procedures that amount to non-invasive cancer detection techniques. We learned that the inherent tumor heterogeneity and ability of cancer genomes to evolve are not properly captured by tissue specimens. GRAIL instead looks at cell-free DNA that is shed by cells and is trying to develop highly accurate. The team also took some time to explain their day to day operations and explained that bioinformatics is becoming exceedingly important due to the massive amounts of data per patient. They use bioinformatics to derive patterns that can generate further clinical insight or help develop more effective treatments in the future.  </p>
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<h4>Takeaway:</h4>
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<p> After learning from GRAIL, we understood that despite its limitations, liquid biopsy seems to be more advantageous and addresses many of the concerns we had uncovered earlier. As a team, we decided to shift from tissue specimen analysis to liquid biopsy because of the inherent challenges with the molecular heterogeneity. </p>
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Latest revision as of 01:59, 18 October 2018

Human Practices Silver

hpSilver

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.