Access to Experimental Drugs

Experimental drugs can be a lifeline for those with conditions for which conventional treatments are not working or readily available. At the same time, doctors and patients want to have confidence that they are making safe and informed choices when requesting the use of drugs that have not have fully completed the clinical trial process.  With many doctors turning to experimental treatments for COVID-19 patients, this topic has recently gained renewed attention. Two processes in particular: compassionate use and Right to Try, give patients with serious or terminal conditions the ability to gain access to treatments which have not received FDA approval. These treatments can be potentially lifesaving for those whom conventional treatment is either unavailable or not working.

Compassionate use, formally known as Expanded Access, allows patients access to experimental treatments with approval from their doctor, the FDA, and an Institutional Review Board (IRB). The patient must meet several criteria, including having a serious disease or condition for which no comparable satisfactory treatment is available and being unable to enroll in clinical trials for the drug. If patients decide to pursue compassionate use, they must first speak to their physician, who then files a request to both the FDA and IRB. Eligibility is granted by the FDA if the agency determines that both (1) the benefits of using the experimental treatment outweigh any risks and (2) that its use will not jeopardize ongoing clinical trials. The FDA must respond to such a request within thirty days, and approval has historically been granted in 99% of cases. Secondly, the use must be approved by a registered IRB. Only once both of these steps are complete is the patient allowed access to the drug.

In May 2018 Congress passed the Right to Try Act, establishing a second process for patients to gain access to experimental treatments. Under Right to Try, patients with life-threatening conditions no longer need the approval of the FDA and IRBs to gain access to certain experimental drugs. Those with a terminal illness can submit a request directly to the manufacturer of an experimental treatment with the consent of their doctor. They may then obtain the treatment if the manufacturer approves. Similar to with compassionate use, patients using the Right to Try process must have exhausted all available conventional treatments and be unable to participate in clinical trails involving the experimental drug. The medication must also have completed Phase 1 clinical trials, an additional requirement not present in the compassionate use process. Right to Try has proven controversial in the scientific community since its conception. Proponents claim it cuts red tape patients for terminally ill patients in obtaining treatment, but critics point to the lack of reporting requirements and say that Right to Try removes safeguards in the compassionate use process that ensure patient safety.

While compassionate use and Right to Try have different processes, the programs share several key limitations. Importantly, manufacturers have no obligation to provide experimental drugs under either process, and the FDA has no power to compel companies to do so. Many manufacturers are reluctant to provide patients access to experimental drugs due to concerns that adverse reactions could lead to negative publicity or interfere with the FDA approval process.  Additionally, insurance companies are under no obligation to cover experimental treatments. The fact that many patients must pay out-of-pocket for experimental treatments has led to a stratified system where low-income patients are unable to obtain experimental drugs.

Despite these constraints, both compassionate use and Right to Try continued to be utilized by doctors and patients across the country. Many individuals with severe or terminal illness can’t afford to wait the seven to twelve years it takes for drugs to be approved by the FDA. Through compassionate use and Right to Try, these patients with few options left get a renewed chance.

Introduction to Artificial Intelligence and Healthcare

The healthcare industry generates a lot of data. X-rays, pathology slides, patient vitals, clinical trial information; we have mountains of information accessible at the touch of a button. But it’s costly and time-inefficient for humans to manually pour over it. So what do we do with all of this data?

The field of intelligence (AI) allows not only to let us analyze all our data, but to find subtle and complex patterns in them. Machine learning algorithms are particularly responsible for these advancements. Engineers have developed software that’s able to look at a dataset, find relationships between a bunch of variables, and then make mathematical models that we can use to predict behaviors in the future or analyze other sources of data: images, patient records, etc.

What does that mean in the real world? Computer scientists can make systems that can analyze an image and detect a disease better than humans can. They can make programs that are able to predict the notoriously unpredictable process of how proteins fold, or even make drugs which are currently in human trials. Let’s learn a little more about how machine learning works, and see some of the current applications.

How machine learning systems work

Machine learning systems are complex algorithms. Algorithms are methods of “treating” data: a computer receives an input, some sort of data. The computer recognizes that data and sorts it. For example, let’s say I have a program that can tell me if the color of an animal I’m thinking about makes sense. if I type in the phrase “blue horse,” there might be something in the code that recognizes the word “blue” and the word “horse.” The code then might have some information about the colors a horse can be, and would have an instruction to compare “blue” with “horse.” If “blue” isn’t in the “horse” database, then the computer would have an instruction to tell me “No, horses can’t be blue.” To make it simple, algorithms are sets of instructions that do something with information we give it.

AI Flow Chart

A simple algorithm for calculating interest. Courtesy of Edraw.

They get way more complex than that example. Specific algorithms can take ridiculous amounts of data and look for statistical relationships between them. Machine learning systems are able to make new models by using what are called learning algorithms. There are a bunch of different types, but the most conceptually simple ones involve supervised learning. These learning algorithms are exposed to a “training set” of data with a bunch of examples with known “right answers” — for example, a bunch of CT scan images from patients whom we know have cancer or not. The algorithm “doesn’t know” which patients have the disease. It keeps changing the instructions inside of its algorithm to try to — if the computer sees a white spot in a patient’s liver, it says yes, but this turned out to be wrong, so the next time the computer doesn’t care about that spot when saying yes or no.

Do this a bunch of times, and eventually the algorithm learns what data points lead to the correct output: the machine learns. Over time, these algorithms get very accurate, and we can use them for specific applications.

Radiology and imaging

Image analysis is a very natural application of this sort of software. The cancer example above isn’t science fiction: Google’s already developed a system that’s able to detect breast cancer. A very recent study published information about a deep learning model that’s able to diagnose forms of common hip arthritis at an accuracy rivaling radiologists’ analysis.

But there are concerns about the current state of radiology AI and bringing these technologies to the clinic. Analyzing images is a very complex process, critics argue, and we don’t always know how these machine learning systems actually work. Although applications are rapidly developing, it’s clear that radiologists are still very necessary.

Breast Cancer Image

A picture of an image where an AI system found cancer in a human breast. Courtesy of Northwestern University via The New York Times.

Drug discovery

UK-based startup Exscientia became the first company to develop a small-molecule drug entirely designed by artificial intelligence. Small-molecule drugs are tiny chemicals that generally “stick” to proteins of interest. It is very hard to know what sort of molecules will stick and treat a disease and which ones won’t. The scientists at Exscientia use a learning algorithm that takes data from human-run tests to optimize the structure of the chemical they’re making, reducing the amount of time it takes to get a working drug. The compound, titled DSP-181 and targeted toward treating obsessive-compulsive disorder, is set to enter clinical trials in Japan soon.

Point-of-care solutions

AI doesn’t just help us make drugs; it can help us deliver them, too. Electronic health record systems are growing more and more. Nurses say that bureaucratic work cuts their time spent with patients by about 25 percent. Doctors report that less than half of their patients are what they’d describe as “highly engaged” in their course of care. Engineers are already developing systems that can not only manage data, but use electronic information to make predictions about how patients might comply with certain treatments.

From point-of-care solutions and radiology to drug discovery and beyond, it’s clear that artificial intelligence will play an increasingly large role in analyzing healthcare data in the future in ways both known and unknown to us now. New applications of machine learning systems are rapidly developing as engineers aim to create new machine learning algorithms that can analyze and find complex data. Used in tandem with the expertise of doctors, radiologists, and other healthcare professionals, these algorithm-based technologies are already modernizing our healthcare system and have the potential to improve public health on an even larger scale in the future.

Finding Emory Innovations to Build Your Company’s Product Pipeline

Emory has approximately 600 technologies available to license at any given time. In particular, Emory offers a variety of live science resources such as therapeutics, diagnostics, and research tools that are marketed by Emory OTT.  

However, finding new technologies available at a university can be time-consuming and potentially frustrating for startups and established companies alike. Below are simple ways to find and remain up-to-date with technologies coming from Emory University.

  1. Subscribe to TechFeed to receive email notifications about products: TechFeed is a notification system where users can sign up to receive emails about recently added technologies. It can be individually customized to get notifications based on what products you’re interested in and how frequently you want to be notified. 

  2. Use our Technology Listings page: To get an improved searching experience with more accurate results, use our Google-powered search option. Through this, you can find non-confidential summaries of available technologies. Alternatively, if you’re looking for something around a specific indication or topic, click on Keywords in our word cloud and Technology Categories to get a list of these technologies.

  3. Visit our Featured Innovations page: Using these articlesable technologies.

  4. Contact our knowledgeable Marketing Associate, Quentin Thomas: Reach out to Quentin via email to request a hand-picked selection of technologies related to your needs and areas of interest. Quentin also encourages interested parties to set up a face-to-face conversation with him so he can guide the path from there. 

  5. Subscribe to our RSS feed and follow us on Twitter @Emory OTT: By doing this, you can stay up-to-date with all of our new technologies as soon as they’re listed on the website.

Additionally, to find a one-stop shop to find technologies from Emory as well as universities worldwide, there are a number of third-party listing services available to search free of charge, including the Association of University Technology Managers (AUTM) Innovation Market (AIM).

Our goal as technology matchmakers is to simplify the process for industry colleagues to find our technologies. If you have any suggestions on how we can improve this process, please contact us.

Announcements

Two important updates 

  1.  All staff in the Office of Technology Transfer are now working remotely, telecommuting. The office is still open for business and fully functional. Please reach out and we are ready to help. To find a complete staff listing go to our staff page on our website.

  2. Any new request for an Unfunded Research Contract should be sent to ott-mta [at] emory [dot] edu. Please fill out the appropriate questionnaire from our website to reduce processing time. The review of the agreement can not start until this information is submitted.

  3. Submitting a disclosure form can now be done on-line with our new tool called IdeaGate. Please go to the IdeaGate website to submit.

  4. The blog posts will slow down during this work from home period.

More Than Life Science Technologies

In 2011, Emory University was listed in the New England Journal of Medicine as the 4th largest contributor to drug discovery among public-sector research institutions. Even with this accomplishment, drug discoveries comprise about 35% of the 1,634 active technologies managed by the OTT. This indicates a powerful research program, where researchers also produce cutting-edge advances in diagnostic technology, medical devices, medical software, research tools, and more.

As such, the technologies the Office of Technology Transfer (OTT) markets and licenses are often life science technologies. This article exposits various non-medical technologies currently being marketed by OTT in an attempt to showcase work taking place in other corners of the university. Emory is known for strong research programs across each of its schools, from the College to the Rollins School of Public Health. The technologies below illustrate the work of Emory researchers outside of life sciences.

An Emory Information Security Scientist Improves Upon Institutional Phishing Prevention
With the roll-out of an award-winning Duo Two Factor authentication system, the Emory information security team has established itself as one of the leaders in its field. Naturally, its specialists would eventually turn their eye to “phishing” attacks – fraudulent emails purported to come from credible sources under the pretenses of extracting personal information. Recently, for those within Emory, you may have noticed “[External]” tags attached to emails sent from outside of the Emory network. This has been one method to weed out phishers and other scams. A few years ago, Elliot Kendall produced another method, this one meant to help build targeted education campaigns for Emory employees. His software improves upon the service provided by PhishMe, Inc., a phishing attack simulator meant to suggest how often employees provide sensitive information to illegitimate sources. Kendall found a way to combine PhishMe report data with institutional demographic data, such as email address or departmental building, in order to demonstrate where phishing-vulnerable employees were clustered. By understanding who exactly was falling for PhishMe’s fake phishing attempts, the information security team could directly work with affected respondents and provide them with the resources to avoid real phishing attacks in the future. Our office’s technology brief of the software can be found here.

Insecticide Applications from the Work of Emory Chemists
While searching for a novel therapeutic compound, Emory’s Erwin Van Meir, along with collaborator Binghe Wang from GSU, stumbled across a molecule capable of blocking mitochondrial complex I. “In the mitochondria, there is the electron chain transport that is part of how a cell makes its energy,” Dr. Van Meir told me. “The electron chain transport produces ATP through a process that goes through five different complexes. Complex I and II are generally seen as the root, where the others are dependent on their activity.” Cells can also make ATP through glycolysis, where glucose is converted to pyruvate, but only in small amounts. Furthermore, pyruvate sometimes converts to lactate, acidifying the surrounding environment and damaging other cells. This means that mitochondrial complex I is crucial for energy production, and its inhibition produces deleterious effects. In recent years, insecticide manufacturers have targeted the complex in their formulas, as its inhibition in insects would remove their presence from farmland. “Mitochondrial Complex 1 is really complex, comprised of roughly 50 different proteins, so it’s hard to know exactly where our molecule binds,” Van Meir furthered. “However, our molecule is also the most potent inhibitor that I’m aware of.” Greater potency allows for the deployment of lower doses, mitigating broader environmental consequences. Read our office’s technology brief for the compound here.

Air Detoxification Technologies Produced by Emory Researchers
As consumers pay more attention to environmentally harmful chemicals and their damaging impacts on human health, researchers have begun to search for ways to remove toxins from our surroundings. In a series of breakthroughs, Goodrich C. White Professor Craig Hill collaborated with postdocs and colleagues to develop various compounds that can detect, absorb, and detoxify harmful chemicals. One such technology is a polymer that transforms into a gel upon contact with toxins, entrapping and neutralizing them. Not only does the polymer change color upon detoxifying a substance, but its versatility allows for customization in selecting target chemicals. As referenced in our featured technology piece, Hill and his colleagues have continued to research the polymer and hope to perfect it further. Their development, however, is only the most recent in a line of other detoxification projects headed by Hill. Previously, Hill collaborated with Yurii Geletii, as well as a few postdocs, on a catalyst to neutralize nerve agents and other toxic substances. This technology, which is detailed further in our office’s brief, marked an innovation in solely requiring oxygen as a reagent. In the late 90’s, Hill worked with a graduate student to produce a fabric that could remove both gaseous and liquid contaminants from the ambient environment. Our office’s technology brief for the polymer can be found here.

Emory Researchers Inch Closer to a Hydrogen Economy
Another central focus of The Craig L. Hill Research Group is the development of materials for water oxidation. Our current mode of energy production burns hydrocarbons for fuel, which notoriously leaks carbon dioxide and other carbon pollutants into our atmosphere. As the combustion of hydrogen only produces clean water, hydrogen fuel has become a leading alternative for sustainable energy. This is also due, in part, to the known inefficiencies of solar power storage. Rather than rely on solar batteries, researchers have begun considering using sunlight to separate hydrogen molecules out of water and produce hydrogen fuel. This requires a water oxidation catalyst (WOC), a molecule that can perform the separation. Dr. Hill’s team at Emory debuted a polyoxometalate-based catalyst (technology brief here) that propelled the group to the forefront of their field. Not only were they the first research group to develop polyoxometalate for water oxidation, but they discovered that such a catalyst was more stable and efficient than any previous effort and highly cost-effective to produce. More recently, the Hill research group developed a new catalyst twice as efficient as their first WOC (technology brief here). These advances move towards a global-scale catalyst that could efficiently and sustainably shoulder humanity’s collective energy demand. No matter where the research community goes from here, if hydrogen fuel eventually becomes the global standard, it will be indebted to the work of Emory scientists.

Brain-Machine Interfaces, Deep Learning, and Neural Modulation

How biomedical neuroengineering can make our collective future brighter 

Eva Dyer’s research centers on machine learning and neuroscience, and developing computational methods that uncover principles governing the organization and structure of the brain. Chethan Pandarinath’s research focuses on neuroengineering, deep learning, brain-machine Interfaces, and neural coding, as applied to devices that assist people with disabilities and neurological disorders.

Dyer and Pandarinath, both assistant professors in Emory and Georgia Tech’s Coulter Department of Biomedical Engineering, were awarded 2019 Sloan Research Fellowships honoring early career scholars, “with a unique potential to make substantial contributions to their field.”

We spoke with them about their research, the future of biomedical engineering, and what brains and birds have in common.

Both of your research lies at the intersection of biomedical engineering and neuroscience. What is the big question about the brain right now?

Chethan Pandarinath

CP: My area of research is neuroengineering, which focuses on repairing the nervous system in cases of injury or disease and also on developing new tools or quantitative approaches to study the brain and further expand our understanding. We bring in cutting-edge computational techniques from computer science and artificial intelligence to better understand the brain, and then try to use these insights to develop new therapeutic approaches to treat brain injury or disease. There’s no question to me—this combination of new tools is going to fundamentally change how we understand the complex processes in the brain that make us who we are, and if we can start to compare these processes between healthy individuals and cases of injury and disease, we can develop new strategies for repairing the brain.

ED: One of the major questions that is driving my research is a question of heterogeneity and variability. In particular, when we study disease models, we would like to learn signatures of disease from data. Because brains are so different in their structure, however, they all produce different measurements. I am fascinated by how we can build expressive models that capture this variability to build better decisions about brain state and disease. This trend toward personalization in health care could end up being critical in the study of brain disease as well. With all of these topics and projects, engineering is critical because we need to design new data analysis tools that enable discovery in large and complex datasets.

You each have a background in electrical engineering and now work in the BME field. What do you find exciting about BME right now and where do you see BME heading in the future?  

CP: I think this is an unbelievably exciting time for our field. For a long time, neuroscience has been really limited by a lack of tools. The brain is incredibly complex, made up of billions of individual neurons that are intricately connected into powerful networks. Yet, in terms of neuroscientific experiments, we’ve mostly been able to study the activity of one or a handful of neurons at a time. When you’re staring at the activity of one neuron, it’s extremely challenging to say anything concrete about what a billion-neuron network is really doing. There is a confluence of factors now that promise to transform our understanding of the brain. On the one hand, we’re getting new tools that allow us to monitor many thousands of neurons simultaneously, and these capabilities are growing exponentially. When you can monitor the activity of 10,000 neurons for long periods of time, you start to create truly massive datasets, which will hopefully allow us to ask fundamentally different questions about how neural networks in the brain really work. At the same time, our ability to process complicated data has transformed over the last 6-7 years, thanks to the rise of a field of artificial intelligence known as “deep learning.” Now we can build artificial neural networks that are capable of processing large and complex datasets in very sophisticated ways, allowing us to uncover relationships in data that we’d never be able to pull out in the past.

Eva Dyer

ED: As we continue to see exponential growth in data analysis and the computational sciences, it has become increasingly attractive to bring these tools to bear on problems in biomedical research. BME is becoming increasingly dependent on the use of data for discovery – and this trend seems to only be growing in BME and other areas. BME is really about combining engineering and biology, and thus, as we continue to see problems arise that require that integration of engineering and biology, biomedical engineers will be at the forefront of many of these integrative innovations. As the size of datasets that are being generated in neuroscience continue to grow, it will be even more critical that we use machine learning and data-driven methods to help us uncover the mysteries of the brain. As we scale up our learning methods, we will be able to apply the lessons learned from simple controlled experimental tasks and scale these ideas to more realistic and naturalistic settings which will not place constraints on behavior. Being able to record and interpret the activity of neural populations “in the wild” will likely contribute to major breakthroughs in our understanding of the brain.

Where do you see your own research headed?

ED: A lot of the projects in my lab now focus on learning variability in large-scale neural datasets—this could be individual differences, changes in brain structure and function due to disease, or even changes that occur during learning or development. The aim is to develop automated systems that can navigate through large datasets and identifying changes that could be due to any of these factors. With automated approaches to discover changes in brain structure, even in light of individual differences, this will enable a new class of approaches for diagnosing disease and hopefully catching small changes at early stages in brain disease to address the problem early. I am excited about the possibility of leveraging information about the brain’s architecture to build and inspire the design of the next generation of deep learning architectures.

CP: Neuroengineering holds tremendous potential for developing new methods to help treat brain injury and disease. Traditionally, the options we’ve had for treating brain disorders are either medication or surgery. There’s a growing recognition that biomedical engineering solutions can play an important role here. We already have a rich history of using electrical stimulation in the brain, including deep brain stimulation for disorders like Parkinson’s disease, and cochlear implants to restore hearing for people who are deaf. Now we’re seeing emerging applications of closed-loop brain stimulation to epilepsy, depression, psychiatric disorders, and memory. We also have a rich history here at Emory. Mahlon DeLong, W.P. Timmie Professor of Neurology at Emory School of Medicine, who has been at Emory for decades, has laid down much of the scientific basis for how deep brain stimulation might be effective in Parkinson’s disease. Neurologist Helen Mayberg, who was here for quite a while before recently departing for University of Southern California, has been a pioneer in applying deep brain stimulation to other disorders like chronic depression. So I’m really excited by the team we have at the Emory Neuromodulation Technology Innovation Center (ENTICe), which brings together researchers from neurosurgery, neurology, and biomedical engineering, and also partners with folks at the GT Neural Engineering Center. We have an amazing team in place to develop the next generation of neuroengineering therapies for brain disorders.

If you wanted to convince a former colleague to move to Atlanta, what would be your top reasons?

CP: In terms of science, I love the community. As a member of the biomedical engineering department that spans Emory and GA Tech, I get to interact with wonderful colleagues at two very different institutions. Everybody here is extremely friendly and supportive. People genuinely want to interact and build collaborations and community and there’s not even a hint of competitiveness.

ED: I feel lucky to be part of a thriving community of neuroscientists, neuroengineers, and data scientists in Atlanta. Being part of both Georgia Tech and Emory provides exposure to a wide range of perspectives, plenty of opportunities for growth and collaboration, and what I perceive to be a lot of momentum around computational approaches to neuroscience.

If you could ask any person, dead or alive, to join your lab for a day, who would you ask?

ED: Richard Feynman. He was not only a brilliant scientist but also a dedicated teacher and mentor. It would be so cool to see him in action. He also created these diagrammatic representations of the behavior of subatomic particles called Feynman diagrams. Would be cool to see how he might think about visualizing and interpreting the types of problems that we are working on.

CP: One of the concepts we use in our lab a lot is called “dynamical systems theory”, which is a mathematical framework for understanding how complex systems behave. I think these approaches are key to understanding how the complex networks of neurons in the brain work. So I’d probably get a world-expert in dynamical systems, someone like Professor Steven Strogatz at Cornell, and force him to listen to me drone on and on about neurons until he caves and just tells us how to solve the brain.

A bonus question for CP: You’ve compared the behavior of neurons to the flocking of birds. How would you describe your research to someone who had no background in BME or neuroscience but doesgo bird-watching?

CP: So the activity of neurons and flocking behavior of birds has a little more in common than you might think. When you look at a flock of birds, you see these beautiful patterns pop out, and with complex, coordinated behaviors. Yet, there’s no one leader coordinating all of their activity and telling them what to do. You just have a bunch of individuals doing their own thing, but through very basic interactions, the group as a whole does something that’s tightly coordinated. This is what’s called emergent behavior, where putting relatively simple elements together can result in complex and coordinated activity. Neurons are very similar! You have a bunch of individual neurons that behave in certain ways, but the fact that they’re all wired up together and interacting with each other results in this coordinated, emergent system that is capable of doing really profound things. Another similarity here is that if I only showed you what one bird in a flock is doing, you’d have a hard time saying what the group as a whole is doing. But as you zoom out and start to observe more and more elements, the underlying patterns become clear. We think (and hope!) the same is true of neurons. My lab is monitors the activity of lots of neurons. Rather than focusing on what any one individual neuron is doing, we try to understand the coordinated activity of the network, and we try to really concretely understand how that network-level activity relates the brain’s control of behavior.

Courtney Shin

Student: My Experience Writing for OTT

I came across the listing for a Marketing & Communications Intern at the OTT on Handshake during the first weeks of my senior year at Emory. Before I read over the requirements for the job, I had never heard of OTT or even tech transfer. I always assumed that the fully realized technologies the school advertised were a natural extension of research and produced by faculty by their own volition. Clearly, I had no clue about the complexities of patents, intellectual property, licensing agreements, FDA approval, etc. Though I had a very limited background in biomedicine, the journalistic aspect of the job drew me in, and I was ecstatic when I was brought on board.

A whole year later, I can definitively say that working in OTT was one of my most worthwhile experiences at Emory. I’ve learned so much during my tenure, not only about medical technologies, chemistry, biology, and computer software, but also writing, editing, journalism, and science communication. What I found at OTT was an office full of deeply committed people who were always willing to talk about their work. Some of the most insightful feedback I’ve gotten on my writing has come from members of the OTT, like my supervisor Linda and the case managers, who set me up for my interviews with researchers. It was fascinating to see all the professional and academic backgrounds of people who pass through the office, whether it was chemistry PhDs or former lawyers and MBAs. If Emory is internationally renowned for its contributions to society and the medical field in particular, it is due in no small part to the efforts of each member of this team.

Every assignment I had for the OTT was a delight, an excuse to learn about some new topic I would never approach otherwise. Whether I was writing Featured Innovation pieces or blog posts on the inner workings of startups, I always felt like I was enriching myself. I loved talking to researchers and faculty, who were always wonderful and kind. As the year went on, I loved the opportunities I had to pitch and develop my own articles. Experiences like these have pushed me as a writer and I can truly say I’ve developed journalistic experience. It is a blessing to leave with such a varied portfolio of published work.

Whenever someone talks about the stature of Emory or the erudition of its faculty, the staff of OTT deserves to be mentioned in the same breath, as they have truly elevated the profession beyond the transactional. There is no Emory without OTT – it is a living core of the university.

— Kim Lee Miller

Emory Entrepreneurship and Venture Management

At the beginning of his past fall semester, Rain Tian ‘21BBA went to South Korea with his friends in what he thought would be a much-needed reprieve from the world of Emory’s campus. Once they arrived, however, Tian realized his friends were all tethered to the university – “Even when we were at home getting ready to go out, even when we were outside, they would be on their phone, messaging on Slack, working on EEVM stuff. I never saw that from any of the other clubs I’m in. When I’m having a lot of fun, I wouldn’t think of replying to a DM on Slack,” he said. Intrigued by this display of camaraderie, Rain joined EEVM, or Emory Entrepreneurship and Venture Management. In its promise of kinship, the club hasn’t failed – “Honestly, I resonate and vibe with the community so well… In EEVM, we post photos of our adventures. I went on Spring Break with a lot of EEVM people.”

If you’ve spent enough time on Emory’s campus, chances are you’ve spotted a student wearing a HackATL t-shirt. This business-minded hackathon is the flagship event of EEVM and regularly draws in hundreds of eager students from all over the country, expanding its yield each year. The momentum from HackATL has allowed EEVM to position itself as the central resource for aspiring entrepreneurs on campus. As told by Naam Srisaard ‘19BBA, former Director of HackATL and now an advisor to the executive board, “We are the only student-run entrepreneurship organization at Emory University. We run at the university level, so we are not under College Council or the Goizueta Business School. We serve the entire university and our mission is to provide entrepreneurial resources for any and every student that is interested in entrepreneurship, startups, pursuing their business idea, or even if they’re just interested in the industry.”

Founded only five years ago, the club now offers a startup accelerator program, a co-working space on the Clairmont Campus, an online publication, and more. Most importantly, the club offers a community to its members, who are united by a passion for innovation. Take Daniel Kessler ‘22C, whose knack for entrepreneurship was first uncovered in elementary school. “The NYC Sanitation Department ran a competition to see which elementary school could implement the best sustainability project.,” he told me. “I used Apple technology to create a database that graded each classroom’s sustainability and we actually won.” Kessler saw EEVM as a natural extension of his interests in “using entrepreneurship to better the lives of others and address social ills.” Since joining, he has ascended to the position of Director of Corporate Partnerships, along with Tian, and is responsible for securing sponsorships for HackATL and other EEVM events. In a testament to EEVM’s stature, the Student Programming Council recently contacted them for help in recruiting restaurants for this year’s Taste of Emory.

If EEVM is a community, it is organized around an ideology of self-actualization, which is considered best brought about in a collaborative environment. “We aim to promote entrepreneurship because we believe that everyone could have the next idea to change the world. We hope to give entrepreneurs the resources to realize their vision,” Tian told me. Entrepreneurship is cast as an inner awakening, one that transforms the world in the process, as expressed in Kessler’s view that “When I look at entrepreneurship or technology, I don’t see it as the implementation of accumulated knowledge. I see it as a comprehensive expression of who we are as people and how we can amplify our best selves using these tools.”

Srisaard echoed these sentiments, portraying entrepreneurship as future-minded and uniquely suited for the modern world – “Everyone is all about entrepreneurship because the traditional corporate business model is fading away. That alone calls for a more innovative mindset, design thinking, reiterative sprints of new ideas.” In her definition of entrepreneurship as “knowing how to identify problems and solve them,” she poignantly characterized entrepreneurship as an all-purpose model for diagnosis and treatment, the optimal road to meaningful change.

EEVM’s inclusive view of entrepreneurship removes it from the corporate board rooms and venture capitalist dreams one frequently associates it with. Anyone can be an entrepreneur and EEVM is ready to guide their journey. EEVM’s democratization of an industry often requiring connections and capital is reflected in the success of their events. Speaking on her experience competing in HackATL, Michelle He ‘22C said “I came into HackATL with the misconception that hackathons are limited to those with coding abilities or an interest in computer science. In the most wonderful way, HackATL proved me wrong… It has an incredibly accessible registration process (that is completely free!) and gives students a very holistic overview of the entrepreneurial process. I really enjoyed getting to work with other college students of vastly different strengths and interests to create a product that I am very passionate about.”

The club has similarly empowered its members, as Srisaard told me that “being in EEVM is like being in a startup. There isn’t a single lesson it taught me, but it gave me the experience of being in a fast-paced environment where everyone is just as driven as you. Someone might see we won’t have enough money for the future, so we go out hustling, selling ramen in the library. It teaches you that startup grind, that founder’s mentality where if you care about it, you get it done.” Next year, she will start work as a consultant at Ernest & Young, undoubtedly propelled as a candidate by her remarkable work for the club. Tian also found that “talking to sponsors has made me more confident about job interviews. My first networking call was supposed to go for thirty minutes, but I was so nervous it lasted less than ten. Now, the hardest part for me is actually waiting for a reply. Once I get it and can talk to a person, I immediately get into my comfort zone.” By creating a network of excited young entrepreneurs on campus, EEVM meaningfully trains students to engage in the career path of their choice.

What lies ahead for EEVM? This past April, participants in their startup accelerator presented new ideas at a Demo Day held at the Goizueta Business School. Envisions, EEVM’s design-thinking consultancy group, is currently wrapping up work on an app that will help first-year students, new arrivals from Oxford, and transfer students become better acclimated to campus. Kessler, who is on the Envisions team, shared his hope that he could help new students “find resources to unleash their full potential.”

As for the more distant future, Tian hopes to “increase member engagement so that people will be working with their friends with a common goal in mind.” Kessler yearns “to engage more meaningfully with the community around us, to use the skills of EEVM members to serve the broader Atlanta community in their entrepreneurial efforts, beyond just Emory students.” In this direction, the club is considering community service and non-profit organizations to affiliate with and exploring the possibility of a digital platform that would provide information and video resources to help aspiring entrepreneurs. Srisaard simply hopes that “EEVM can live up to its full potential and touch every student’s life, across every school at Emory, not just those currently interested in entrepreneurship.” In this world, the name of the game is growth.

Interested readers can access EEVM’s website, their Facebook page, or their Twitter.

10 Unusual Holiday Traditions from Around the World

As the holiday season approaches, families everywhere gear up for their yearly rituals. And while you might think some of your family’s practices are idiosyncratic, trust that enough unique traditions exist out there to make your aunt Ellen’s Christmas ramen look as festive as a snow-swept street. To honor our commitments to tradition, as the holidays are meant to do, we at the OTT have compiled some of the more left-field celebrations from around the world.

  1. The Mummering of Newfoundland
    Brought to Newfoundland by British settlers, “mummering” currently enjoys a resurgence in popularity. The practice had faded due to its tendency to incite violence. But in the last 30 years, rural populations have brought it back in good spirits. To “mummer,” one dons an elaborate costume and joins a small group in knocking on neighbors’ doors. Upon invitation into a home, the “mummers” prompt a merry celebration. If a homeowner correctly guesses the true identity of a mummer, their mask comes off before they leave for the next house. The tradition is practiced during the Twelve Days of Christmas, but some mummers might make you think you’ve been transported back to spooky October.

  2. The Yule Cat of Iceland
    Folklore is central to the holidays – whether it’s canonized by carols or stories traded over the dinner table. In Iceland, folklore dictates the importance of the Yule Cat, a giant, vicious predator that emerges to eat anyone who hasn’t received new clothes before Christmas Eve. While the Yule Cat sounds outrageous, its popularity interestingly originates in the labor history of Iceland. Farmers yearned to incentivize wool workers to process all autumn wool before winter hit. Workers who completed their share received new items of clothing. Thus, the Yule Cat, who could weed out slow workers, was circulated.

  3. Chinese Food on Christmas in NYC
    New York City hosts the largest Jewish community outside of Israel, but Jews still comprise only 13% of the official population. So, although the city never sleeps, one might be hard-pressed to find many businesses open on Christmas Day. Thus, the convergence of two demographics – Chinese non-Christians working in the restaurant industry and Jews looking for somewhere to eat. This uniquely urban linkage began in New York’s old Lower East Side where Chinese and Jewish immigrants once lived in close proximity. Today, however, Jews carry the torch simply by needing food on Christmas Day. Plus, who could resist such a delicious ritual.

  4. The El Gordo of Spain
    The El Gordo, officially known as Sorteo Extraordinario de Navidad, is a national lottery held in Spain on Christmas Day. The El Gordo is remarkable as the second-longest continuously running lottery in the world and biggest lottery worldwide as measured by total prize payout. Even during the Spanish Civil War, the government managed to organize the El Gordo, with opposition parties throwing an El Gordo of their own. We sanctify the holidays as a time of charity and graciousness, but it’s fun to throw a little gambling in the mix, particularly when the payoff is so alluring.

  5. SantaCon in the U.S.
    There’s nothing novel or unusual about Santa Claus, likely the most ubiquitous figure during the month of December. But what about dressing up as Santa for a day long pub crawl in the city of your choice? And if you were joined by hundreds, often thousands, of other Santas? Meet SantaCon, the rowdy tradition that’s struck urban centers across the country. On this day, Santa look-a-likes flood the streets to celebrate the holidays, but mostly to drink. The other traditions on this list are regarded with a nostalgic fondness – but SantaCon, not so much due to the noise and mess it brings.

  6. KFC Dinner in Japan
    As one might expect, Christmas is not widely celebrated in Japan. But while the island nation has largely passed on the Western holiday, it’s offered a warmer welcome to the season’s connotative consumerism. Initially debuted in 1974, the KFC Christmas Dinner was meant to cater to homesick Americans who wound up in Japan for the holiday season. Since then, the demand has boomed, and the chain now requests that customers place their Christmas order at least two months in advance. Through sheer marketing genius, KFC has convinced the Japanese public that their chicken-and-a-side meals are a holiday fixture in the States, creating a new tradition across the Pacific in the process.

  7. The Gävle Goat of Sweden
    The Gävle goat stands proud in the center of the town that provides its namesake – Gävle, Sweden. Each year, local community groups come together to build a massive goat from straw to honor the traditional Swedish Yule Goat. This tradition might seem mild and good-spirited, but it has birthed a parallel, more pernicious occurrence. The Gävle goat suffers from a chronic vandalism problem, having been burned to the ground by arsonists 38 out of the 52 times it has been erected since 1966. This year’s goat went up on December 2nd, and we’ll all be holding our breath hoping it makes it past Christmas Day.

  8. The Giant Lantern Festival of the Philippines
    Every year, the people of San Fernando in the Philippines come together to host the event that has earned them the title of “Christmas Capital of the Philippines.” This festival lasts through the latter half of December and originated as a means for neighborhoods throughout the province to display their communal light works. As technology advanced over time, allowing for larger lanterns and light displays in the decorations, the festival became an in-demand location to visit and see. Now, lanterns are made from steel frames that can sometimes pack over 5000 lightbulbs to make for beautiful, seasonal displays of craftsmanship.

  9. Santa Descends in France
    Santa climbs down chimneys all over the world, but once a year he makes a special stop in Douaia township located in the north of France, to rappel down the city’s belfry tower. Since 1966, Santa has made this yearly descent, likely getting more exercise than he’s used to in the sleigh. The local tradition is meant in part to honor the belfries of Douai, considered some of the most impressive in the country. Sadly, in recent years, the celebration has had to relocate to Douai’s Hotel Du Dauphin after a young man tragically fell from the belfry during a rehearsal last winter.

  10. Priscilla the Pig in Atlanta
    Priscilla the Pig has been adored by the Atlanta population for 65 years now, originally debuted at the historic Rich’s Department Store and now housed by the Macy’s in Lenox Square. Whereas Priscilla initially toured Rich’s toy department, she now lives in a tent on the top deck of the Macy’s parking garage where she showcases a wondrous installation for children and parents alike. And not only does Priscilla occupy a special place in Atlanta’s winter heart, but the desegregation of Rich’s, and the monorail ride specifically, in 1961 was seen as one of the largest advancements by the Civil Rights Movement at the time.

Healthcare, Big Data, and Emory

From our phones to wearable devices, modern technology allows us to both collect and analyze data like never before. In healthcare, reams of data are collected from a number of sources; often there is too much information for patterns and trends to stand out to the human eye. Up until recent advances in data analysis the use and benefits of such “big data” was difficult and the potential benefits to patients and research remained obscured. Although the relationship between healthcare and big data is still in its early phases, researchers at Emory and all over the globe are using previously developed knowledge of health science and pairing it with computer science to extend the abilities of those working in modern healthcare.

Big data describes data sets that are so vast that computational analysis is required to derive meaning from them. Because public health is built around finding trends and links between an abundance of factors, this technology is a useful tool. It gathers information and uncovers connections with extreme efficiency, although the computers are not working alone, but in concert with humans. The National Institutes of Health (NIH) All of Us research program is teaming up with research institutions like Emory all over the country to gather data on nearby populations.

Michael Zwick, PhD, assistant dean of research at Emory School of Medicine and assistant vice president of research at Woodruff Health Sciences Center, is principally overseeing Emory’s role in the All of Us Research Program with the help of Arshed Quyyumi, MD, Greg Martin, MD, James Lah, MD, PhD, Andrew Post, MD, PhD, and Alvaro Alonso, MD, PhD. They are making an effort to include as much of the population as possible to increase the accuracy of the research, ensuring underserved communities that are otherwise rarely considered are included. Big data, with the help of some of the top minds at Emory and other institutions, will help make sense of the social and health experiences of millions of people in an effort to improve lives.

While big data can be applied to populations, collecting and efficiently interpreting large amounts of data can also be helpful when applied to the individual. When it comes to our health, our bodies have a multitude of measurable responses to ailments and illnesses. Some are telltale signs and some are subtle, interconnected, and difficult to identify. Emory researchers like Timothy Buchman, MD, PhD director of the Center for Critical Care (ECCC) and Shamim Nemati, PhD assistant professor the Department of Biomedical Engineering are using technology to help monitor patients’ statuses while in critical condition, taking some of the weight off the shoulders of staff and leading to stronger accuracy of diagnoses and predictions. Buchman founded the ECCC and recently initiated Emory’s electronic ICU (eICU), a patient data monitoring system that has a specific taskforce in charge of overseeing the process and work in conjunction with the other ICU staff. He is currently working on a streaming analytics system that looks for patterns in real-time patient data and alerts medical personnel of crises like heart failure, sepsis, or pneumonia.

Nemati’s work is in much the same field, but with a focus on sepsis. Sepsis occurs when the body overcompensates for infection, causing rampant inflammation. It is a severe, life-threatening complication that causes more deaths in the United States than breast cancer, prostate cancer, and AIDS combined. It is vital to catch it as early as possible to lessen the potential for death. Nemati and his colleagues are working on monitoring algorithms that can predict the onset of sepsis very early using measurements from more than 65 different indicators. By interpreting these measures in concert with one another, computers can predict sepsis up to 12 hours ahead of time, better than any previously developed sepsis prediction technology. The computers are “trained” on years of Emory ICU admission data to be as accurate as possible.

The application of big data concepts extends beyond physical ailments. Ying Guo, PhD, director of the Center for Biomedical Imaging Statistics at Emory, is looking to create analytical tools that search for and find biosignatures in brain scans that identify abnormalities such as mental illnesses, addiction, and cognitive issues. The data being collected from brain scanning technologies (fMRIs, sMRIs, DW-MRIs) is getting continually more sophisticated with vast amounts of data contained within a single scan, far too much for an individual to fully interpret. Guo and her collaborators at the Emory School of Medicine are developing algorithms that filter through the immense amount of data from scans in search of signs and trends that point to cognitive dysfunctions. Guo’s work aims to combine information from various types of scans to achieve more holistic understanding of the cognitive functioning of patients. This multi-modality imaging is already proving helpful to other researchers. Tanja Jovanovic, PhD, of Grady Hospital has used Guo’s technology to validate her previous findings concerning the brains of PTSD patients. Guo is also extending her work to characterize data sets collected to study subtypes of depression and therefore can be used to develop and train Guo’s algorithms.

The interconnection between technology and healthcare is only just beginning. The work being done by programs like the All of Us research and other big data projects by Emory researchers are exciting fusions between computer science and health science. These will open pathways for the researchers, scientists, and healthcare providers of the future, and will continue to lead to safer and more capable healthcare practices.

Works Cited