Data is the new oil. It is highly valuable, and it is everywhere, even if you're not aware of it. For example, it's there when you use social media. Sharing pictures on Facebook lets its facial recognition software peg you and your friends. Thanks to that software, now anywhere you visit that has installed cameras, your face can be identified and your actions recorded.
The big data revolution is advancing much faster than the ones before, and it carries both promises and perils for humanity.
It's there when you log into Twitter, posting one of the 230 million tweets per day, which up until last month were all archived by the Library of Congress and will be made public for research. These social media data can be used to predict your political affiliations, ethnicity, race, age, how close you are with your family and friends, your mental health, even when you are most likely to be grumpy or go to the gym. These data can also predict when you are apt to get sick and track how diseases are spreading.
In fact, tracking isn't limited to what you decide to share or public spaces anymore. Lab experiments show Comcast and other cable companies may soon be able to record and monitor movements in your house. They may also be able to read your lips and identify your visitors simply by assessing how Wi-Fi waves bounce off bodies and other objects in houses. In one study, MIT researchers used routers and sensors to monitor breathing and heart rates with 99% accuracy. Routers could soon be used for seemingly good things, like monitoring infant breathing and whether an older adult is about to take a big tumble. However, it may also enable unwanted and unparalleled levels of surveillance.
Some call the first digital pill a snitch pill, medication with a tattletale, and big brother in your belly.
Big data is there every time you pick up your smartphone, which can track your daily steps, where you go via geolocation, what time you wake up and go to bed, your punctuality, and even your overall health depending on which features you have enabled. Are you close with your mom; are you a sedentary couch potato; did you commit a murder (iPhone data was recently used in a German murder trial)? Smartphone-generated data can be used to label you---and not just you, your future and past generations too.
Smartphones are not the only "things" gathering data on you. Anything with an on and off switch can be connected to the internet and generate data. The new rule seems to be, if it can be, it will be, connected. Washing machines, coffee makers, medical appliances, cars, and even your luggage (yes, someone created a self-driving suitcase) can and are often generating data. "Smart" refrigerators can monitor your food levels and automatically create shopping lists and order food for you—while recording your alcohol consumption and whether you tend to be a healthy or junk food eater.
Even medicines can monitor behaviors. The first digital pill was just approved by the FDA last November to track whether patients take their medicines. It has a sensor that sends signals to a patient's smartphone, and others, when it encounters stomach acid. Some call it a snitch pill, medication with a tattletale, and big brother in your belly. Others see it as a major breakthrough to help patients remember to take their medications and to save payers millions of dollars.
Big data is there when you go shopping. Credit card and retail data can show whether you pay for a gym, if you are pregnant, have children, and your credit-worthiness. Uber and Lyft transactional data reveal what time you usually go to and leave work and who you regularly visit (Uber data has been used to catch cheating spouses).
Amazon now sells a bedroom camera to see your fashion choices and offer advice. It is marketing a more fashionable you, but it probably also wants the video feed showing your body measurements—they're "a newly prized currency," according to the Washington Post. They help retailers create more customized and better fitting clothes. Amazon also just partnered with Berkshire Hathaway and JPMorgan Chase, the largest bank in the United States by assets, to create an independent health-care company for their employees--raising privacy concerns as Amazon already owns so much data about us, from drones, devices, the AI of Alexa, and our viewing, eating, and other purchasing habits on Amazon Prime.
Data generation and storage can also be used to make the world better, safer and fairer.
Big data is arguably a new phenomenon; almost all the world's data (90%) were produced within the last 2 years or so. It is a result of the fusion of physical, digital, and biological technologies that together constitute the fourth industrial revolution, according to the World Economic Forum. Unlike the last three revolutions, involving the discoveries of steam power, electrical energy, and computers—this revolution is advancing much faster than the ones before and it carries both promises and perils for humanity.
Some people may want to opt out of all this tracking, reduce their digital footprint and stay "off the grid." However, it is worth noting that data generation and storage can be used for great things --- things that make the world better, safer and fairer. For example, sharing electronic health records and social media data can help scientists better track and understand diseases, develop new cures and therapies, and understand the safety and efficacy profiles of medicines and vaccines.
While full of promise, big data is not without its pitfalls. Data are often not interoperable or easily integrated. You can use your credit card practically anywhere in the world, but you cannot easily port your electronic health record to the doctor or hospital across the street, for example.
Data quality can also be poor. It is dependent on the person entering it. My electronic health record at one point said I was male, and I was pregnant at the time. No doctors or nurses seemed to notice. The problem is worse on a global level. For example, causes of death can be coded differently by country and village. Take HIV patients: they often develop secondary infections, like TB. Do you record the cause of death as TB or HIV? There isn't global consistency, and political pressure from patient groups can exert itself on death records. Often, each group wants to say they have the most deaths so they can fundraise more money.
Data can be biased. More than 80 percent of genomic data comes from Caucasians. Only 14 percent is from Asians and 3.5 percent is from African and Hispanic populations. Thus, when scientists use genomic data to develop drugs or lab tests, they may create biased products that work for only some demographics. Take type 2 diabetes blood tests; some do not work well for African Americans. One study estimates that 650,000 African Americans may have undiagnosed diabetes, because a common blood test doesn't work for them. Using biased data in medicine can be a matter of life and death. Moreover, if genomic medicine benefits only "a privileged few," the practice raises concerns about unequal access.
Large companies are selling data that originated from you and you are not sharing in the wealth.
We need to think carefully and be transparent about the values embedded in our data, data analytics (algorithms), and data applications. Numbers are never neutral. Algorithms are always embedded with subjective normative values--sometimes purposely, sometimes not. To address this problem, we need ethicists who can audit databanks and algorithms to identify embedded norms, values and biases and help ensure they are addressed or at least transparently disclosed. Additionally, we need to determine how to let people opt out of certain types of data collection and uses—and not just at the beginning of a system, but also at any point in their lifetimes. There is a right to be forgotten, which hasn't been adequately operationalized in today's data sphere.
What do you think happens to all of these data collected about us? The short answer is the public doesn't really know. A lot of it looks like what is in a medical record—i.e. height, weight, pregnancy status, age, mental health, pulse, blood pressure, and illness symptoms--- yet, it isn't protected by HIPPA, like your medical record information.
And it is being consolidated into the hands of fewer and fewer big players. Large companies are selling data that originated from you and you are not sharing in the wealth.
A possible solution is to create an app, managed by a nonprofit or public benefit corporation, through which you could download and manage all the data collected about you. For example, you could download your credit card statements with all your purchasing habits, your Uber rides showing transit patterns, medical records, electric bills, every digital record you have and would like to download--into one application. You would then have the power to license pieces or the collection of your data to users for a small fee for one year at a time. Uses and users could be monitored and audited leveraging blockchain capabilities. After the year is up, you can withdraw access.
You could be your own data landlord. We could democratize big data and empower people to better control and manage the wealth of information collected about us. Why should only the big companies like Amazon and Apple profit off the new oil? Let's create an app so we can all manage our data wealth and maybe even become data barons—an app created by the people for the people.
In late March, just as the COVID-19 pandemic was ramping up in the United States, David Fajgenbaum, a physician-scientist at the University of Pennsylvania, devised a 10-day challenge for his lab: they would sift through 1,000 recently published scientific papers documenting cases of the deadly virus from around the world, pluck out the names of any drugs used in an attempt to cure patients, and track the treatments and their outcomes in a database.
Before late 2019, no one had ever had to treat this exact disease before, which meant all treatments would be trial and error. Fajgenbaum, a pioneering researcher in the field of drug repurposing—which prioritizes finding novel uses for existing drugs, rather than arduously and expensively developing new ones for each new disease—knew that physicians around the world would be embarking on an experimental journey, the scale of which would be unprecedented. His intention was to briefly document the early days of this potentially illuminating free-for-all, as a sidebar to his primary field of research on a group of lymph node disorders called Castleman disease. But now, 11 months and 29,000 scientific papers later, he and his team of 22 are still going strong.
On a Personal Mission<p>In the science and medical world, Fajgenbaum lives a dual existence: he is both researcher and subject, physician and patient. In July 2010, when he was a healthy and physically fit 25-year-old finishing medical school, he began living through what would become a recurring, unprovoked, and overzealous immune response that repeatedly almost killed him.</p><p>His lymph nodes were inflamed; his liver, kidneys, and bone marrow were faltering; and he was dead tired all the time. At first his doctors mistook his mysterious illness for lymphoma, but his inflamed lymph nodes were merely a red herring. A month after his initial hospitalization, pathologists at Mayo Clinic finally diagnosed him with idiopathic multicentric Castleman disease—a particularly ruthless form of a class of lymph node disorders that doesn't just attack one part of the body, but many, and has no known cause. It's a rare diagnosis within an already rare set of disorders. Only about 1,500 Americans a year receive the same diagnosis. </p><p>Without many options for treatment, Fajgenbaum underwent recurring rounds of chemotherapy. Each time, the treatment would offer temporary respite from Castleman symptoms, but bring the full spate of chemotherapy side effects. And it wasn't a sustainable treatment for the long haul. Regularly dousing a person's cells in unmitigated toxicity was about as elegant a solution to Fajgenbaum's disease as bulldozing a house in response to a toaster fire. The fire might go out (though not necessarily), but the house would be destroyed.</p><p>A swirl of exasperation and doggedness finally propelled Fajgenbaum to take on a crucial question himself: Among all of the already FDA-approved drugs on the market, was there something out there, labeled for another use, that could beat back Castleman disease and that he could tolerate long-term? After months of research, he discovered the answer: sirolimus, a drug normally prescribed to patients receiving a kidney transplant, could be used to suppress his overactive immune system with few known side effects to boot.</p><p>Fajgenbaum became hellbent on devoting his practice and research to making similar breakthroughs for others. He founded the Castleman Disease Collaborative Network, to coordinate the research of others studying this bewildering disease, and directs a laboratory consumed with studying cytokine storms—out-of-control immune responses characterized by the body's release of cytokines, proteins that the immune system secretes and uses to communicate with and direct other cells. </p><p>In the spring of 2020, when cytokine storms emerged as a hallmark of the most severe and deadly cases of COVID-19, Fajgenbaum's ears perked up. Although SARS-CoV-2 itself was novel, Fajgenbaum already had almost a decade of experience battling the most severe biological forces it brought. Only this time, he thought, it might actually be easier to pinpoint a treatment—unlike Castleman disease, which has no known cause, at least here a virus was clearly the instigator. </p>
Thinking Beyond COVID<p>The week of March 13, when the World Health Organization declared COVID-19 a pandemic, Fajgenbaum found himself hoping that someone would make the same connection and apply the research to COVID. "Then like a minute later I was like, 'Why am I hoping that someone, somewhere, either follows our footsteps, or has a similar background to us? Maybe we just need to do it," he says. And the CORONA Project was born—first as a 10-day exercise, and later as the robust, interactive tool it now is. </p><p>All of the 400 treatments in the CORONA database are examples of repurposed drugs, or off-label uses: physicians are prescribing drugs to treat COVID that have been approved for a different disease. There are no bonafide COVID treatments, only inferences. The goal for people like Fajgenbaum and Stone is to identify potential treatments for further study and eventual official approval, so that physicians can treat the disease with a playbook in hand. When it works, drug repurposing opens up a way to move quickly: A range of treatments could be available to patients within just a few years of a totally new virus entering our reality compared with the 12 - 19 years new drug development takes.</p><p>"Companies for many decades have explored the use of their products for not just a single indication but often for many indications," says Stone. "'Supplemental approvals' are all essentially examples of drug repurposing, we just didn't call it that. The challenge, I think, is to explore those opportunities more comprehensively and systematically to really try to understand the full breadth of potential activity of any drug or molecule."</p>
The left column shows the path of a repurposed drug, and on the right is the path of a newly discovered and developed drug.
Cures Within Reach
A Confounding Virus<p>The FDA declined to comment on what drugs it was fast-tracking for trials, but Fajgenbaum says that based on the CORONA Project's data, which includes data from smaller trials that have already taken place, he feels there are three drugs that seem the most clearly and broadly promising for large-scale studies. Among them are <a href="https://www.thelancet.com/journals/lanres/article/PIIS2213-2600(20)30503-8/fulltext" target="_blank" rel="noopener noreferrer"><u>dexamethasone</u></a>, which is a steroid with anti-inflammatory effects, and <a href="https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-drug-combination-treatment-covid-19" target="_blank" rel="noopener noreferrer"><u>baricitinib</u></a>, a rheumatoid arthritis drug, both of which have enabled the sickest COVID-19 patients to bounce back by suppressing their immune systems. The third most clearly promising drug is <a href="https://www.nih.gov/news-events/news-releases/full-dose-blood-thinners-decreased-need-life-support-improved-outcome-hospitalized-covid-19-patients" target="_blank" rel="noopener noreferrer"><u>heparin</u></a>, a blood thinner, which a recent trial showed to be most helpful when administered at a full dose, more so than at a small, preventative dose. (On the flipside, Fajgenbaum says "it's a little sad" that in the database you can see hydroxychloroquine is still the most-prescribed drug being tried as a COVID treatment around the world, despite over the summer being <a href="https://www.nejm.org/doi/full/10.1056/NEJMoa2021801" target="_blank" rel="noopener noreferrer"><u>debunked</u></a> widely as an effective treatment, and continuously since then.)</p><p>One of the confounding attributes of SARS-CoV-2 is its ability to cause such a huge spectrum of outcomes. It's unlikely a silver bullet treatment will emerge under that reality, so the database also helps surface drugs that seem most promising for a specific population. <a href="https://jamanetwork.com/journals/jama/fullarticle/2773108" target="_blank" rel="noopener noreferrer"><u>Fluvoxamine</u></a>, a selective serotonin reuptake inhibitor used to treat obsessive compulsive disorder, showed promise in the recovery of outpatients—those who were sick, but not severely enough to be hospitalized. <a href="https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2772185" target="_blank" rel="noopener noreferrer"><u>Tocilizumab</u></a>, which was actually developed for Castleman disease, the disease Fajgenbaum is managing, was initially written off as a COVID treatment because it failed to benefit large portions of hospitalized patients, but now seems to be effective if used on intensive care unit patients within 24 hours of admission—these are some of the sickest patients with the highest risk of dying. </p><p>Other than fluvoxamine, most of the drugs labeled as promising do skew toward targeting hospitalized patients, more than outpatients. One reason, Fajgenbaum says, is that "if you're in a hospital it's very easy to give you a drug and to track you, and there are very objective measurements as to whether you die, you progress to a ventilator, etc." Tracking outpatients is far more difficult, especially when folks have been routinely asked to stay home, quarantine, and free up hospital resources if they're experiencing only mild symptoms. </p><p>But the other reason for the skew is because COVID is very unlike most other diseases in terms of the human immune response the virus triggers. For example, if oncology treatments show some benefit to people with the highest risk of dying, then they usually work extremely well if administered in the earlier stages of a cancer diagnosis. Across many diseases, this dialing backward is a standard approach to identifying promising treatments. With COVID, all of that reasoning has proven moot. </p><p>As we've seen over the last year, COVID cases often start as asymptomatic, and remain that way for days, indicating the body is mounting an incredibly weak immune response initially. Then, between days five and 14, as if trying to make up for lost time, the immune system overcompensates by launching a major inflammatory response, which in the sickest patient can lead to the type of cytokine storms that helped Fajgenbaum realize his years of Castleman research might be useful during this public health crisis. Because of this phased response, you can't apply the same treatment logic to all cases.</p><p>"In COVID, drugs that work late tend to not work if given early, and drugs that work early tend to not work if given late," says Fajgenbaum. "Generally this … is not a commonplace thing for a virus." </p>
Thursday, March 11th, 2021 at 12:30pm - 1:45pm EST
On the one-year anniversary of the global declaration of the pandemic, this virtual event will convene leading scientific and medical experts to discuss the most pressing questions around the COVID-19 vaccines. Planned topics include the effect of the new circulating variants on the vaccines, what we know so far about transmission dynamics post-vaccination, how individuals can behave post-vaccination, the myths of "good" and "bad" vaccines as more alternatives come on board, and more. A public Q&A will follow the expert discussion.
SPEAKERS:<img lazy-loadable="true" data-runner-src="https://leaps.org/media-library/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTY3Mzc4NS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY0NjYwNjU4NX0.Tdrh5pze5P4XxgiJK3J4JFrsrijfabIzNJz-AATghDE/image.jpg?width=534&coordinates=365%2C3%2C299%2C559&height=462" id="87554" class="rm-shortcode" data-rm-shortcode-id="b6c7311be7aec25807f9af19b683bf1d" data-rm-shortcode-name="rebelmouse-image" data-width="534" data-height="462" />
Dr. Paul Offit speaking at Communicating Vaccine Science.commons.wikimedia.org<p><strong><a href="https://www.research.chop.edu/people/paul-a-offit" target="_blank" rel="noopener noreferrer">Dr. Paul Offit, M.D.</a>, is the director of the Vaccine Education Center and an attending physician in infectious diseases at the Children's Hospital of Philadelphia. He is a co-inventor of the rotavirus vaccine for infants, and he has lent his expertise to the advisory committees that review data on new vaccines for the CDC and FDA.</strong></p>
Dr. Monica Gandhi
UCSF Health<p><a href="https://profiles.ucsf.edu/monica.gandhi"></a><strong><a href="https://profiles.ucsf.edu/monica.gandhi" target="_blank">Dr. Monica Gandhi, M.D., MPH,</a> is Professor of Medicine and Associate Division Chief (Clinical Operations/ Education) of the Division of HIV, Infectious Diseases, and Global Medicine at UCSF/ San Francisco General Hospital.</strong></p>
Dr. Onyema Ogbuagu, MBBCh, FACP, FIDSA
Yale Medicine<p><strong><a href="https://medicine.yale.edu/profile/onyema_ogbuagu/" target="_blank" rel="noopener noreferrer">Dr. Onyema Ogbuagu, MBBCh</a>, is an infectious disease physician at Yale Medicine who treats COVID-19 patients and leads Yale's clinical studies around COVID-19. He ran Yale's trial of the Pfizer/BioNTech vaccine.</strong></p>
Dr. Eric Topol
Dr. Topol's Twitter<p><strong><a href="https://www.scripps.edu/faculty/topol/" target="_blank" rel="noopener noreferrer">Dr. Eric Topol, M.D.</a>, is a cardiologist, scientist, professor of molecular medicine, and the director and founder of Scripps Research Translational Institute. He has led clinical trials in over 40 countries with over 200,000 patients and pioneered the development of many routinely used medications.</strong></p>