Your Questions Answered About Kids, Teens, and Covid Vaccines
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
On May 13th, scientific and medical experts will discuss and answer questions about the vaccine for those under 16.
This virtual event convened leading scientific and medical experts to address the public's questions and concerns about Covid-19 vaccines in kids and teens. Highlight video below.
DATE:
Thursday, May 13th, 2021
12:30 p.m. - 1:45 p.m. EDT
Dr. H. Dele Davies, M.D., MHCM
Senior Vice Chancellor for Academic Affairs and Dean for Graduate Studies at the University of Nebraska Medical (UNMC). He is an internationally recognized expert in pediatric infectious diseases and a leader in community health.
Dr. Emily Oster, Ph.D.
Professor of Economics at Brown University. She is a best-selling author and parenting guru who has pioneered a method of assessing school safety.
Dr. Tina Q. Tan, M.D.
Professor of Pediatrics at the Feinberg School of Medicine, Northwestern University. She has been involved in several vaccine survey studies that examine the awareness, acceptance, barriers and utilization of recommended preventative vaccines.
Dr. Inci Yildirim, M.D., Ph.D., M.Sc.
Associate Professor of Pediatrics (Infectious Disease); Medical Director, Transplant Infectious Diseases at Yale School of Medicine; Associate Professor of Global Health, Yale Institute for Global Health. She is an investigator for the multi-institutional COVID-19 Prevention Network's (CoVPN) Moderna mRNA-1273 clinical trial for children 6 months to 12 years of age.
About the Event Series
This event is the second of a four-part series co-hosted by Leaps.org, the Aspen Institute Science & Society Program, and the Sabin–Aspen Vaccine Science & Policy Group, with generous support from the Gordon and Betty Moore Foundation and the Howard Hughes Medical Institute.
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Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
To Speed Treatments, Non-Traditional Partnerships May Be the Future
A handshake between a scientist and a businessman.
Drug development becomes even more complex as time passes. Increased regulation, new scientific methods, coupling of drugs with biomarkers, and an attempt to build drugs for much more specific populations – even individuals – all make clinical development more expensive and time-consuming. But the pressure is also constantly increasing to develop new, innovative medicines faster. So companies invest more dollars, with steadily decreasing yields in terms of such drugs on the market.
"Collaborations are in many cases the only possible solution--a powerful force driving old and new models."
The traditional models for clinical development are thus not producing the best results. Can collaboration between companies, academic institutions, and public (government and non-profit) organizations help solve the problem?
Collaboration has in fact yielded important developments in diagnostic and therapeutic products. However, truly collaborative efforts are in the minority. Particularly for biotech, diagnostic, device and pharmaceutical companies with stock traded on the public markets, or with funding from venture capital, private equity, or other investment-oriented platforms, there are strong drivers for limiting collaboration.
Particularly onerous are intellectual property (IP) concerns. Patent attorneys are normally terrified of collaborations, where the ownership of IP may be explicitly or implicitly impaired. Investment banks and fund managers are very nervous about modeling financial returns on new products where IP is shared. Development companies often have overt or implied policies greatly favoring internal development over collaboration. It could be argued that the greatest motivation behind the huge product in-licensing game is the desire to fully own product rights rather than to continue collaborations where the rights are not exclusive.
Bu the good news is that long-standing models and newer innovations in collaboration do work. Some examples are worth exploring. A huge influence currently on collaboration models across the spectrum is the revolution in immuno-oncology. More cash has gone into the development of drugs which enlist the immune system to attack cancer than any other field of drug development in history, some estimate by a factor of three. The great majority of current human clinical trials in the U.S. are in this field. There are over 200 separate drugs in development that attack a single target, PD-1--completely unprecedented. Due to the vast complexity of the human immune system, and also to the great promise that these drugs have shown in previously intractable cancers, the field has recognized that these drugs can only perform to full potential when used in combination. But the rationale for combinations is very obtuse, there are huge numbers of new drug targets and candidates, and there are many hundreds of institutions and companies involved in development of these combinations. Thus, collaborations are in many cases the only possible solution--a powerful force driving old and new models.
"As drugs have become more expensive, a huge drive has emerged, spurred by the brokers of health care, to limit the populations eligible to be prescribed an expensive new drug."
As marketing and reimbursement become increasingly complex, large commercial companies share the marketing of more products. Almost every large pharmaceutical and biotech company has products which are jointly sold with others.
Some pharmaceutical companies do a creditable job, often driven by ethical rather than economic concerns, of identifying drugs in their commercial or development portfolios which would be best in the hands of others, or which should be combined with products owned by others to achieve maximum patient benefit. Pfizer, for example, has a strong internal culture of not allowing products to become "dormant" in its hands, and actively seeks to collaboratively develop or license out such products.
Particularly in the immuno-oncology field, given the lack of firm knowledge about which combinations will work best in patients, both large and small companies are collaborating on both preclinical and clinical development. Merck, with its drug Keytruda, the leading anti-PD-1, has almost 1000 collaborative trials in progress. In most cases, the IP rights to a successful combination are not specified up-front; the desire is to see what works and deal with the rights and financial issues later.
Other companies have specifically engaged non-profit foundations and/or public bodies in collaborative efforts. This is of course not new--there is a very long history of pharmaceutical, diagnostic, and device companies either collaborating with the NIH or disease-focused foundations for development of products born from institutional research. The reverse is also true--both the NIH and foundations are often engaged to collaborate on development of products owned by industry. Sometimes these collaborations can be relatively complex. For example, Astra-Zeneca, Sloan Kettering, the Cancer Research Institute, and the National Cancer institute have engaged in a partnership to conduct clinical trials on combination cancer therapies involving the portfolio owned by Astra-Zeneca in combination with drugs owned by others, with device therapies and procedures, and with diagnostic products.
As drugs have become more expensive, a huge drive has emerged, spurred by the brokers of health care--the so-called 'insurance' companies and pharmaceutical benefit managers--to limit the populations eligible to be prescribed an expensive new drug. Thus, the field of "companion diagnostics" has crystallized. In a number of fields, including cardiology, urology, neurodegenerative disease, and oncology, developers of diagnostics and drugs seek each other out to jointly develop drug/diagnostic pairs which appropriately select patients for treatment. The number of such collaborations is escalating dramatically, although many large pharmaceutical companies have their own in-house programs.
"The lack of clinical trial data sharing has engendered some notable collaborative efforts."
But most large pharmaceutical companies are not in the business of selling diagnostic products, even if those products are so closely linked to a specific drug that they are included in the FDA-approved 'label' of that drug. As a result, some very collaborative relationships are emerging. Merck, which has a very large and active companion diagnostics development group, almost always seeks development and commercialization partners for internally innovated diagnostics – to the extent that the company actually gives away the rights and the commercial benefits of the diagnostic product. Such was the case with the Merck-developed Tau imaging agents related to Alzheimer's disease, which Merck made available without license to the entire industry. The company continues to drive such non-financial collaborations in other clinical disciplines.
Collaborations certainly take place between academic centers, but in comparison to others, they are few and of far less productive outcome. Many appear to be innovative and have great potential, but the results are often different. The collaboration between medical schools and research institutions in Northeast Ohio seems promising, but it is in large part just a means for gathering hard-to-find clinical trial patients into the giant local institutions, Case Western and the Cleveland Clinic. And the actual output of academic versus commercial development programs is usually poor. One new company recently did an exhaustive search for new clinical drug development candidates in a specific therapeutic area in academia and came up empty-handed, only to find a solid handful of candidate drugs "hiding" in pharmaceutical companies that they were willing to provide collaboratively or to license.
The lack of clinical trial data sharing has engendered some notable collaborative efforts. The Parker Institute for Cancer Immunotherapy initially set out to promulgate standards for clinical trial data collection to make trial results in the thousands of combination trials more comparable. However, after some initial frustration, they are now working collaboratively with biotech companies, academia, and pharmaceutical companies to drive forward specific combination trials that experts believe should be done.
Foundations and public organizations also enable or initiate collaborative research. The Prostate Cancer Foundation has aggressively put academic and hospital-based research institutions together with industry to push the development of new effective therapies and diagnostics for prostate cancer, with remarkable success. The Veterans Administration has recently embarked on an aggressive program of collaborations with industry (with the help of funding from the Prostate Cancer Foundation) to allow use of the VA population and the very complete patient records to start clinical trials and other development efforts that would otherwise be very difficult.
"The near future will bring some surprising collaborative successes in the development of new drugs, devices, and diagnostics, but of course, some serious disappointments as well."
Finally, the financial industry at times facilitates collaborations, although they are usually narrow. Fund managers often get two or more of their portfolio companies to pool assets and/or IP to push forward more rapid development, or to provide structure for developments that otherwise could not go forward due to size or other resource limitations. For example, Orbimed, a health-care-focused investment firm, consistently drives cross-company development efforts within its large portfolio of drug and device companies.
So collaborative efforts are very much alive and well, which is great news for patients. Current realities in science, politics, reimbursement, and finance are driving diversity in collaborative arrangements. The near future will bring some surprising collaborative successes in the development of new drugs, devices, and diagnostics, but of course, some serious disappointments as well. And the very negative influence of the IP profession on collaborations will not be soon defeated.
Big Data Probably Knows More About You Than Your Friends Do
A representation of the digital lifestyle prevalent today that enables the collection of a wealth of data.
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.