With over 27 million confirmed cases worldwide and over 1 million deaths (over 12 million confirmed cases and 250,000+ deaths in the U.S. alone), the #COVID19 pandemic has not only upended life, economies, industries and the world-at-large as we know it but is also the largest public health catastrophe we will most likely experience in our lifetime.
Fortunately, scientists, drug makers, and the government are moving at an expeditious rate to develop a vaccine to stop COVID-19 in its tracks.
Here are the three most promising vaccines on the horizon awaiting FDA approval and their advantages and potential risks for consideration, along with a dive into how advanced analytics and AI can be leveraged to help position, distribute, and administer these life-saving vaccines.
1.RNA Genetic Vaccine from BioNTech and Pfizer
The genetic vaccine based on an experimental approach called mRNA involves injecting part of the COVID-19 virus’ genetic code into the body to train the immune system. This triggers a generation of antibodies and T-cells within the body to destroy the infected cells and fight COVID-19.
Pfizer expects to produce 50 million doses worldwide in 2020 and up to 1.3 billion doses in 2021.
Advantage: Clinical trials reveal that the mRNA genetic vaccine has a 90% efficacy (according to the press release), but the data needs to be analyzed further and validated which will be done by the FDA as part of the Emergency Use Authorization that Pfizer is going to apply for.
Potential risks: The mRNA vaccine needs to be stored and kept at –70 degrees Celsius (–94 degrees Fahrenheit), and once transferred to a refrigerator, it must be administered within five days. This demands a “cold supply chain” for distributing the vaccine and getting it to hospitals and pharmacies for administration. This introduces a huge risk since the vaccine can lose its efficacy if not stored at the -70-degree temperature. Pfizer has invested over $2B to produce special thermal coolers to store and transport the vaccine over dry ice with temperature monitoring from “production to administration.”
2.RNA Genetic Vaccine mRNA-1273 from Moderna
Moderna is an American biotech firm founded in 2010, based in Cambridge, MA, where their focus is on drug discovery, development, and vaccine technologies based on the messenger RNA (mRNA) technique. Its novel technology platform inserts synthetic viral mRNA into living cells which then reprograms the cells in the human body to develop their own immune responses. Incidentally, no mRNA drug has ever been approved for human use, so this, much like the Pfizer mRNA vaccine, is precedent setting. Moderna received over $ 1.5B from the U.S. government’s “Operation Warp Speed” to deliver 100M doses of the vaccine with the option to purchase an additional 400M doses on demand.
Moderna’s vaccine must be shipped at –20 degrees Celsius (–4 degrees Fahrenheit), and it can then be stored at that temperature for six months. Once thawed and kept in a refrigerator between two and eight degrees Celsius (36 to 46 degrees Fahrenheit), it is good for up to 30 days.
The company intends to manufacture 20 million doses in 2020 and 500 million to 1 billion in 2021. The Moderna vaccine will be distributed by McKesson (one of the three largest pharma distributors in the U.S.) who has been designated as the official distributor for vaccines in the U.S. by the government.
Advantage: The Moderna vaccine reduced the risk of COVID-19 infection by 94.5%. There were 95 cases of infection among patients in the company’s 30,000-patient study. Only five of them occurred in patients who developed COVID-19 after receiving Moderna’s vaccine, mRNA-1273.
Potential risks: Moderna has not produced or delivered a single drug or vaccine since its inception in 2010, so there is a healthy level of skepticism regarding its ability to deliver and scale a mRNA vaccine for which there has been no precedent.
A person receiving either mRNA vaccine (Pfizer or Moderna) will need two doses, administered three or four weeks apart.
3.The Viral Vector Vaccine from AstraZeneca, developed at the Oxford University in the UK
The Oxford University-developed vaccine being manufactured and marketed by AstraZeneca uses a completely different approach than the mRNA vaccines developed by Pfizer and Moderna.
This is a genetically modified common cold virus that is used to infect chimpanzees. It has been altered to stop it causing an infection in people and to carry the blueprints for part of the coronavirus, known as the “Spike Protein.”
Once these blueprints are inside the body, they start producing the coronavirus’ spike protein, which the immune system recognizes as a threat and tries to squash it and prevent the virus from replicating inside the body.
Advantage: The Oxford University-developed AstraZeneca vaccine is a third of the price of the Pfizer vaccine and costs one fifth the price of the Moderna vaccine. The technology is far more mature, and the vaccines can be stored in a refrigerator and distributed to every corner of the world, including developing countries in Asia, Latam, and Africa.
Potential risks: With two doses, the vaccine has shown an efficacy rate of only 70% relative to the 95% efficacy from the Pfizer and Moderna vaccines, but researchers believe that they can get to an efficacy of 90% by tweaking the dose.
How will Policy Makers, Public Health Agencies and Healthcare Organizations Leverage Advanced Analytics and AI?
The most compelling event of 2021 will be the FDA Emergency Authorization of these (and other) COVID-19 vaccines validated for safety through clinical trials, and then positioning, distributing, and administering them to a majority of the 320 million Americans as well the 7 billion people across the globe, prioritized based on risk.
As well, these patients will need to be monitored for potential adverse events triggered by the vaccine, which will need to be captured thru an Adverse Event Management System (AEMS) and reported back to the FDA and the manufacturer(s), to potentially halt distribution and administration, if needed.
Key Questions That Advanced Analytics and Artificial Intelligence (AI) can Address
(A). Who are the patients most at risk of contracting COVID-19, and who should be prioritized for the vaccine(s)?
- Use Case: Segment and stratify the U.S. population by zip code based on risk (demographics, co-morbidities, socio-economic determinants of health)
- Use Case: Can we correlate and map high-risk patients in a state/city/county/zip code by the strain of COVID-19 persistent there?
(B). Where do these patients reside, and do they have access to quality healthcare facilities?
- Use Case: Segment high-risk patients based on their proximity to the nearest healthcare facility, especially in rural and community areas
- Use Case: For patients who are not near hospitals, can the USPS/UPS/FEDEX distribute vaccines and therapeutics in a safe, risk-free manner, while ensuring the efficacy of the vaccine?
- Use Case: Are their retired or mobile nurses who can be recruited to administer these vaccines safety to these patients and monitor them post-administration of the vaccines?
(C).What kind of treatment or vaccines would work best for each of these segments of the high-risk population?
- Use Case: Correlate and map high-risk patients to classes of treatment and therapeutics available – vaccines, therapeutics, convalescent plasma, etc.
- Use Case: Segment vaccines (single dose vs. multiple doses) by manufacturer (Pfizer, Eli Lilly, Moderna, etc.) and correlate with the high-risk patient population predicated on the clinical data from Stage 3 trials
- Use Case: How many doses of the vaccine(s) would these patients need based on their age and co-morbidities? Can they handle more than one dose?
(D). How do we orchestrate a “Cold Chain” using a hub-and-spoke supply network to distribute the vaccines in a safe and secure manner?
- Use Case: Can we monitor, measure, and analyze the temperatures that the vaccines were subjected to across the chain of custody from cradle-to-grave?
- Use Case: Can we model and do a network analysis of the supply chains needed to distribute these vaccines based on risk?
- Use Case: Can we model and determine whether we distribute the vaccines using the pharma distribution chain or use Army Logistics and FEMA (Federal Emergency Management Agency) to accomplish this?
- Use Case: Leveraging the data and analytics from vaccine’s 1, 2, and 3 above, how can we effectively match supply of the vaccines to the demand by segment, by each zip code, or hospital?
- Use Case: How can we proactively detect whether a vaccine has potentially lost its efficacy and discard these before they are administered to patients, especially seniors with multiple co-morbidities?
(E). How can we monitor high-risk patients post administration of the vaccines and proactively detect adverse events as and when they happen?
- Use Case: How can we monitor a patient post-administration of the vaccine(s) using Tele-Health and Remote Patient Monitoring (RPM) to ensure they are doing well and not displaying any side effects (fever, rash, hives, seizure, or other symptoms)?
- Use Case: How can we rapidly collect and report data on adverse events from these patients and report to the FDA/CDC to potentially halt distribution of a particular vaccine if it triggers many adverse events beyond the suggested thresholds of safety?
- Use Case: Can we return defective vaccines to the manufacturer using the same cold chain for analysis?
The good news is that one or more of these three vaccines will potentially be ready for administration by the end of December 2020, starting with front line responders and essential workers, as well as seniors in nursing homes.
If all goes well and we do not see significant “adverse events” triggered by these vaccines, we could potentially get the vaccine available for mass distribution in the June to September 2021 period. Until then, we have our masks and social distancing to adhere to and keep us safe.
Disclaimer: The perspective and views expressed in this blog post are my own and do not represent those of my current or previous employers.
Read This Next.
Robots, Analytics, And The Future of Healthcare Delivery
Discover 14 ways how data, AI, and robotics are transforming the future of healthcare.
Beyond COVID-19: What Will the New Model for Patient Engagement Look Like?
The disruption caused by COVID-19 has culminated in an unprecedented and exponential increase in digital health innovation for virtual healthcare delivery.