The right way to get a vaccine at 'warp speed'

Coronavirus vaccines are rapidly advancing through the development pipeline. The University of Oxford's vaccine is in large trials in Britain, Brazil and South Africa. In the United States, researchers just began enrolling around 30,000 volunteers to test Moderna's vaccine, and more trials are starting every day. Operation Warp Speed has set an ambitious goal of delivering 300 million doses of a safe, effective vaccine by January.

But the concept of developing a vaccine at "warp speed" makes many people uncomfortable. In a May survey, 49% of the Americans polled said they plan to get a coronavirus vaccine when one is available, 20% do not, and 31% indicated that they were not sure. The World Health Organization considers "vaccine hesitancy" a major threat to global health, and poor uptake would jeopardize the impact of a coronavirus vaccine.

This hesitancy isn't surprising. Why should we expect Americans to agree to a vaccine before one is even available? "I think it's reasonable to be skeptical about a vaccine that doesn't exist yet," Dr. Paul Offit, the director of the Vaccine Education Center at Children's Hospital of Philadelphia, told Today.

I'm a vaccine researcher, and even I would place myself in the "not sure" bucket. What we have right now is a collection of animal data, immune response data and safety data based on early trials and from similar vaccines for other diseases. The evidence that would convince me to get a COVID-19 vaccine, or to recommend that my loved ones get vaccinated, does not yet exist.

That data can be generated by the large trials that are just beginning, known as Phase III or efficacy trials. Some have argued that we already have enough safety and immune response data to start vaccinating people now. But this would be a big mistake.

This is how Phase III trials work: Thousands of healthy adult volunteers are randomized to receive either a new COVID-19 vaccine or a control — a placebo or an already licensed vaccine for another disease. Then they go about their normal lives. They do not know what they have received (known as "blinding") so the two groups behave similarly in terms of risk taking.

Participants are monitored for side effects and contacted regularly to ask about symptoms and to be tested for infection. The goal is to compare the rates of disease or infection across the two groups to measure how well the vaccine prevents COVID-19 "in the field."

How many people need to be protected by a vaccine before it's recommended for widespread use? Ideally, rates of disease will be 70% lower in vaccinated people than in unvaccinated people. The World Health Organization says a vaccine should be at minimum 50% effective, averaged across age groups. (We know from influenza that vaccines don't always work as well on older adults whose immune systems have declined.)

This benchmark is crucial because a weak vaccine might be worse than no vaccine at all. We do not want people who are only slightly protected to behave as if they are invulnerable, which could exacerbate transmission. It is also costly to roll out a vaccine, diverting attention away from other efforts that we know work, like mask-wearing, and from testing better vaccines.

The last thing Phase III trials do is examine safety. Earlier trials do this, too, but larger trials allow us to detect rarer side effects. One of those rare effects researchers are paying attention to is a paradoxical phenomenon known as immune enhancement, in which a vaccinated person's immune system overreacts to infection. Researchers can test for this by comparing the rates of disease severe enough to require hospitalization across the two groups. A clear signal that hospitalization is higher among vaccinated participants would mark the end of a vaccine.

The speed of the trials depends on how quickly we can detect a difference between the two groups. If two vaccinated people became sick vs. 10 who got a placebo, it could be because of chance. But if it were 20 compared with 100, we would feel much more confident that the vaccine was working.

Key to getting a quick result is placing the trial in outbreak hot spots where people are most likely to be infected. We can even target the highest-risk people within those areas, using mobile teams to travel to neighborhoods, bringing the trial directly to the people. Some trials explicitly prioritize essential workers like health care workers or grocery employees. Others are simply focused on enrolling large numbers of participants as fast as possible.

There are ways for vaccines to be approved without definitive efficacy data, based on animal or immune response data instead, but the bar is extremely high, and for good reason. A precondition is that efficacy trials are not possible, typically because the disease is so rare or sporadic that it would require hundreds of thousands of participants to be followed for many years to tell if the vaccine is effective (rabies, for example). That is not the situation here.

While there is promising data from smaller trials that measured the antibody response in people who got a vaccine, it's not enough to approve a vaccine. We don't know the level of antibodies needed to prevent infection from this virus. There is a history of vaccines with promising immune response data that did not pan out in the field.

With this in mind, the FDA has committed to the need for traditional efficacy trial data to approve COVID-19 vaccines. And it follows the WHO's recommendation, stating that vaccines must be at least 50% effective to be approved.

I worry nonetheless that public pressure may mount to approve a product that doesn't meet our standards. Other countries may decide to approve vaccines based on weaker evidence. Russia, for example, claims to be on track to approve a vaccine in just a few weeks.

We must resist the desire to rush out a product. Creating vaccines is hard, and we should be prepared for the reality that some promising ones will not meet the FDA's criteria. Researchers and the government should also commit to transparency so that people can see the results for themselves to understand the regulatory decisions.