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A lab technician wearing a protective face mask (Bloomberg)
A lab technician wearing a protective face mask (Bloomberg)

Vaccine Phasebook: The Essence of Trials

Neither the volunteers nor the researchers should know who will receive what treatment

It’s one of those pandemic sidelights. We’ve learned plenty of resonant phrases and concepts that we might not otherwise have done. Like: exponential growth, herd immunity (or even, as a certain President recently had it, herd mentality), peaking … and Phase 1, or even 2 and 3.

Those last three refer to clinical trials of vaccines to fight the virus. That is, a potential vaccine has to go through three different kinds of trials, each more elaborate and wide-ranging than the previous. Only after it has passed those trials can the vaccine be put on the market for widespread use. With this particular virus, there are efforts around the globe to find a vaccine, and some are now starting Phase 3 trials.

This may mean a vaccine will be available soon. Or not. There’s doubt because it must actually pass the Phase 3 trials, and we don’t know if it will. But what we have no doubt about is that we don’t yet have a vaccine. Oh, there are those who may tell you different. They may try to sell you a “cure" for the virus that will give you “100% recovery" from it. Until it has gone through those trials, treat such “cures" as the snake-oil they are.

But leave aside snake-oil. What do those trials entail, anyway?

Let’s say you lead a lab that has been working feverishly for weeks with the corona virus, peering at it under the microscope. You’ve made progress. You’ve identified its vulnerabilities and have put together a cocktail of chemicals to mount an attack on them. At least on your Petri dishes and under your microscopes, the cocktail seems able to neutralize or even destroy the virus. It’s time, you believe, to try it on humans.

Thus Phase 1. This is a trial in which you ask for a few healthy volunteers — typically a few dozen — and administer the cocktail to them, the first people to get it. Why healthy? Think about it: the first priority with a new medicine must be to ensure it doesn’t cause some entirely different complications in otherwise healthy people. This is particularly important when a virus has caused so many infections that there is already an undue strain on healthcare systems.

Nevertheless, the kinds of questions you want answered in Phase 1 are: does the vaccine have any side-effects? If so, does the size of the dose make a difference to the side-effects? Is it safe? And of course, does it appear to be working?

Also, with any new medicine, you want to find its most appropriate dosage, with the fewest side-effects. So the first few volunteers are given in a very low dose and observed closely. If side-effects are only minor, the next set of volunteers get a higher dose. This cycle repeats until we find a dose strength that seems to work, while only causing an acceptable level of side-effects. This is called the “maximum tolerated dose" of the potential vaccine.

When Phase 1 tests suggest that the new medicine is safe, it’s time for Phase 2. This time, you call for a larger number of volunteers, perhaps a few hundred. While they are not all infected with the virus, many are. They are treated with doses of the medicine up to the maximum tolerated dose, as identified in Phase 1.

Again, there are questions that need answers. How effective is the medicine in preventing the virus from infecting healthy people, and in treating people who are already infected—that is, does the medicine work as preventive vaccine and curative drug? Is there an “optimum dosage" — short of the maximum tolerated dose — that we can identify? Does the medicine affect the volunteers’ immune systems and, if so, how? How do factors like age and gender affect its effectiveness?

Typically in Phase 2, there will also be a group of patients simultaneously being given a placebo — meaning something that looks identical to the treatment under trial, but that has no medicinal value and does nothing by way of treatment. The point here is to establish a standard, a reference, against which the performance of the new drug can be measured. Absent such a “control" reference, how can you conclude that the medicine is working?

And if you do come to that conclusion, you will probably embark on Phase 3 trials. By this time, you have a good idea of the final chemical composition of your cocktail, and of the appropriate dosage to give both healthy and infected people.

So now, the medicine is administered to several thousand people — one Phase 3 trial of a potential corona vaccine in the US, for example, is enrolling up to 30,000 adult volunteers. Typically, Phase 3 volunteers will come from different countries and living conditions. It is also usually administered in conditions and environments similar to the way it will be used when fully approved. Again, some volunteers will be treated with a placebo, so they are a control group.

If your cocktail passes the Phase 3 trials, you can apply for a licence to manufacture and distribute it as an approved vaccine.

Now, this is a broad and not necessarily definitive outline of these trials. But perhaps you’re wondering: what does it mean to conduct these trials, and for a particular new vaccine to “pass"? Well, apart from administering doses and monitoring patients, there’s a reason these tests interest me. Just a taste of that here; I’ll leave a more detailed exploration for a future column.

For one thing, how do you decide that the medicine has side-effects? Suppose your Phase 1 trial involves 100 volunteers. Of those, two start limping after taking the medicine. Is that worth noting? What if 60 start limping? That is, at what point do you decide that limping is a likely side-effect of this new medicine?

Also, since you are choosing healthy volunteers for Phase 1, you’re not gathering a random set of people. That automatically means these tests might suffer from a well-known problem when analysing numbers. Who chooses the volunteers, and how?

To make this clear, imagine that you deliberately, for reasons of your own, choose volunteers who have already been infected and have recovered. Volunteers who are, thus, now immune. What effect will this “selection bias" have on your trial?

Consider the administration of placebos and the “control" group of volunteers. Suppose the trial is being run by a doctor who is already persuaded that the medicine works. Knowingly or not, he might try to help volunteers who appear more ill than others by putting them in the group that’s getting the actual treatment, not the placebo. Clearly, this will skew the test results. This is why we must ensure that neither the volunteers nor the researchers know who will receive what treatment. This produces a “double blind" control.

Finally, how does a medicine “pass" these tests? If 50% of our Phase 3 volunteers recover from the infection, is that a pass? Is that enough to allow it to be promoted as a cure? Will 50% of those who use it actually recover? Answers to questions like these take into account concepts like “sample size" and a “confidence interval" for our results.

Those quoted phrases in the last few paragraphs are mathematical — really, statistical — terms. They signal that phase trials are essentially mathematical exercises. That’s why we gain confidence in the drugs we use. That’s why these trials so fascinate me.

Once a computer scientist, Dilip D’Souza now lives in Mumbai and writes for his dinners. His Twitter handle is @DeathEndsFun

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