The following is just part of a guest op-ed in The New York Times by Bill Gates. He has a point. We need to be able to develop therapeutic treatments faster when hit by a pandemic. He writes:
Today, drug discovery still relies on a mixture of good science and good luck. Unfortunately, when an outbreak appears to be headed toward a pandemic, there’s no time to count on luck. The next time we’re faced with a contagion, scientists will need to develop treatments as fast as possible, much faster than they did for Covid.
So let’s suppose we’re in that situation: There’s a new virus that looks like it could go global, and we need a treatment. How will scientists go about making an antiviral?
The first step is to map the virus’s genetic code and figure out which proteins are most important to it. These essential proteins are known as the “targets,” and the search for a treatment essentially boils down to defeating the virus by finding things that will keep the targets from working the way they should.
Until the 1980s, researchers trying to identify promising compounds had to rely on slow trial and error to identify the right ones. Today, using 3-D modeling and robotic machines that run thousands of experiments at a time, companies can test millions of compounds in a matter of weeks — a task that would otherwise take a team of humans years to complete.
Once a promising compound is identified, the scientific teams will analyze it to determine whether it’s worth further exploration. Once they’ve found a good candidate, they will typically spend several years in the “preclinical” phase, studying it to determine whether it is safe and triggers the desired response. The first studies will be done in animals. (Finding the right animal is not easy. Researchers have a saying: “Mice lie, monkeys exaggerate and ferrets are weasels.”)
If all goes well in the preclinical phase, the drug will move into the riskiest and most expensive part of the process: clinical trials in humans. With permission from a government regulator — in the United States, it’s the Food and Drug Administration — scientists will start a small trial involving a few dozen healthy adult volunteers. They will be looking to see whether the drug causes any adverse effects and to zero in on a dosage that’s high enough to be beneficial but not so high that it makes the patient sick.
Assuming all goes well once again, it will move on to larger and larger trials. Finally, after three phases, if they believe the drug is safe and effective, the scientists will go back to the regulatory agency and apply for approval. Then — assuming they get the green light — it’s time to start manufacturing.
At this point, a team of chemists will work on finding a consistent way to produce the key part of the drug, known as the “active ingredient.” Then, the scientific team will address the next big question: How to make sure it actually reaches everyone who needs it. Not at all an easy problem to solve.
As you can see, drug development is a complex and labor-intensive science, and each step is fraught with scientific and logistical obstacles — but we need to accelerate the process. The faster researchers are able to produce safe, effective drugs for quick-spreading pathogens like Covid, the more lives will be saved and the more we can reduce the burden on health care systems. Fortunately, there are ways to speed up and streamline the process without sacrificing safety.
One of the keys to ensuring that health care workers have better treatment options in the next big outbreak than they did for Covid will be investing in large libraries of drug compounds that researchers can quickly scan to see whether existing therapies work against new pathogens. Some of these libraries exist already, but the world needs more. We need libraries that cover many types of drugs, but the most promising, in my view, are those known as pan-family and broad-spectrum therapies — either antibodies or drugs that can treat a wide range of viral infections, especially those that are likely to cause a pandemic.
Researchers could also find better ways of activating what’s known as “innate immunity,” which is the part of your immune system that kicks in just minutes or hours after it detects any foreign invader — it’s your body’s first line of defense. By boosting your innate immune response, a drug could help your body stop an infection before it takes hold.
To deliver on these promising approaches, the world needs to invest more into understanding how various dangerous pathogens interact with our cells. Scientists are working on ways to mimic these interactions so that they can quickly figure out which drugs might work in an outbreak.
A few years ago, I saw a demonstration of a “lung on a chip,” an experimental device you could hold in your hand that operated just like a lung, allowing researchers to study how different drugs, pathogens and human cells affect one another. With advances in artificial intelligence and machine learning, it’s now possible to use computers to identify weak spots on pathogens that we already know about, and we’ll be able to do the same when new pathogens arise. These technologies are also speeding up the search for new compounds that will attack those weak spots.
With adequate funding, various groups could take the most promising new compounds through Phase 1 studies even before there’s an epidemic, or at least have several leads that can be turned into a product quickly once we know what the target looks like.
In short, although therapeutics didn’t rescue us from Covid, they hold a lot of promise for saving lives and preventing future outbreaks from crippling health systems. But to make the most of that promise, the world needs to invest in the research and systems we’ll need to find treatments much faster. That’s why my foundation has supported a therapeutics accelerator at Duke University, but broader initiatives will be necessary to make lasting change. This will require substantial investment to bring together academia, industry and the latest software tools. But if we succeed, the next time the world faces an outbreak, we’ll save millions more lives.
