Can AI Address America’s Post-Pandemic Medical Time Bomb?
There’s a health timebomb ticking in America. It’s been accelerated by the COVID pandemic, which has caused widespread changes in so many aspects of our lives. But its real impact on the health and wealth of the nation is yet to be felt.
There are millions of Americans with pre-existing conditions unrelated to the pandemic who postponed treatment, and millions more with undiagnosed conditions — all because healthcare providers prioritized COVID over all else.
Over the last two years, tens of thousands of routine cancer screenings were postponed because of it. As normalcy returns, many are only now discovering they have cancer, and a more advanced form of the disease than would be the case had their symptoms been discovered earlier.
Across every type of curable and manageable illness that falls outside the scope of the pandemic the story is the same: testing and treatment have been routinely ignored and access to necessary care severely limited.
The ramifications are huge.
If this is left unaddressed healthcare premiums will soar and put affordable insurance cover out of the reach of many middle-class Americans.
And this is only the tip of the United States’ healthcare crisis. The true challenge starts with how we discover cures for treatable diseases. This matters because expectations of the advancement of science and the curability of ailments increase every year.
Yet despite all the scientific advancements of the last century, we can only treat around 500 out of more than 7,000 known human illnesses. Often the treatments we do have work poorly and have a long list of undesirable side effects. But should we attempt to significantly expand the number of treatments available using current methods of identifying and trialing, the cost of new treatments would be mind-blowing.
At today’s rate and method of medical advancement, we are so far cry from the commonly shared vision of a future where we take a pill for nearly any condition it may as well be science fiction. And it is science-fact that none of this will change until the pharmaceutical industry changes how it discovers drugs.
This is because no matter the advances claimed in drug discovery in recent decades, manual, human-led lab-based trial-and-error testing remains the core approach. Automation of this trial-and-error testing, and advances in making variants of known drug-like molecules, created buzz and hype in the 1990s. But none of those marginal advances replaced the basic, manual trial-and-error method. So, to move beyond, today the industry now rests its hopes on Artificial Intelligence.
It's important to cut through the hype that this has created.
A.I. alone cannot propel the advances in drug discovery the world needs or at least not if all Big Pharma does is attempt to apply A.I. to speed up already exhausted methods of finding them. If pharma giants simply take data they already possess and run this through A.I. computer programs in the attempt to speed up discovery of new cures, they are doing nothing more than trying to fish faster in the same empty pond.
But should A.I. be applied differently, there can be seismic change. The fact is there are literally trillions of untried chemical molecule combinations that have not been discovered by lab technicians in white coats using century-old human trial and error methods.
Through a new approach, however, we are learning that we don’t have to create that data at all – rather, we can simulate it. Recent advances in modeling molecular physics allow us to accurately simulate via a computer how a potential new drug molecule would bind to a disease-causing protein in the human body. Through these computer-generated predictions, we can quickly obtain enough data for today’s A.I.-based tools to identify and test the vast ocean of chemical molecule combinations that until now seemed just out of reach.
The novel, easily distributable, orally administrable drugs we desperately need for the post-pandemic world will be found in this previously unexplored ocean of chemical structures. Improvement in the efficiency and speed of discovering these new medicines can help us put the pandemic and its health consequences behind us and avert the next public-health catastrophe.
A.I. can address America’s post-pandemic medical time bomb. The real question is, will Big Pharma use it?
Adityo Prakash is the founder of VERSEON, an A.I.-based drug design and development platform.
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