The 'AI Superboom' That Will Change Medicine
We're on the cusp of a biopharmaceutical renaissance powered by AI tools...
Over the past two decades, the number of clinical studies registered with the U.S. government has steadily and dramatically increased.
What began as a small database of fewer than 3,000 studies in 2000 has swelled to more than 560,000. Take a look...
Zooming out like this, the big long-term trend is clear. But over the past five years, these trials hit some unexpected speed bumps.
In particular, the pandemic upended hospital routines, diverted staff, and made it harder to bring patients on-site... delaying and dragging out trials.
According to research firm McKinsey, roughly 75% of global pharmaceutical companies paused site activation during the pandemic and 50% paused recruitment.
This caused a much longer-term ripple effect that has only just begun to recover over the past couple of years...
Today, trial numbers are bouncing back. You can see this in the 2025 data above.
Money is again flowing back into clinical testing. The largest pharmaceutical companies together spent more than $190 billion in research and development (R&D) in 2024. That's up $80 billion, or 73%, from five years ago.
And those investments are flowing into new areas, too. AI-driven drug design, for instance, is reshaping how scientists discover and test new therapies.
The number of AI-discovered molecules in clinical trials has spiked over the past five years. It has gone from 17 in 2020 to 103 as of March this year.
Researchers are using AI for everything from discovering new drug targets to improving traditional small-molecule drugs and advanced antibody drugs.
A 2024 paper published in the science journal Drug Discovery Today suggests that AI-derived molecules could have a success rate of 80% to 90% in Phase I trials. That blows past historical averages, which come in at 30% to 40%.
With more Phase I successes, more drug candidates can advance to Phase II and III... And we'll likely see more new drugs get approved.
So it makes sense that a lot of biotechs, pharmaceutical companies, and academic institutions are actively investing in AI.
They're focusing on new machine-learning models to find patterns. These algorithms mine disease data... vast stores of unstructured information like medical records, genomic studies, trial protocols, and decades of journal articles to uncover patterns a human researcher might miss.
In drug development, this level of analysis helps identify which molecules are most likely to work and which patients are most likely to respond to treatment.
This advance has two benefits. First, since pharma companies won't waste their time on dead ends, they'll get more successful, potentially lifesaving drugs into patients' hands. And second, drugmakers won't throw their money away on failed projects.
Each clinical trial can cost hundreds of millions of dollars and years of work – before a company finds out whether a drug will even work. Machine-learning models can shrink the costs of that "trial and error" phase.
Still, without reliable, comprehensive datasets, even the most advanced AI algorithms are flying blind. That's where I see the biggest investment opportunity...
For readers who don't know me, I love investing in healthcare because it combines both my professional specialties... I'm a former Wall Street trader and board-eligible eye surgeon.
And right now, I've identified a small group of businesses that produce, measure, and manage the biological data pharmaceutical companies depend on. Even with AI helping the process, it's a gamble to bet on which drugs will ultimately pan out... But these companies will benefit from increased research spending either way.
The federal government has already committed $5 billion that will benefit these companies. And a critical congressional funding decision is expected on December 11. That leaves a narrow window of opportunity to get positioned before Wall Street recognizes these companies' potential and sends their share prices significantly higher.
You can learn all about the next "AI superboom" and how to position your portfolio for it here.
Now, let's get to this week's Q&A... And as always, keep sending your comments, questions, and topic suggestions to feedback@healthandwealthbulletin.com. My team and I read every e-mail.
Vitamin C and Kidney Stones
Q: I am surprised your answer did not contain a caution about taking vitamin C and its possible adverse link to kidney stones. – D.B.
A: Thanks for your comment, D.B. The risk between kidney stones and vitamin C supplements isn't clear, but here's what we do know...
Calcium-containing stones account for roughly 80% of kidney stones, and most of those contain calcium oxalate. Your body makes oxalate naturally as a waste product. Some oxalate comes from food, while much of it is made as the liver breaks down other compounds.
These stones can form when calcium and oxalate become too concentrated in urine, stick together, and grow into a solid mass of calcium oxalate. So if you have chronic kidney disease or someone who already suffers from kidney stones, it may be worth avoiding this risk.
Still, most research points to this risk only among men who take a ton of vitamin C (we don't see the same results for women). For example, in a long-term study published in the American Journal of Kidney Diseases, more participants reported kidney stones if they consumed more than 1,000 milligrams ("mg") of vitamin C per day.
I only take about 500 mg of pure vitamin C a day as a powdered supplement I mix in water. This form avoids fillers and other ingredients often mixed into capsules and tablets. That way, I know exactly what I'm getting and how much. There's no firm evidence that this dosage increases the risk of kidney stones.
What We're Reading...
- Did you miss it? Biotech is finally coming back.
- Something different: Do you want to live and work on the moon?
Here's to our health, wealth, and a great retirement,
Dr. David Eifrig and the Health & Wealth Bulletin Research Team
November 13, 2026