Hello, Reader.
I’ve been talking about AI a lot lately…
Specifically, how it can – and is – revolutionizing different industries, from healthcare to semiconductor chips.
And now, artificial intelligence has come to change biotech’s game in unfathomable ways.
Namely, AI could revolutionize the economics of drug discovery.
- First, it could boost the success rates of new therapies by pre-qualifying potential drug candidates more expertly than traditional trial-and-error processes could.
- Second, it could reduce the average expense and timeline of advancing these candidates through clinical trials by shortening the drug-development timeframe.
Amgen, a multinational biopharmaceutical company, provides the following perspective…
Protein drug development is long, arduous and costly. Drug developers have typically looked to proteins in nature as starting points, and then gone through the slow, painstaking process of shaping those natural proteins into safe, effective drugs. But the advent of artificial intelligence (AI)… is changing all of this through a process called generative biology.
Similar to how generative AI systems (like ChatGPT) allow for the generation of new data such as text or images from existing inputs, generative biology allows for the generation of new protein-based drugs that have desired structures and properties based on existing protein data inputs.
Researchers at Amgen have started using data collected in the lab about a protein’s sequence, structure and function to train machine learning (ML) algorithms to design drug candidates more quickly and with greater success than turning natural proteins into drugs.
Consider two hypothetical scenarios, in combination with one another…
AI Could Lower Costs
Let’s imagine that AI was able to pre-qualify potential drugs to such an extent that it could eliminate 25% of the flawed candidates before they ever entered clinical trials.
That improvement, by itself, would reduce the average cost of drug development from $2.6 billion to about $2 billion. Let’s next imagine that AI-centric analytical processes, like in silico testing, could reduce the drug-development timeline by 25%. That improvement could shave an additional 25% off drug development costs to lower the average to less than $1.5 billion.
In other words, the all-in average cost of drug development could drop more than $1 billion. If the pharmaceutical industry could save $1 billion here and $1 billion there, eventually it would be saving real money.
Obviously, these back-of-the-envelope projections could be wide off the mark. AI might not bestow a near-term benefit of this magnitude. On the other hand, it might.
A Biotech Gold Rush
To illustrate that potential, let’s return to the gold industry and the famous California Gold Rush. The early 49ers would spend long days panning for gold in California streams. But in 1853, a fellow named Edward Mattison invented the sluice box, which separated gold flakes from stream gravel.
Because the early sluices could process about 10 times more gravel per day than a panner could, this new invention exponentially improved the productivity and economics of placer mining.
AI could impart a similarly game-changing efficiency to the drug-development process, and thereby shower pharmaceutical companies with a pixie dust of enormous prosperity.
Collectively, the pharmaceutical industry seems to be banking on the pixie dust scenario.
Meanwhile, many of the biggest pharmaceutical companies in the world are paying tens of billions of dollars to snap up promising, albeit profitless, biotech companies. You could call it a biotech gold rush.
Presumably, the “crazy” prices major pharmaceutical companies are paying to acquire early-stage biotech companies aren’t crazy at all. The acquiring companies must believe that they can utilize AI to quickly convert the profitless potential of their biotech acquisitions into robust profitability.
I trust their collective judgement, and I believe that the pharmaceutical industry, in aggregate, will reap handsome rewards from the expansion of AI in healthcare. Specifically, I expect a growing number and variety of AI-derived therapies to enter clinical trials during the next couple of years.
However, as a non-expert of biotech stocks, I would not dare to pick specific winners and losers. Instead, I am picking the industry itself as a major winner of the nascent “AI era.”
How to Prosper in AI
Biotech isn’t going to be the only winner in the AI race, though.
In fact, the winning stocks for the AI Wars of 2024 are already being decided – thanks to the U.S. government.
As I’ve mentioned before, the new Federal Law 117-167 has a critical deadline of Thursday, Feb. 1.
In short, Congress is set to bring in new regulation, laws, and funding to the $15.7 trillion AI industry here in America.
Now, this critical deadline is only a few days away. And when this deadline hits, thanks to the coming AI Wars, you could double your money at least 10 different times in 2024.
If this sounds unbelievable, I can’t blame you for being skeptical…
However, now is the time to prepare. So, to get more details on the critical Feb. 1 deadline – and how to come out as a winner in the AI Wars – click here.
Regards,
Eric
