These days, large language models are pushing the line between schizophrenic break and reality closer than ever before.
In a wild new post that’s going viral on X-formerly-Twitter, an enterprising young biochemist named Douglas Yao showcased a new drug he’s been developing with the aid of ChatGPT. He’s not employed by any pharma company, and his drug lab is setup on a couple folding tables in his garage.
Specifically, Yao enthuses about a new drug he calls “PAC-3310,” which he says is meant to treat schizophrenia. “It was designed by ChatGPT,” Yao explains, “and I synthesized it in a chemistry lab I built in my garage.”
The result is a small vial of yellow powder — the first sample of 3310, apparently — which Yao says is modeled after the recently-authorized antipsychotic Cobenfy, “but improved.”
On his GitHub page, Yao boasts that he’s used AI to “design several thousand new small molecule drugs” over the past year, including a “new Alzheimer’s drug,” which he’s developing in addition to the schizophrenia treatment.
“I then taught myself synthetic chemistry, built a chem lab in my garage, and synthesized a hundred of them,” he continued. “I’m now testing these compounds in cell lines and mice.”
But whatever the one-man pharma lab hopes to accomplish is difficult to say. Yao references the fact that “drug developers typically spend tens of millions of dollars generating pre-clinical efficacy evidence for a new drug,” saying that “my approach can do this at 1/1000 the cost.” This seems to suggest dreams of someday manufacturing the various drugs on a massive scale for human consumption — a process that would take years of grueling and expensive work for a well-resourced drug lab, let alone a solo entrepreneur using a box fan as a fume hood.
For instance, to even approach the Food and Drug Administration’s “New Drug Application” — itself a costly 12-month process requiring inspection of the facility where the drug will be manufactured — one first has to conduct rounds of preclinical testing followed by three phases of clinical trials. Forget “tens of millions,” as Yao mentions; this is a process that can easily cost several billion.
Even then success is far from guaranteed, as only 13.8 percent of drugs that enter clinical trials go on to obtain full approval from the FDA.
While Yao might have been right at home in the free-wheeling research landscape of the 1970s, we no longer live in a world where a mad genius can synthesize hundreds of new drugs a year from a private lab. For one thing, the regulatory environment is much more demanding, as outlined above, to say nothing of the fact that all the low-hanging fruit has been picked from the vine decades ago.
When it comes to Yao’s ChatGPT-generated Alzheimer’s treatment, the landscape is particularly fraught. As one 2019 study found, no new drug has been approved to treat Alzheimer’s since 2003, and not for a lack of trying: as the study notes, over 200 proposed substances meant to treat the disease have either failed in clinical trials or been abandoned by their creators.
The graveyard of failed Alzheimer’s treatments is so vast that the renowned organic chemist Derek Lowe has built a blog on drug discovery which routinely features after-action reports on failed substances designed to treat the neurodegenerative disease. Simply put, to think that ChatGPT alone is enough to overcome these scientific and institutional hurdles is delusional.
Replies to Yao’s post were quick to point out the irony here, of using ChatGPT — which is well-known for leading vulnerable users down dangerous breaks from reality — to synthesize drugs to treat cognitive diseases like Alzheimer’s and schizophrenia.
“Hello schizophrenic, take this medicine that chatgpt made for you,” one poster quipped on X.
Another replied that “believing you single-handedly cured schizophrenia on a commercial laundry folding table in a garage is, ironically, a classic symptom of schizophrenia.”
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