start here https://slate.com/technology/2021/10/facebook-unfollow-everything-cease-desist.html

finally, they have automated couriers kicking packages

There are already a few instances that ignore delete requests

ah yes, the torment nexus

just after nitter was killed

it’s not the boomy plutonium

huh, sounds helpful (i should be writing)

you absolutely can lol

AbsolutelyNotCats is (probably) talking about some of not-yet-banned compounds predicted to have some recreational properties, sold as a “research chemicals” because these are not and will be not tested. people like DMT or 2C-B? slap a methyl here or hydroxyl there and you’re good to go with selling this because it’s not illegal to do so. you can’t call this thing as safe or pharmaceutical or anything else, because it’s not tested this way

there are also CROs that will make a panel of compounds of your choice that you then test in some high-throughput screening and these are legit, non-sketchy companies that do participate in pharmaceutical design. that’s entirely different thing

i don’t think so, if the model is owned by single company, trained on their own dataset, access is restricted and basically used as an internal tool, that would make that company sole owners of all generated content right? that’s what happened with chematica, this is used for synthesis planning at merck so mildly similar area

i hate to be the one that tells you this, but some rando cooking tryptamines in garage is not the kind of “research chemicals” that legit drug research uses. these are called CRO, contract research organizations and that would be Enamine ltd most of the time, they can make a wide array of compounds on demand. legit labs can get whatever they need (with appropriate paperwork), either as material for in vivo/in vitro testing or analytical standard

sometimes people get paid for participating in phase 1 trials, not the other way around

this thing was rediscovered four years ago and no trial was done? gee i wonder why

Experts applaud the computational approach, but say these compounds are not likely to be the drugs we need

The results show “how much can be achieved when skilled practitioners and machine-learning teams work together,” says Günter Klambauer, who leads an AI drug-discovery lab

Antibiotics experts also praised the group’s methods but were unimpressed by halicin. Several said the group’s results did not suggest the compound is the kind of antibiotic doctors need

the algorithm was too limited and didn’t allow the program to find truly novel structures: “We need new antibacterial chemotypes that may be hard to find through this approach,” says Richard E. Lee, an antibiotics researcher at St. Jude Children’s Research Hospital. And nitroaromatic groups can be toxic to human patients, as can the membrane-associated mechanism of action the researchers describe, says Shahriar Mobashery, a biochemist at the University of Notre Dame.

Collins says it’s fair to point out their molecules’ similarities to existing antibiotics. But he stresses that one of the major values in using machine learning is its speed in searching for antibiotic-like molecules. It took their model about 4 days to evaluate more than 100 million molecules.

(J. J. Collins is corresponding author of the paper cited) it’s garbage, but that garbage was generated fast!

John H. Rex, chief medical officer at the drug discovery firm F2G, echoed that critique. Rex, a former editor of the journal Antimicrobial Agents and Chemotherapy, says the work did not meet his standards for announcing a new antibiotic drug lead. In addition to his concerns about its efficacy against the most dangerous bacteria, Rex said the group’s tests of halicin’s toxicity fell short. He says he’d like to have seen the researchers test its toxicity against mammalian cells, which could provide a clearer picture of whether halicin would be toxic in the human bloodstream.

“It is quite easy to kill bacteria, even the tough ones, with toxic agents—and quite easy to find those,” says antibiotic expert Lynn Silver, who worked at Merck & Co. for 2 decades. But she says finding drugs is much harder: “Even well studied antibacterials fail in clinical trials due to toxicity.”

src: https://web.archive.org/web/20200809094713/https://cen.acs.org/physical-chemistry/computational-chemistry/AI-finds-molecules-kill-bacteria/98/web/2020/02

my policy of keeping techbros out of wet lab is unchanged

soo, they trained AI on some set of compounds, then AI combed through them and found an old failed diabetes drug, and it seems to be killing some bacteria, via mechanism that involves binding to metals, which is notoriously nonselective, with no comment on how toxic can it be, incl that failed diabetes-influencing activity

i remain sceptical on this one

why it was restricted in the first place?