I don't know, its missing putting your sample in a big grey machine and then getting a number from the big grey machine.
Yeah there are robots, but they tend to be $500,000+ and many scientists in this field are tech luddites who are allergic to learning how to program a robot.
A postdoc will do the same work for (probably) less than 1/10 of the price AND do free overtime. Better yet, you can sometimes get students to do this work for free/nearly free.
That's also assuming they are able to get funding to cover any of these costs.
As for using a multipipetter, it just depends on the experiment and you can do ~10 at once.
Also too there is a lot of prep to get those thousands at once. Maybe 10x the work rather than 1000x but if your doing basic research your looking at effects small scale. ramp up happens when results are promising.
Yeah, but those are for scaled up processes. If you're doing basic research, most of the time you'll want to do it yourself. Plus, those bots are very expensive.
They already make machines to do repetitive pipetting, it's just that humans are cheaper and more widely usable.
Our lab's auto pipetter is broken about 60% of the time, most days we just shut it off and reroute specimens to the workbenches to do it by hand because it's faster than attempting to fix it or call customer service. Maybe once the good-for-nothing customer service repair phone line is replaced by AI it will actually function and be worth the half a million dollars we spent on this stupid machine, lol
I am meaning more than just the piping as AI is starting to observe now too. Read here the other day that an AI is researching new materials unassisted in a lab.
You're lucky if people in the physical sciences know how to restart their computer. Sure, they're experts in their fields, but actively avoid learning new technology unless someone twists their arm.
The fields that could benefit from robots the most are the least equipped in terms of money and requisite tech knowledge to use a robot. Instead, you're likely to see them used in for-profit labs and those aren't the ones that tend to do novel research. Well-funded biotech and pharmaceutical companies are likely to have robots, but many of those don't want to do discovery-stage research. They tend to buy discoveries from public university labs.
