My wife is a bench scientist. The perspective I get from her is that automation is typically much slower than doing it by hand, especially since there are tools like multi-channel pipettes that give you a lot of the benefits of automation without needing to do any coding. The general task of sucking up liquids is also tough to calibrate due to differences in viscosity. An automation engineer will need to spend a lot of time calibrating while someone who has a lot of experience can go by feel.
This is a very interesting comment because the project I am currently on is trying to assess viscosity with computer vision in basically the same way you are saying.
I am surprised you say that doing stuff is faster by hand, can you elaborate what you wife mean by this? Is the bottleneck the user-friendliness of programming the robots? Because I have a hard time believing the actual motion of the researcher pipetting beats the $500k hamilton liquid handlers... could be wrong though!
I work as a journalist covering the lab space. Lab informatics and automation in particular.
A few factors off the top of my head (there are more):
- Proprietary communication protocols between equipment from different OEMs. It's possible to automate to a greater extent if every asset speaks the same language. They often don't. Instruments exist in the OEM's walled gardens.
- Robots do save money in the long run, but they are expensive upfront. This is a deterrent, especially labs on a small budget that just don't have the CapEx for robots. This is the case for many academic labs, in particular.
That said, there is progress being made toward automating wet labs to a greater extent. There are projects to standardize protocols so you can have communication between assets from different OEMs. One of my sources from the NIH also told me last week that there are advancements being made in mobile robots that can cart samples from instrument to instrument autonomously.
Okay, this is helpful and definitely aligns with what I've heard. The proprietary protocols problem keeps coming up.
Is there any chance we can connect for me to ask a few more questions or read some of your reporting? My email is in my profile.
I am currently doing a masters in robotics and my capstone is aiming to do some lab automation. I don't have background in the area, so I am trying to learn everything I can. Thanks!
My wife is a bench scientist. The perspective I get from her is that automation is typically much slower than doing it by hand, especially since there are tools like multi-channel pipettes that give you a lot of the benefits of automation without needing to do any coding. The general task of sucking up liquids is also tough to calibrate due to differences in viscosity. An automation engineer will need to spend a lot of time calibrating while someone who has a lot of experience can go by feel.
This is a very interesting comment because the project I am currently on is trying to assess viscosity with computer vision in basically the same way you are saying.
I am surprised you say that doing stuff is faster by hand, can you elaborate what you wife mean by this? Is the bottleneck the user-friendliness of programming the robots? Because I have a hard time believing the actual motion of the researcher pipetting beats the $500k hamilton liquid handlers... could be wrong though!
I work as a journalist covering the lab space. Lab informatics and automation in particular.
A few factors off the top of my head (there are more):
- Proprietary communication protocols between equipment from different OEMs. It's possible to automate to a greater extent if every asset speaks the same language. They often don't. Instruments exist in the OEM's walled gardens.
- Robots do save money in the long run, but they are expensive upfront. This is a deterrent, especially labs on a small budget that just don't have the CapEx for robots. This is the case for many academic labs, in particular.
That said, there is progress being made toward automating wet labs to a greater extent. There are projects to standardize protocols so you can have communication between assets from different OEMs. One of my sources from the NIH also told me last week that there are advancements being made in mobile robots that can cart samples from instrument to instrument autonomously.
Okay, this is helpful and definitely aligns with what I've heard. The proprietary protocols problem keeps coming up.
Is there any chance we can connect for me to ask a few more questions or read some of your reporting? My email is in my profile.
I am currently doing a masters in robotics and my capstone is aiming to do some lab automation. I don't have background in the area, so I am trying to learn everything I can. Thanks!
Somewhat related -https://www.asimov.press/p/making-the-modern-laboratory
Helpful link, thanks!