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Keoni Gandall

@koeng101 • 3,232 subscribers

everyone should have the opportunity to build beautiful things with biology

Shorts

For storage, I’m freeze drying most of my cells rather than storing in a -80c. Can have em at room temperature with full stability for decades. Way less energy use and I don’t need to worry about power turning off or freezers breaking

For storage, I’m freeze drying most of my cells rather than storing in a -80c. Can have em at room temperature with full stability for decades. Way less energy use and I don’t need to worry about power turning off or freezers breaking

68,340 views

Dual concurrent DNA builds going. Can create 192 plasmids / day at approx $20 per plasmid

Dual concurrent DNA builds going. Can create 192 plasmids / day at approx $20 per plasmid

53,498 views

And automated plating for the concurrent 192 as well. Key is to dispense 5uL of 6uL above the agar plate then stab. Makes a droplet form a tiny circle. Do serial dilutions == plating solved!

And automated plating for the concurrent 192 as well. Key is to dispense 5uL of 6uL above the agar plate then stab. Makes a droplet form a tiny circle. Do serial dilutions == plating solved!

20,026 views

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I created a demo of a bioautomation system that uses LLMs, Opentrons, and lua to create a dynamic programming environment for cloud labs or robot/human clusters. It can reason about its own code based off of lab measurements. Most importantly, I actually fucking implemented it, and it is open source. Took about 4 days for this rough draft, and it is very much a draft. The user inputs their task, the system creates code, and then executes it. The code defines control flow from data generated in the lab. Not only can it create code, but it can reason about things that could have gone wrong, run analysis using an internal sandbox, and then create new code based off of that analysis for execution. Timestamps: 0:00 - intro and code generation 3:04 - homebrewed replacement for Opentrons API for running all this code 5:26 - dynamic control flow using data 6:10 - LLM reasoning about a biological protocol and fixing it 10:15 - rant on the future of cloud labs and bioautomation I made this as a demo for how I think we should be thinking about building and scaling biology. I believe we can encode the tacit knowledge of a laboratory into the knowledge of an LLM, that we can do reinforcement learning off of results it creates, and that we must do that by leveraging a sufficient quantity of unique, useful, verifiable protocols. That doesn't come from just doing drug screens - it comes from doing basic everyday experiments and doing them well. Through the elimination of tacit knowledge necessary to physically operate a lab + proper batching + models writing code, I think we can make building biotechnology 10x-100x cheaper and easier than it is nowadays.

I created a demo of a bioautomation system that uses LLMs, Opentrons, and lua to create a dynamic programming environment for cloud labs or robot/human clusters. It can reason about its own code based off of lab measurements. Most importantly, I actually fucking implemented it, and it is open source. Took about 4 days for this rough draft, and it is very much a draft. The user inputs their task, the system creates code, and then executes it. The code defines control flow from data generated in the lab. Not only can it create code, but it can reason about things that could have gone wrong, run analysis using an internal sandbox, and then create new code based off of that analysis for execution. Timestamps: 0:00 - intro and code generation 3:04 - homebrewed replacement for Opentrons API for running all this code 5:26 - dynamic control flow using data 6:10 - LLM reasoning about a biological protocol and fixing it 10:15 - rant on the future of cloud labs and bioautomation I made this as a demo for how I think we should be thinking about building and scaling biology. I believe we can encode the tacit knowledge of a laboratory into the knowledge of an LLM, that we can do reinforcement learning off of results it creates, and that we must do that by leveraging a sufficient quantity of unique, useful, verifiable protocols. That doesn't come from just doing drug screens - it comes from doing basic everyday experiments and doing them well. Through the elimination of tacit knowledge necessary to physically operate a lab + proper batching + models writing code, I think we can make building biotechnology 10x-100x cheaper and easier than it is nowadays.

21,319 views • 1 year ago

Continuing my new years tradition of cloning on the eve! This is a cool demo of several tiny innovations that have a big impact: - usage of Opentrons OT2 multichannel as a single channel pipette - 0.5 rather than 2 or 1.5 mL tube for compatibility with p20 - temperature control of competent cells - pipette tip reuse and order of operations for maximizing cold-time

Continuing my new years tradition of cloning on the eve! This is a cool demo of several tiny innovations that have a big impact: - usage of Opentrons OT2 multichannel as a single channel pipette - 0.5 rather than 2 or 1.5 mL tube for compatibility with p20 - temperature control of competent cells - pipette tip reuse and order of operations for maximizing cold-time

13,037 views • 1 year ago

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