I’ll give your analogy a try. Google could do that because the basic components were so cheap due to consumer imaging. On the lab side, there’s no similar dow

I’ll give your analogy a try. Google could do that because the basic components were so cheap due to consumer imaging. On the lab side, there’s no similar downward pressure for making more accurate automated pipettes cheaper - I fully believe it’s possible, but the market isn’t there. Also, with imaging books, you can get away with a lot since ML/cheap labor/etc can be thrown at the distortion correction problem. With lab tests, you can’t really accept that same amount of error (ok, you can iff you understand the distortion and can process more samples to compensate). I do agree that most companies just want a service that works. The issue is that there’s no standardization. Depending on the assay you do, you will need wildly different setups and sensor systems. When you optimize whatever you are doing, often you have to re-tune your entire assay to bring it line with the new dynamic range of your output. If that weren’t the case, companies like Emerald and Transcriptic would have succeeded years ago. Selling things like DNA or cell lines have been the closest to a standard, scalable product. Otherwise, it’s just replacing armies of people at a CRO (Contract Research Org) with a custom project for automation and assaying (Zymergen’s model).