Joined October 2025
2 Photos and videos
Those who grasp what we’re doing at @precigenetic tend to be very bullish. A year before I joined, I learned about Parm and her efforts. I sounded just like this guy👇
Replying to @parmita
the great thing about parm is that she's not selling. she's celling. never ever bet against parm
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CEO who can easily see beyond the dominant paradigm >>> 🔥 WAGMI
whenever i get off call with my CTO i freak tf out like man we are really on to next level shit with our hardware omg this is game changing lmao we are systemically destroying the need for every piece of clunky lab equipment and making this shit a factory with lasers and no humanoid robots or even much robot arms needed
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sasaan showghi reposted
whenever i get off call with my CTO i freak tf out like man we are really on to next level shit with our hardware omg this is game changing lmao we are systemically destroying the need for every piece of clunky lab equipment and making this shit a factory with lasers and no humanoid robots or even much robot arms needed
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Firing up my grill and fired up for build week at Precigenetics! Excited to start our first scratch built MBOP. Scalable, low-cost platform for rich multimodal human-relevant datasets…no animal trials💚 Kicking off with liver tox on Proto1. Big step for precision medicine! #MBOP #MemorialDay2026
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Never thought a chip could cure cancer, but here we are. For months, our hardware team at Precigenetics has been secretly working on MBOP: Modular Biological Observation Platform. We’re now fabricating v.1, and here’s why you should be excited. MBOP is the first microfluidic initiative from an AI drug discovery company. By leveraging commoditized methods from the semiconductor and microelectronics industries, we’re integrating our entire disease modeling and cell-culture protocol into a modular chip format. This core building block will exponentially increase throughput of our high-content imaging, while making cell culture and cell imaging a repeatable, programmable, high-fidelity data source for our training models. Our aim is simple: making data that actually answers the questions current methods lose. In an industry of sparsity, middlemen, and a repeatability crisis, we’re finding the needles in the haystack that make curing disease inevitable.
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