Skip to main content

Launch HN: Radix Labs (S18) – Downloading drugs with programmable lab automation https://ift.tt/2AUQ3zE

Launch HN: Radix Labs (S18) – Downloading drugs with programmable lab automation Hi HN, ​ We're Dhash and Ian, the founders of Radix Labs. We build software that lets biologists automate and transparently share their work. Our software glues together biologists' existing lab hardware and provides a seamless way for biologists to execute their protocols on it. Check us out at http://radix.bio/ . We think lab equipment is like mainframes were in the 1980’s - you have to program each one as a special snowflake. All that we've done is built an operating system so you can write a program once that runs on all of them. Just like developers write apps for android, they write recipes for Radix. In the future with our technology, you’ll be able to download a recipe for making a coca-cola and if you have the right robots and precursors in your lab, they’ll just start making it. Technically, do this by making biologists describe their protocol in a formal language with verified operational semantics. We do this with a web UI, so they’re don’t have to write “real” source code. We compile this protocol to our IR, deriving control and data flow graphs to inform our place-and-route algorithms. After the program is realized to robot/lab instrument commands, we generate code to be run on the automated machinery. If the entire protocol can’t be totally realized by automation, we generate natural language instructions for humans to interact with the runtime system. We go through this process to gain features you’re used to in your “normal” operating system. We provide a virtual memory abstraction so that programs compose, concurrency primitives for executing tasks in parallel and synchronizing access to fluids, and drivers to support a wide variety of different lab hardware. These abstractions differentiate us from companies like Transcriptic and Emerald Cloud Labs by allowing us to write programs with branching control flows, support for on-premise deployments, a wider variety of compatible hardware, and an advanced optimizing compiler to allow users to specify optimization criteria like minimum execution time, minimum consumable usage, or max flow to run a lab as a high-throughput assembly line. Right now we’re compatible with some pipetting robots (Opentrons and some Tecan robots) and we're working on adding more devices. Contact us and let us know what you need automated. Launch HN: Radix Labs (YC S18) - Software for Bio Lab Automation We’re doing this to bring better lab-scale tooling to biologists, it currently costs 2.3B to get a new drug to market. This is too high to the point of where promising drugs are scrapped for economic reasons, and we think we can help fix that. We’ll be here to answer any questions you have about us and our product for the next few hours as @Ian_Paul and @Dhash. Also feel free to fill out this ( https://ift.tt/2AQsWpK ) form and we’ll answer any question you have over email August 8, 2018 at 10:47AM

Comments

Popular posts from this blog

Launch HN: Simmer (YC W19) – Reviews for Delivery Dishes https://ift.tt/2Y4sD67

Launch HN: Simmer (YC W19) – Reviews for Delivery Dishes Hi HackerNews community! We’re Vaibhav and Richard, founders of Simmer ( https://usesimmer.com ). Simmer aggregates dishes from DoorDash, Caviar, GrubHub, and basically every other delivery platform out there, and tells users the best dishes across the board. We do this by providing dish-level reviews. Users find highly reviewed dishes on Simmer, choose the delivery platform of their liking, and we deep link them into their chosen delivery app. We essentially lead gen to delivery. We started working on Simmer because we loved trying new restaurants, but never knew what to order. Especially, when there’s a 5 page menu. We always asked ourselves, “Why aren’t there ratings for individual dishes?” We launched our app with this restaurant-centric use case (reviews for every dish at every restaurant), but when we rolled out delivery integrations, we realized that users resonated most with the delivery angle. They found it particularly ...