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1849 bio designs microbes enabling cheap metal extraction allowing miners to unlock value from low quality copper and gold ores. Surprisingly, the mining industry is one of the largest scale users of biotech in the world with biomining processes accounting for ~1% of global copper production. Biomining is ultra-low cost, running around ~$1/ton of ore vs ~$7/ton for conventional processes. Unfortunately, while biomining is cheap, it can’t be applied to over 80% of copper ores, leaving vast resources without profitable extraction methods. An estimated ~$800B of copper sit today in waste materials and stockpiles with negative unit economics. While a great deal of effort has been spent on optimizing microbial metal extraction processes, very little effort has been spent on optimizing the microbes themselves. To change that, we’re creating new biotech tools and platforms applied directly to the types of biology most relevant to miners. This enables us to develop new microbes and tackle some of the most difficult problems in biomining, unlocking billions in value from unprofitable resources while being more environmentally friendly than conventional processes. We’re world class microbial engineers. We met while doing our PhDs in synthetic biology, where we spent our time applying and developing the most advanced bioengineering technologies to engineer living cells. 

Yoneda Labs provides software to help chemists optimise reactions. When chemists make a drug or a material, we help them figure out the best reaction parameters such as temperature, concentration and catalyst. When Jan was working at chemical labs, he experienced the struggle of spending weeks guessing reaction conditions. We then started experimenting with ML to speed up the process. Now, as a team of three friends from the University of Cambridge, we’ve spent the last month combining our domain expertise in Computer Science, Machine Learning and Chemistry to develop state of the art models for reaction optimisation. Although ML is becoming well established in other fields, current chemical models generalise poorly and require lots of programming experience. We make our models easily accessible to chemists in the lab. Finding the right conditions quickly allows pharmaceutical companies to test more drugs, and finding better optima makes manufacturing process cheaper and more environmentally friendly.