Re: AI in science. Using AI to solve barriers in translational models could drive impact.
Alpha Fold is a great example. AI is being used to explore protein design spaces that humans haven't yet done / can't.
But if you find a protein of interest, it still needs to be synthesized, tested, and ultimately manufactured to become a therapeutic and get to market. Each of those steps incorporates manual workflows and distinct tech stacks.
Building tools (e.g., intelligent automation systems that work in labs and can be linearly scaled from n = 1 to n 100+ to scale production, removing tech transfer bottlenecks; new sensing systems + computational models to have "digital twins" with real predictive power) to solve these bottlenecks could help turn "really cool AI-powered science" into products that generate economic impact / help people faster.
Talking about one aspect of applied biology here. But the idea holds true for most verticals in biotech + most areas of scientific research.
Great to see the thesis being flushed out, Matt!
Re: AI in science. Using AI to solve barriers in translational models could drive impact.
Alpha Fold is a great example. AI is being used to explore protein design spaces that humans haven't yet done / can't.
But if you find a protein of interest, it still needs to be synthesized, tested, and ultimately manufactured to become a therapeutic and get to market. Each of those steps incorporates manual workflows and distinct tech stacks.
Building tools (e.g., intelligent automation systems that work in labs and can be linearly scaled from n = 1 to n 100+ to scale production, removing tech transfer bottlenecks; new sensing systems + computational models to have "digital twins" with real predictive power) to solve these bottlenecks could help turn "really cool AI-powered science" into products that generate economic impact / help people faster.
Talking about one aspect of applied biology here. But the idea holds true for most verticals in biotech + most areas of scientific research.