The recent article “We Still Can’t Predict Much of Anything in Biology” by Claus Wilke captures a truth our team at SynPlexity works with every day…biology is hard, and predictive modeling alone won’t solve it. The path forward depends on data: not just more of it, but the right kind, with the structure and context needed to make learning possible.

That’s where SynPlexity comes in. Our platform uses Broad Mutational Scanning (BMS) to accelerate biological discovery by systematically mapping how sequence variation drives function. This approach creates the dense, structured data that AI models need, data that includes both “yes” and “no,” success and failure.

While many in the field hope to model biology directly, the reality is that biology still resists simple parameter tuning. SynPlexity’s mission is to change that by building the datasets that make predictive biology possible. To model biology, we first have to measure it — at scale.

[We Still Can't Predict Much of Anything in Biology] (https://blog.genesmindsmachines.com?utm_source=navbar&utm_medium=web)