Drug Discovery
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Finding a new drug is like searching for a specific grain of sand on a beach - blindfolded. As an ML engineer in drug discovery, I get to build tools that make this process less painful.
The Quick and Dirty on Drug Discovery
You find a protein that’s causing trouble, design a molecule to fix it, make sure it won’t kill anyone, and prove it works. Simple, right? Except it takes 10-15 years and costs billions. That’s where ML comes in.
ML’s Superpowers
Target Finder: Instead of manually digging through data, we train models to spot promising drug targets. Like having a really good metal detector.
Molecule Designer: We’ve got AI that can dream up new molecules with specific properties. Want something that can cross the blood-brain barrier? Just tweak the parameters.
Crystal Ball: We can predict if a molecule will be toxic or work in the body. Not perfect, but way better than testing everything in the lab.
Trial Optimizer: ML helps match the right patients with the right trials. Think Tinder, but for drugs and people.
The Catch
It’s not all smooth sailing. We’re still dealing with limited data, black box models, and skeptical scientists. But that’s what keeps it interesting! Every day, we’re finding new ways to make drug discovery faster and more efficient. Who knows? Maybe one day we’ll have an AI that can design the perfect drug in minutes. Until then, we’ll keep iterating and debugging our way to better medicines.