Workflow-first, not tool-worship
The focus is why a step belongs in your pipeline and what evidence it produces — not memorizing one docking command. Tools change; reasoning lasts.
Who's behind DeepDrug AI
Practitioners,
not marketers.
DeepDrug AI is a small, practitioner-led program built by someone working in computational drug discovery and machine learning, based in the EU. It exists for one reason: too many in-silico workflows are copied protocol-by-protocol without scientific reasoning — and that's exactly the habit this cohort is built to break.
You don't have to take it on faith
The standard is visible before you pay a cent. Judge the work, then decide.
Validation over vibes
Pose checks, applicability domains, uncertainty, scaffold-split thinking. The same scrutiny a real project would demand of you, applied from day one.
Judge before you join
Read the blog. Open the full program. The depth there is the credential — if it doesn't read like the work of someone who does this professionally, don't sign up.
Real science, not protocol cloning
This program is run by a computational drug-discovery practitioner. No fluff, no protocol-cloning — the work on the blog and in the curriculum is the credential, and it's all open for you to inspect first.
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