How to Build Drug Discovery AI Agents

💰 I 𝗿𝗲𝘃𝗲𝗿𝘀𝗲-𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗲𝗱 a 𝗯𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 Medical AI Agents paper so 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗯𝘂𝗶𝗹𝗱 𝗶𝘁 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳. Replaces $𝟭.𝟱𝗠 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀. Gets AI to 𝗽𝗮𝘁𝗶𝗲𝗻𝘁 𝗯𝗲𝗱𝘀𝗶𝗱𝗲.

Most medical AI dies in deployment.

Why? 

+ Clinicians don't trust black-box AI.
+ Data scientists waste 80% of their time cleaning messy data. 

While
- Hospitals spend $1.5M per year. 
- BUT End up with Broken systems. 

This paper solves it with six helper agents.

I rebuilt it with 𝗣𝘆𝘁𝗵𝗼𝗻 𝘂𝘀𝗶𝗻𝗴 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵. 
Here's how it works:

》𝗔𝗴𝗲𝗻𝘁 𝟭 : File Reader 

✸ Reads CSV, Excel, JSON, ZIP files instantly 
✸ Opens folders inside zip files automatically
✸ Sends each file to the right place

→ Result: You never touch files manually.

》𝗔𝗴𝗲𝗻𝘁 𝟮: Privacy Guard

✸ Finds names, emails, patient IDs, social security numbers 
✸ Hides sensitive info with **** 
✸ Blacks out text in medical images

→ Result: Privacy protection happens automatically.

》𝗔𝗴𝗲𝗻𝘁 𝟯: Data Reader

✸ Spreadsheets: Grabs column names like "age" and "diagnosis" 
✸ Images: Figures out scan type (like "colon scan") 
✸ Images: Spots what disease it shows (like "Polyp")

→ Result: System understands what your data is about.

》𝗔𝗴𝗲𝗻𝘁 𝟰: Model Matcher

✸ Creates a unique ID for each data column 
✸ Finds the AI model that fits your data best 
✸ Removes columns you don't need

→ Tools: Medical database + Model library.

》𝗔𝗴𝗲𝗻𝘁 𝟱: Data Preparer

✸ Labels columns: yes/no, categories, numbers, or text 
✸ Cleans big datasets automatically (over 50MB) 
✸ Gets images ready for each specific model

→ Result: Data matches model perfectly.

》𝗔𝗴𝗲𝗻𝘁 𝟲: Predictor + Explainer

✸ Fast method for small data, deep learning for big data 
✸ Shows which 10 factors mattered most 
✸ Highlights important areas in medical images

→ Result: Doctors see WHY, not just the answer.

》𝗧𝗲𝘀𝘁𝗲𝗱 on Real Patient Data:
✸ Predicting falls in elderly patients. 
✸ Measuring anxiety in end-of-life care. 
✸ Finding polyps in colon scans.

》𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 Used:
Google tools · 
Privacy scanner · 
Medical AI models · 
Image detector · 
Explanation tools

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👩‍💻 Written by Dr. Maryam Miradi
CEO & Chief AI Scientist
 I train STEM professionals to master real-world AI Agents.