Clinical Trial Success Predictor

Using Python, SQL, and interactive visualizations, I've created a solution that transforms complex trial data into actionable insights.

The dashboard features:

Intuitive inputs for trial parameters (phase, patient count, duration)

Real-time success probability predictions using logistic regression

Visual representations of historical success rates and trends

Comprehensive analysis of factors influencing trial outcomes

This project demonstrates how data science can accelerate drug development by helping researchers identify promising trial designs before significant resources are committed. It's a perfect example of how predictive analytics can deliver immediate value in the pharmaceutical industry without requiring specialized in-house expertise.

I've leveraged Hex's collaborative features to create a polished, secure solution that can be easily shared with interested parties. The clean interface makes complex statistical concepts accessible to non-technical stakeholders.

If you're interested in learning more or seeing a demo of this tool, please reach out through the contact form on my website.