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3D Molecular Intelligence: Accelerating Drug Discovery through Predictive Analytics
The Impact: This project addresses a critical bottleneck in pharmaceutical research: determining molecular solubility (logS). By replacing slow, expensive lab tests with high-precision machine learning, this system enables scientists to screen thousands of compounds in seconds, significantly reducing the cost and time required to bring new life-saving drugs to market.
Drastic Cost Reduction: The predictive pipeline reduces early-stage experimental screening costs by 70–90%, allowing research teams to focus resources on the most promising drug candidates.
High-Precision Forecasting: Utilizing a hybrid 3D feature engineering approach, the system achieves a remarkable 91.3% accuracy (R² score) in predicting solubility, providing a highly reliable alternative to physical testing.
Accelerated R&D Cycles: By automating the identification of viable molecules, the tool dramatically shortens the "hit-to-lead" time in pharma and materials science, getting products to market faster.
Empowering Researchers: I deployed a professional Streamlit dashboard featuring an interactive 3D molecular viewer. This allows non-technical chemists to visualize complex structures and make data-driven decisions without needing to write a single line of code
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Great work on this Power BI HR dashboard! The employee rating analysis and demographic breakdown sections are really well done. I’m also working on similar HR analytics projects, and this gives me so many ideas. What was the most challenging part you faced when building it?
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I enjoy building practical Python tools that solve real problems through automation and clean logic.
#Python #Automation #CLI #DataEngineering #Backend
good work Bhawna !
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