PharmOptimizationModel

A Python project for pharmaceutical inventory optimization. Features a Streamlit dashboard for visualizing inventory trends, ARIMA-based demand forecasting, and large-scale data cleaning with Pandas and NumPy.

Created at the Rutgers Bits Datathon 2025 and presented to judges at Barclays.

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🚀 Key Features

📊 Streamlit Dashboard Visualize pharmaceutical inventory trends Interactive stock management tools Real-time data exploration

🔮 Demand Forecasting ARIMA time series forecasting Predict demand fluctuations Mitigate stockout/overstocking risks

🧹 Data Cleaning & Processing Processed & cleaned 600,000+ sales records Used Pandas and NumPy for data integrity Automated pipeline for large datasets

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🏗️ Technical Architecture

Core Scripts clean_data.py: Data cleaning pipeline app.py: Main optimization logic dashboard.py: Streamlit dashboard (if present)

Data Files sales_data.csv: Raw input data cleaned__salesmonthly.csv: Cleaned output

Documentation Pharmaceutical Inventory Optimization.pdf: Project report and methodology

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🛠️ Technologies

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🏁 Getting Started

System Requirements

• Python 3.7 or higher
• pip

Installation Steps

1. Clone the Repository

   git clone https://github.com/sameerj05/PharmOptimizationModel.git
   cd PharmOptimizationModel

2. Install Dependencies

   pip install -r requirements.txt

3. Clean the Data

   python clean_data.py

   • Processes sales_data.csv and outputs cleaned__salesmonthly.csv.

4. Run the Optimization Model

   python app.py

   • Uses the cleaned data to perform inventory optimization.

5. Launch the Streamlit Dashboard (if available)

   streamlit run dashboard.py

   • Visualize trends and interact with inventory data.

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🗂️ Project Structure

PharmOptimizationModel/
├── Pharmaceutical Inventory Optimization.pdf   # Project documentation
├── app.py                                     # Main application script
├── clean_data.py                              # Data cleaning script
├── cleaned__salesmonthly.csv                  # Cleaned sales data (sample)
├── sales_data.csv                             # Raw sales data (sample)
├── requirements.txt                           # Python dependencies
├── dashboard.py                               # Streamlit dashboard (if present)

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📄 Documentation

For a detailed explanation of the methodology and results, see Pharmaceutical Inventory Optimization.pdf.

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👥 Contributors

Mohammed Hossain  |   | 

Sameer Jiandani  |   | 

Rayyan Khatib  | 

Yassir Khan  | 

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This project was developed as a demonstration of pharmaceutical inventory optimization using Python, Streamlit, ARIMA, Pandas, and NumPy.
Created at the Rutgers Bits Datathon 2025 and presented to judges at Barclays.
Contributors: Mohammed Hossain, Sameer Jiandani, Rayyan Khatib, Yassir Khan.