Pymaceuticals

This is the submission of the Data Visualization Challenge called "Pymaceuticals" for Joe Portnoy.

I leveraged my class notes and code to complete the project while also using ChatGPT to debug.

The objective of the project was to generate tables and figures for the clinical study for Capomulin, a treatment regimen for squamous cell carcinoma (SCC), a commonly occurring form of skin cancer.

Analysis

I analyzed the relationship between mouse weight and tumor volume for various drug regimens (focused specifically in the Capomulin treatment).

The data showed that there was a strong correlation between the two, meaning that the heavier mice tend to have larger tumors.

This relationship could have practical applications for monitoring treatment progress, optimizing dosing strategies, and better understanding how weight influence treatment options.

Support for the Analysis

• Prediction

  • The weight of the mouse is a strong predictor of tumor size, making it a useful metric for managing treatment.

• Treatment

  • Heavier mice typically have larger tumors, suggesting dosages or treatments might need to be adjusted based on weight for better results.

• Consistency in Data

  • The data shows a clear, consistent trend with little variability, reinforcing the reliability of the weight-tumor relationship.