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This project uses python, pandas, and matplotlib to analyze the efficacies of cancer-treating drugs on metastatic spread and survival rates.

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Matplotlib-Challenge

This project uses python, pandas, and matplotlib to analyze the efficacies of cancer-treating drugs on metastatic spread and survival rates.

Study Findings

This study focused on the treatment drug effects of Capomulin, Infubinol, and Ketapril, as well as a placebo therapy during mice trials. The drug Capomulin was the only drug of the four compared variables (Capomulin,Infubinol, Ketapril, and Placebo) that actually decreased tumor size instead of just slowing down the progression of tumor mass increase.

Furthermore, Capomulin was the most effective at reducing the rate of metatastic spread compared to placebo and the other two study drugs in the course of the experiment.

Mouse survival rates were also the highest in the group treated with Capomulin (over 80% survived the course of treatment of 45 days), compared to less than 50% mouse survival rate of the Placebo, Infubinol, Ketapril groups.

Overall, Capomulin had the highest efficacy on the study trials on mice, and is the best choice out of the drugs analyzed in this study in continuing further trials and investment for cancer therapy.


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LinkedIn: https://www.linkedin.com/in/marsha-vongjesda/

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This project uses python, pandas, and matplotlib to analyze the efficacies of cancer-treating drugs on metastatic spread and survival rates.

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