Clinical Trial Response Rates

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(999)

treatments = ['Standard', 'Experimental', 'Combination', 'Placebo']
data = []
for treat in treatments:
    n = 42
    dosage = np.random.uniform(10, 100, n)
    efficacy = {'Standard': 0.6, 'Experimental': 0.75, 'Combination': 0.85, 'Placebo': 0.15}
    response = efficacy[treat] * np.log(dosage + 1) * 10 + np.random.normal(0, 5, n)
    response = np.clip(response, 0, 100)
    for d, r in zip(dosage, response):
        data.append({'Dosage (mg)': d, 'Response Score': r, 'Treatment': treat})

df = pd.DataFrame(data)

sns.set_style("whitegrid", {
    'axes.facecolor': '#ffffff',
    'figure.facecolor': '#ffffff',
    'grid.color': '#eeeeee'
})

palette = ['#276CF5', '#F5276C', '#5314E6', '#888888']

g = sns.lmplot(
    data=df,
    x='Dosage (mg)',
    y='Response Score',
    hue='Treatment',
    col='Treatment',
    col_wrap=2,
    height=3.5,
    aspect=1.2,
    palette=palette,
    scatter_kws={'alpha': 0.7, 's': 50, 'edgecolor': 'white', 'linewidths': 0.6},
    line_kws={'linewidth': 2.5},
    ci=95
)

g.fig.set_facecolor('#ffffff')
for ax in g.axes.flat:
    ax.set_facecolor('#ffffff')
    for spine in ax.spines.values():
        spine.set_color('#dddddd')

g.fig.suptitle('Therapeutic Efficacy Comparison', fontsize=14, fontweight='bold', color='#1a1a1a', y=1.02)
plt.tight_layout()
plt.show()