bio_sim_v10.py

import numpy as np
import plotly.graph_objects as go

class MetabolicTwinV10:
    def __init__(self):
        # Clearance factors based on genotype (1.0 = Normal)
        self.phenotype_map = {
            "Poor": 0.2,
            "Intermediate": 0.5,
            "Normal": 1.0,
            "Rapid": 1.5
        }

    def simulate_drug_clearance(self, drug_name, phenotype="Normal"):
        """
        Simulates serum concentration over 48 hours using a 
        one-compartment pharmacokinetic model.
        """
        factor = self.phenotype_map.get(phenotype, 1.0)
        t = np.linspace(0, 48, 100)
        
        # Simple PK Formula: C(t) = (Dose/V) * exp(-ke * t)
        # We adjust the elimination constant (ke) by the genomic factor
        ke = 0.1 / factor 
        concentration = 100 * np.exp(-ke * t)
        
        fig = go.Figure()
        fig.add_trace(go.Scatter(x=t, y=concentration, mode='lines', 
                                 name=f"{drug_name} ({phenotype})",
                                 line=dict(color='#4285f4' if factor == 1.0 else '#ea4335')))
        
        fig.update_layout(
            title=f"Metabolic Stress Test: {drug_name}",
            xaxis_title="Hours Post-Dose",
            yaxis_title="Serum Concentration (%)",
            paper_bgcolor='rgba(0,0,0,0)',
            plot_bgcolor='rgba(0,0,0,0)',
            font_color="#e0e0e0"
        )
        return fig