digital-twin-patient-builder

name	digital-twin-patient-builder
description	Build digital twin patient models to test drug efficacy and toxicity in virtual environments
version	1.0.0
category	AI/Tech
tags	[]
author	AIPOCH
license	MIT
status	Draft
risk_level	High
skill_type	Hybrid (Tool/Script + Network/API)
owner	AIPOCH
reviewer
last_updated	2026-02-06

Digital Twin Patient Builder (ID: 208)

Function Overview

Build a "digital twin" model of a patient, integrating genotype, clinical history, and imaging data to test the efficacy and toxicity of different drug doses in a virtual environment.

Use Cases

• Personalized drug treatment plan design
• Drug dose optimization
• Adverse reaction risk assessment
• Clinical trial virtual simulation

Input

Data Type	Description	Format
genotype	Patient genotype data (SNPs, CNVs)	JSON
clinical_history	Clinical history and laboratory indicators	JSON
imaging_features	Imaging features (MRI, CT, etc.)	JSON

Output

Output Type	Description
efficacy_prediction	Efficacy prediction results
toxicity_prediction	Toxicity reaction prediction
optimal_dose	Optimal dose recommendation

Usage

Command Line Usage

python scripts/main.py --patient patient_data.json --drug drug_profile.json --doses "[50, 100, 150]"

Parameters

Parameter	Type	Default	Required	Description
--patient	string	-	Yes	Path to patient data JSON file
--drug	string	-	Yes	Path to drug profile JSON file
--doses	string	-	Yes	Dose range to test (JSON array format)
--output, -o	string