https://github.com/certara/certara-iq-vpop-training-1
A first training project for virtual population calibration with Certara IQ
https://github.com/certara/certara-iq-vpop-training-1
Last synced: 21 days ago
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A first training project for virtual population calibration with Certara IQ
- Host: GitHub
- URL: https://github.com/certara/certara-iq-vpop-training-1
- Owner: certara
- Created: 2025-10-17T17:26:51.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-10-17T23:35:44.000Z (9 months ago)
- Last Synced: 2025-10-30T01:55:37.872Z (9 months ago)
- Language: Jupyter Notebook
- Size: 141 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Virtual Population Training 1
This project introduces the Virtual Population (VPop) training workflow in Certara IQ, demonstrating how mechanistic models
can be used to simulate diverse virtual patients after calibrating a virtual population against observed data.
## Overview
### Objective:
Train and evaluate a virtual population that matches observed data distributions using Certara IQ’s modeling and simulation framework.
### Core workflow:
Propose candidate patient parameterizations
Simulate the model across all proposals
Select those forming a population consistent with observed or target distributions
## Where to start
Begin with `training_1_vpop.ipynb`. There is an accompanying solution file.