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QSP Cycle

Cutting Model Translation Time With Pumas-QSP Importers

This webinar answers the question - How do you use performance research without having to go through the painstaking model development steps again?

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Julia collaboration has taken a revolutionary leap forward with JuliaHub Projects.

Tuesday, April 25th | 1:00 PM ET (US)

Cutting Model Translation Time with Pumas-QSP Importers

Building accurate and comprehensive models takes months and involves many iterations of refinement. Model codes are hard to reproduce and reuse, and it takes a long time to generate appealing figures to visualize the results. You, the modeler, know the challenges involved.

How do you use this performance research without having to go through the painstaking model development steps again? This webinar will cover how to import models from community standards and describe complete optimization problems without knowing Julia. We will show how to leverage PEtab, a spreadsheet & SBML-based format, which is growing in popularity in systems biology.

In this demo, we will:

  • Specify a full optimization problem with the PEtab format 
  • Import SBML and BioNetGen models together with CSV data

  • Visualize your virtual population

  • Generate a report of the optimization results

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Model Discovery

Combine models with tools like DiffEqFlux and NeuralPDE to discover missing physics and generate digital twins.

Combine with Pre-Built Models and Digital Twins

Grab complete models from the JuliaSim Model Store and compose the pieces to accelerate the design process.

Specialized Numerical Environments

Use the latest numerical tools, like discontinuity-aware differential equation solvers, high-performance steady state solvers, and domain-specific environments.

Blending classical physical modeling with modern Scientific Machine Learning techniques.


JuliaSim is a next generation cloud-based simulation platform, combining the latest techniques in Scientific Machine Learning with equation-based digital twin modeling and simulation. Our modern ML-based techniques accelerate simulation by up to 500x, changing the paradigm of what is possible with computational design. The premise of the software is to facilitate the design and accelerate challenging real-life models of considerable complexity.


JuliaSim allows the user to import models directly from the Model Store (more information below) into the Julia environment, making it easy to build large complex simulations. The user-friendly GUI facilitates the process and makes simulation more accessible to a wider audience.


JuliaSim produces surrogates of blackbox (and regular) dynamical systems using Continuous Time Echo State Networks (CTESNs). This novel technique allows, amongst other features, for implicit training in parameter space to stabilize the ill-conditioning present in stiff systems.

Learn more about the JuliaSim Ecosystem

Julia Computing delivers JuliaSim as an answer to accelerating simulations through digital-twin (or surrogate) modeling. By blending classical, physical modeling with advanced scientific machine learning (SciML) techniques, JuliaSim provides a next-generation platform for building, accelerating, and analyzing models.