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A modular computational framework for medical digital twins

What is being modeled?
A modular computational framework for medical digital twins
Description & purpose of resource

This paper presents a modular software design for the construction of computational modeling technology that will help implement precision medicine. In analogy to a common industrial strategy used for preventive maintenance of engineered products, medical digital
twins are computational models of disease processes calibrated to individual patients using multiple heterogeneous data streams.
They have the potential to help improve diagnosis, prognosis, and personalized treatment for a wide range of medical conditions.
Their large-scale development relies on both mechanistic and data-driven techniques and requires the integration and ongoing update
of multiple component models developed across many different laboratories. Distributed model building and integration requires an open-source modular software platform for the integration and simulation of models that is scalable and supports a decentralized,
community-based model building process. This paper presents such a platform, including a case study in an animal model of a respiratory fungal infection.

Spatial scales
whole organism
Temporal scales
<10-6 s (chemical reactions)
10-6 - 10-3 s
10-3 - 1 s
1 - 103 s
This resource is currently
under early-stage development
mature and useful in ongoing research
Has this resource been validated?
Can this resource be associated with other resources? (e.g.: modular models, linked tools and platforms)
Key publications (e.g. describing or using resource)
  • Masison, J., J. Beezley, Y. MeiH. a. L. RibeiroA. C. Knapp, L. Sordo Vieira, B. Adhikari, et al. “A Modular Computational Framework for Medical Digital Twins.” Proceedings of the National Academy of Sciences 118, no. 20 (May 18, 2021).
J. Masison
J. Beezley
Y. Mei
H. al Ribiero
A. C. Knapp
L. Sordo Vieira
B. Adhikari
Y. Scindia
M. Grauer
B. Helba
W. Schroeder (PI)
B. Mehrad (PI)
R. Laubenbacher (PI)
PI contact information
R. Laubenbacher (
Steady-state binding
Modular design
Slow binding
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