A modular computational framework for medical digital twins

Abstract

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.

Digital Twins: From Personalised Medicine to Precision Public Health

“…Individual modules are only indirectly connected by communicating through a central data structure, the global digital twin model state, rather than exchanging data with each other directly. This approach has a key advantage of preventing any direct dependencies between the computational side of modules, enabling the digital twin model to be easily extended or modified [ 37 ].…”

Building digital twins of the human immune system: toward a roadmap

“…The IDT template model could be composed of many different modules combined in a plug-and-play fashion, for instance using the Python-based hub-and-spokes architecture proposed in ref. 31 . This approach has the advantage that all sub-models access and modify the global model state only, without interacting with each other directly.…”

A Modular Digital Twinning Framework for Safety Assurance of Collaborative Robotics

“…These challenges are also highlighted in a recent review (Lu et al, 2020), emphasising the need for standardisation (with respect to communication mechanisms, model representation and protocols), based on existing industrial standards where appropriate. Masison et al (2021) present a framework to support collaboration and distributed modelling of medical processes using a modular design pattern. The example given centres on infection modelling in the respiratory system and their results are compared to a conventional simulation model.…”