Perspective: Building digital twins of the human immune system: toward a roadmap. Image Credit: metamorworks / Shutterstock

A digital twin for your immune system

In a recent study posted to the NPJ Digital Medicine magazine, researchers illustrated a framework for constructing digital twins of the human immune system.

Perspective: Building digital twins of the human immune system: towards a roadmap† Image Credit: Metamorworks/Shutterstock

Background

Digital twins, personalized simulation models established in the industry, are now being used in healthcare and medicine, with several notable results such as insulin pump control and cardiovascular diagnostics. Custom calculation models can help with everything from drug research to therapy optimization. Additional advanced medical digital twins are needed to make precision medicine a reality.

Digital twins of the immune system can have a significant impact, as the immune system is involved in many diseases and health problems, from fighting pathogens to autoimmune diseases. Nevertheless, due to the intrinsic diversity of the immune system and the complexity of evaluating many components of a patient’s immunological status in vivoposes major challenges for their development.

About the study

In the current perspective article, the authors described a high-level outline of a path to address the issues and develop an immune digital twin (IDT) prototype. The framework was designed as a four-stage approach that included a description of a concrete application case, the construction of a model, customization and constant improvement.

At each relevant physiological scale, known biology and relevant mechanisms are characterized through data collection informing one or more computer models.  The models on the individual scales are then integrated into a comprehensive base model with multiple scales.  In the second step, this basic model is personalized by parameterizing it with data collected from an individual patient.  The resulting digital twin can then be used for clinical decision making for this patient.  (The images are public domain images from Servier Medical Art (https://smart.servier.com/smart_image/tendon-anatomy/), https://all-free-download.com/free-vector/flat- screen-computer-monitor.html, and https://pixabay.com/vectors/man-male-boy-human-people-persons-2099114/).  All other images are created by the authors).  Image Credit: npj Digital Medicine (npj Digit. Med.) ISSN 2398-6352 (online)

At each relevant physiological scale, known biology and relevant mechanisms are characterized through data collection informing one or more computer models. The models on the individual scales are then integrated into a comprehensive base model with multiple scales. In the second step, this basic model is personalized by parameterizing it with data collected from an individual patient. The resulting digital twin can then be used for clinical decision making for this patient. (The images are public domain images from Servier Medical Art (https://smart.servier.com/smart_image/tendon-anatomy/https://all-free-download.com/free-vector/flat-screen-computer-monitor.htmland https://pixabay.com/vectors/man-male-boy-human-people-persons-2099114/† All other images are created by the authors). Image Credit: npj Digital Medicine (npj Digit. Med.) ISSN 2398-6352 (online)

The current IDT prototype promotes collaboration between the global non-profit scientific community, government funders and the private sector. Such an approach requires a collaborative platform and broad consensus on the characteristics of the final outcome. For example, the newly established European-led DigiTwin consortium, which includes clinical, industrial and academic staff from 32 countries, plans to generate digital twins for every European citizen across multiple conditions and could serve as a model for different elements of a international consortium for IDTs.

The four-stage paradigm for industrial digital twin creation will be followed in the development of an IDT and consisted of: 1) setting up a specific application and building an appropriate generic template model, 2) adapting the template model to a specific patient, 3) the final IDT assessment and uncertainty quantification, and 4) the collection of individual patient data for continuous IDT improvement.

Findings, discussions and conclusions

The current perspective research provided a high-level framework for advancing the IDT technique in clinical and biomedical settings. While IDTs face significant scientific and technical challenges, even basic application specifics would help focus ongoing data collection and other improvements, leading to increasingly customized simulation models over time.

The authors recommend using a Predictive Immunology Consortium to bring together the currently disparate transdisciplinary scientists needed to make IDTs a reality. Closely merging modeling and clinical implementation, this integrated human infrastructure could help change the hallmark of biomedical research by significantly accelerating the journey from couch to bed and achieving currently unattainable medical goals. It would also open up a whole host of new training models for computational and biological researchers.

The team foresees a seven-year project with two phases. The first planning process takes two years. During this period, the application, a theoretical map of the IDT, the infrastructure and the composition of the cohort of partners will be defined. The first step was to gather stakeholders such as modellers, clinicians, immunologists, commercial entities, funders, and software engineers to identify targets and techniques. The goal was to (1) create a small number of potential IDT technology applications; (2) a steering committee that could initiate and organize the next steps; and (3) a list of funding sources, starting with resources for a planning phase.

Over the next three years, the consortium will build and test a prototype model of the IDTs and the computing infrastructure that supports them. In the last two years, the IDTs will be validated under patient studies. Furthermore, the consortium should be financially supported as one cohesive project with many implementation sites, with resources for modelling, software development, experimental and clinical assessments and validation.

In particular, the researchers underline the enormous hurdles that such a project entails. The complexity and cost were equal to the Cancer Moonshot Program, funded by the United States National Institutes of Health for $1.8 billion over seven years. IDT may need innovative measurement technologies depending on the initial applications. In addition, major new scientific discoveries and technological breakthroughs will be needed to obtain IDTs accurate and robust enough to meet industry standards.

Overall, the current work shows that the IDT technique was within human reach. The authors mentioned that because the immune system has been implicated in almost all major diseases that people face, such as cardiac, infectious, autoimmune and respiratory disorders, the impact of IDT could be enormous. In addition, they indicated that the time has come to start developing IDT techniques.

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