Since the onset of the COVID-19 pandemic, Indiana University professor James Glazier has been focusing his research on creating a digital twin of the immune system, which could offer precision medicine for a wide array of ailments, including cancer, autoimmune diseases and viral infections such as COVID-19.
After publishing an initial perspective in 2021 calling for the creation of immune digital twins, the researchers realized that for the vision to become reality, a guide had to be developed. With that aim, the working group he co-founded -- the Multiscale Modeling and Viral Pandemics -- recently published "Building digital twins of the human immune system: toward a roadmap" in Nature's Digital Medicine.
The Multiscale Modeling and Viral Pandemics group is part of the U.S. Department of Health and Human Services' Interagency Modeling and Analysis Group and consists of more than 200 scientists spanning the globe. Co-founder Reinhard Laubenbacher, director of the Laboratory for Systems Medicine at the University of Florida, was co-leader until University of Nebraska-Lincoln biochemist Tomas Helikar assumed the role in May.
"One of the challenges with the variability and the speed of change of coronavirus is that treating it is very hard because we don't have the ability to develop new treatments as quickly as the virus changes," said Glazier, a professor in the IU Luddy School of Informatics, Computing and Engineering. "Another critical issue is that different people respond differently to the same virus and the same treatment. The treatment that helps when given at one time may be harmful when given at another. This is why you need an immune digital twin that predicts each individual's specific immune response."
The implications are vast; immune digital twins could be used to project disease trajectories in individual patients, allowing diagnosis before the onset of serious symptoms. They could be used to optimize the timing of medical care, identify biomarkers and more.
"To deliver an immune digital twin is a billion-dollar project and cannot be done by a single investigator," Glazier said. "This group and this roadmap are paving the way to make it happen. Now it seems much more tangible."
In addition to creating the roadmap, the group aims to establish a global alliance for predictive immunology.
The paper outlines 11 steps in a four-stage process to construct an immune digital twin.
- Stage 1: Define a specific application and construct an appropriate generic template model.
- Stage 2: Personalize the template model to an individual patient.
- Stage 3: Conduct final immune digital twin testing and uncertainty quantification.
- Stage 4: Continue to collect individual patient data for ongoing improvement of the immune digital twin.
Glazier, Helikar and Laubenbacher are among 10 authors from six universities on the current paper. Other contributors include two more from the Luddy School: T.J. Sego, a postdoctoral fellow at the IU Biocomplexity Institute, and Paul Macklin, associate professor and director of undergraduate studies in the Luddy School Department of Intelligent Systems Engineering.
The group also runs a virtual seminar series, which has included more than 100 lectures on modeling as it relates to viral infection and immune response. The series includes discussions from subject matter experts from industrial, clinical and academic backgrounds.
The IU Biocomplexity Institute develops open-source CompuCell3D software environment to simplify the construction of digital twins. It is hosting Multicell Virtual Tissue Modeling Online Summer School and Hackathon, a free opportunity for individuals to learn how to build this kind of computer simulation. The workshop will be held virtually July 31 to Aug. 7.