Forum on immune digital twins: a meeting report
Reinhard Laubenbacher (1), Fred Adler (2), Gary An (3), Filippo, Castiglione (4), Stephen Eubank (5), Luis L. Fonseca (1), James Glazier (6),, Tomas Helikar (7), Marti Jett-Tilton (8), Denise Kirschner (9), Paul Macklin, (6), Borna Mehrad (1), Beth Moore (9)

TL;DR
This report summarizes an international expert meeting on developing immune system digital twins, highlighting challenges, ongoing projects, and proposing a 5-year plan to advance personalized immune modeling in medicine.
Contribution
It provides a comprehensive overview of current efforts, challenges, and strategic recommendations for creating digital twins of the immune system in personalized medicine.
Findings
Identification of key questions for immune digital twin development
Description of ongoing digital twin projects
Proposal of a 5-year strategic action plan
Abstract
Medical digital twins are computational models of human biology relevant to a given medical condition, which can be tailored to an individual patient, thereby predicting the course of disease and individualized treatments, an important goal of personalized medicine. The immune system, which has a central role in many diseases, is highly heterogeneous between individuals, and thus poses a major challenge for this technology. If medical digital twins are to faithfully capture the characteristics of a patient's immune system, we need to answer many questions, such as: What do we need to know about the immune system to build mathematical models that reflect features of an individual? What data do we need to collect across the different scales of immune system action? What are the right modeling paradigms to properly capture immune system complexity? In February 2023, an international group…
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Taxonomy
TopicsBiomedical and Engineering Education · Cell Image Analysis Techniques · Single-cell and spatial transcriptomics
