RESUMEN
Digital twins, customized simulation models pioneered in industry, are beginning to be deployed in medicine and healthcare, with some major successes, for instance in cardiovascular diagnostics and in insulin pump control. Personalized computational models are also assisting in applications ranging from drug development to treatment optimization. More advanced medical digital twins will be essential to making precision medicine a reality. Because the immune system plays an important role in such a wide range of diseases and health conditions, from fighting pathogens to autoimmune disorders, digital twins of the immune system will have an especially high impact. However, their development presents major challenges, stemming from the inherent complexity of the immune system and the difficulty of measuring many aspects of a patient's immune state in vivo. This perspective outlines a roadmap for meeting these challenges and building a prototype of an immune digital twin. It is structured as a four-stage process that proceeds from a specification of a concrete use case to model constructions, personalization, and continued improvement.
RESUMEN
Diseases are often a result of multiple malfunctions in complex, nonlinear biological/biochemical networks. As such, these processes are far more complicated to understand because they tend to give rise to functions that are emergent in nature, i.e., higher-level (mal)functions that are more than the sum of their parts. Systems biology provides a new approach to understanding biological systems and diseases from a holistic perspective.
