Forum on immune digital twins: a meeting report

Publikation: Beitrag in FachzeitschriftÜbersichtsartikel (Review)EingeladenBegutachtung

Beitragende

  • Reinhard Laubenbacher - , University of Florida (Autor:in)
  • Fred Adler - , University of Utah (Autor:in)
  • Gary An - , University of Vermont (Autor:in)
  • Filippo Castiglione - , Technology Innovation Institute (TII) (Autor:in)
  • Stephen Eubank - , University of Virginia (Autor:in)
  • Luis L Fonseca - , University of Florida (Autor:in)
  • James Glazier - , Indiana University Bloomington (Autor:in)
  • Tomas Helikar - , University of Nebraska-Lincoln (Autor:in)
  • Marti Jett-Tilton - , Walter Reed Army Institute of Research (Autor:in)
  • Denise Kirschner - , University of Michigan, Ann Arbor (Autor:in)
  • Paul Macklin - , Indiana University Bloomington (Autor:in)
  • Borna Mehrad - , University of Florida (Autor:in)
  • Beth Moore - , University of Michigan, Ann Arbor (Autor:in)
  • Virginia Pasour - , United States Army Research Office (Autor:in)
  • Ilya Shmulevich - , Institute for Systems Biology (Autor:in)
  • Amber Smith - , University of Tennessee Health Science Center (UTHSC) (Autor:in)
  • Isabel Voigt - , Klinik und Poliklinik für Neurologie, Universitätsklinikum Carl Gustav Carus Dresden (Autor:in)
  • Thomas E Yankeelov - , University of Texas MD Anderson Cancer Center (Autor:in)
  • Tjalf Ziemssen - , Klinik und Poliklinik für Neurologie, Universitätsklinikum Carl Gustav Carus Dresden (Autor:in)

Abstract

Medical digital twins are computational models of human biology relevant to a given medical condition, which are 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. In February 2023, an international group of experts convened for two days to discuss these challenges related to immune digital twins. The group consisted of clinicians, immunologists, biologists, and mathematical modelers, representative of the interdisciplinary nature of medical digital twin development. A video recording of the entire event is available. This paper presents a synopsis of the discussions, brief descriptions of ongoing digital twin projects at different stages of progress. It also proposes a 5-year action plan for further developing this technology. The main recommendations are to identify and pursue a small number of promising use cases, to develop stimulation-specific assays of immune function in a clinical setting, and to develop a database of existing computational immune models, as well as advanced modeling technology and infrastructure.

Details

OriginalspracheEnglisch
Aufsatznummer19
Seitenumfang8
Fachzeitschriftnpj systems biology and applications
Jahrgang10
Ausgabenummer1
PublikationsstatusVeröffentlicht - 16 Feb. 2024
Peer-Review-StatusJa

Externe IDs

PubMedCentral PMC10873299
Scopus 85185409105
ORCID /0000-0001-8799-8202/work/176343725
ORCID /0000-0003-0097-8589/work/176344432

Schlagworte

Schlagwörter

  • Humans, Databases, Factual, Precision Medicine