Evidence map›Paper›PMID 33972437›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

A modular computational framework for medical digital twins.

J Masison, J Beezley, Y Mei, Hal Ribeiro, A C Knapp, L Sordo Vieira, B Adhikari, Y Scindia, M Grauer, B Helba and 3 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Integration of microphysiological systems with computational and digital twin modeling for pharmaceutical development: a systematic review.Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2026
    Pooled it
  2. Review
  3. Review
  4. Digital Twin Technology In Radiology.Journal of imaging informatics in medicine · 2026
    Review
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Personalizing computational models to construct medical digital twins.Journal of the Royal Society, Interface · 2025
    Article
  11. Review
  12. Article
  13. Review
  14. Control of medical digital twins with artificial neural networks.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
  15. Review
  16. Review
  17. Personalizing computational models to construct medical digital twins.bioRxiv : the preprint server for biology · 2024
    Article
  18. Challenges and directions for digital twin implementation in otorhinolaryngology.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024
    Review
  19. Review
  20. Forum on immune digital twins: a meeting report.NPJ systems biology and applications · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

J MasisonCenter for Quantitative Medicine, University of Connecticut Health Center, Farmington, CT 06032.ORCID 0000-0003-2113-9282
J BeezleyKitware Inc., Clifton Park, NY 12065.
Y MeiDepartment of Computer Science, University of Michigan, Ann Arbor, MI 48109.
Hal RibeiroDepartment of Medicine, University of Florida, Gainesville, FL 32611.ORCID 0000-0001-9802-5211
A C KnappDepartment of Medicine, University of Florida, Gainesville, FL 32611.
L Sordo VieiraDepartment of Medicine, University of Florida, Gainesville, FL 32611.
B AdhikariCenter for Quantitative Medicine, University of Connecticut Health Center, Farmington, CT 06032.
Y ScindiaDepartment of Medicine, University of Florida, Gainesville, FL 32611.ORCID 0000-0001-6382-6289
M GrauerKitware Inc., Clifton Park, NY 12065.
B HelbaKitware Inc., Clifton Park, NY 12065.ORCID 0000-0003-2628-805X
W SchroederKitware Inc., Clifton Park, NY 12065.
B MehradDepartment of Medicine, University of Florida, Gainesville, FL 32611.ORCID 0000-0001-5198-065X
R LaubenbacherDepartment of Medicine, University of Florida, Gainesville, FL 32611 reinhard.laubenbacher@medicine.ufl.edu.ORCID 0000-0002-9143-9451

Funding

Multiscale modeling of the role of heme during invasive pulmonary aspergillosisR01AI135128 · NIAID · UNIVERSITY OF FLORIDA · PI REINHARD LAUBENBACHER, Borna Mehrad · 2018 to 2026
$4.9M
Skeletal, Craniofacial and Oral Biology Training GrantT90DE021989 · NIDCR · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI MINA, MINA · 2011 to 2022
$4.5M
Modular design of multiscale models, with an application to the innate immune response to fungal respiratory pathogens.U01EB024501 · NIBIB · UNIVERSITY OF FLORIDA · PI LAUBENBACHER, REINHARD, MEHRAD, BORNA · 2017 to 2020
$2.9M
Control of heterogeneous microbial communities using model-based multi-objective optimizationR01GM127909 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI DONGARI-BAGTZOGLOU, ANNA I, LAUBENBACHER, REINHARD · 2018 to 2021
$1.8M
NIAID NIH HHS R01 AI135128NIBIB NIH HHS U01 EB024501NIDCR NIH HHS T90 DE021989NIGMS NIH HHS R01 GM127909
6 · The paper itself

Abstract

This paper presents a modular software design for the construction of computational modeling technology that will help implement precision medicine. In analogy to a common industrial strategy used for preventive maintenance of engineered products, medical digital twins are computational models of disease processes calibrated to individual patients using multiple heterogeneous data streams. They have the potential to help improve diagnosis, prognosis, and personalized treatment for a wide range of medical conditions. Their large-scale development relies on both mechanistic and data-driven techniques and requires the integration and ongoing update of multiple component models developed across many different laboratories. Distributed model building and integration requires an open-source modular software platform for the integration and simulation of models that is scalable and supports a decentralized, community-based model building process. This paper presents such a platform, including a case study in an animal model of a respiratory fungal infection.

Indexed as

Patient-Specific ModelingSoftwareAlgorithmsAnimalsAntifungal AgentsAspergillosisAspergillus fumigatusComputational BiologyHumansPrecision MedicineSpores, FungalAntifungal Agentsmedical digital twinmodular designmultiscale computational model

Identifiers

PMID33972437
PMCPMC8157963

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.