Evidence map›Paper›PMID 33402434›Full record

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

In silico dynamics of COVID-19 phenotypes for optimizing clinical management.

Chrysovalantis Voutouri, Mohammad Reza Nikmaneshi, C Corey Hardin, Ankit B Patel, Ashish Verma, Melin J Khandekar, Sayon Dutta, Triantafyllos Stylianopoulos, Lance L Munn, Rakesh K Jain

Open access · hybridAbstract 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 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
2.7field-weighted citation impact, top 8% of its field
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

34 citing papers in PubMed, 52 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Dynamic metabolic modelling of ATP allocation during viral infection.Journal of the Royal Society, Interface · 2026
    Article
  5. Article
  6. Spatially structured models of viral dynamics: a scoping review.Microbiology and molecular biology reviews : MMBR · 2025
    Article
  7. Article
  8. Article
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  13. Article
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  15. Review
  16. Drug Cocktail Formulation via Circuit Design.IEEE transactions on molecular, biological, and multi-scale communications · 2023
    Article
  17. Mechanistic model for booster doses effectiveness in healthy, cancer, and immunosuppressed patients infected with SARS-CoV-2.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 3 countries.

Chrysovalantis VoutouriCancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678 Nicosia, Cyprus.
Mohammad Reza NikmaneshiDepartment of Mechanical Engineering, Sharif University of Technology, Tehran, Iran, 11155.
C Corey HardinDepartment of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114.
Ankit B PatelDepartment of Medicine/Renal Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115.
Ashish VermaDepartment of Medicine/Renal Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115.ORCID https://orcid.org/0000-0001-9497-6327
Melin J KhandekarDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114.
Sayon DuttaDepartment of Emergency Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114.
Triantafyllos StylianopoulosCancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678 Nicosia, Cyprus; tstylian@ucy.ac.cy munn@steele.mgh.harvard.edu jain@steele.mgh.harvard.edu.ORCID https://orcid.org/0000-0002-3093-1696
Lance L MunnEdwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114; tstylian@ucy.ac.cy munn@steele.mgh.harvard.edu jain@steele.mgh.harvard.edu.
Rakesh K JainEdwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114; tstylian@ucy.ac.cy munn@steele.mgh.harvard.edu jain@steele.mgh.harvard.edu.ORCID https://orcid.org/0000-0001-7571-3548
Harvard University · USBrigham and Women's Hospital · USUniversity of Cyprus · CYSharif University of Technology · IR

Funding

Dissecting Pediatric Brain Tumor Microenvironment to Improve TreatmentR35CA197743 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI JAIN, RAKESH K. · 2015 to 2020
$5.7M
Reprogramming PDAC tumor microenvironment to improve immunotherapyU01CA224348 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BOUCHER, YVES, JAIN, RAKESH K. · 2017 to 2021
$2.9M
Systems biology of lymphatic transportR01HL128168 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI MUNN, LANCE L., PADERA, TIMOTHY P · 2015 to 2019
$2.9M
Reengineering obesity-induced abnormal microenvironment to improve PDAC treatmentR01CA208205 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI FUKUMURA, DAI, JAIN, RAKESH K. · 2017 to 2020
$2.2M
Multiplexed device for rapid coagulopathy testingR21EB031982 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI HARDIN, CHARLES COREY, MUNN, LANCE L. · 2021 to 2021
$462k
European Research CouncilNCI NIH HHS R01 CA208205NCI NIH HHS R35 CA197743NCI NIH HHS U01 CA224348NHLBI NIH HHS R01 HL128168NIBIB NIH HHS R21 EB031982NIH HHS R01 CA2044949
6 · The paper itself

Abstract

Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin-angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8

Indexed as

COVID-19 Drug TreatmentComputer SimulationCOVID-19CytokinesDisease ProgressionHumansImmunity, InnateModels, TheoreticalPhenotypeSARS-CoV-2CytokinesCOVID-19mathematical modelSARS-CoV-2simulation

Identifiers

PMID33402434
PMCPMC7826337
OpenAlexW3118385724

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.