Evidence map›Paper›PMID 33841175›Full record

ReviewFrontiers in physiology2021

History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications.

Karim Azer, Chanchala D Kaddi, Jeffrey S Barrett, Jane P F Bai, Sean T McQuade, Nathaniel J Merrill, Benedetto Piccoli, Susana Neves-Zaph, Luca Marchetti, Rosario Lombardo and 3 more

Abstract readReview
In one paragraph

Review in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
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  12. Towards a comprehensive assessment of QSP models: what would it take?Journal of pharmacokinetics and pharmacodynamics · 2024
    Review
  13. Article
  14. Article
  15. Review
  16. Article
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  18. Article
  19. In Silico Clinical Trials: Is It Possible?Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  20. 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.

Karim AzerQuantitative Sciences, Bill and Melinda Gates Medical Research Institute, Cambridge, MA, United States.
Chanchala D KaddiQuantitative Sciences, Bill and Melinda Gates Medical Research Institute, Cambridge, MA, United States.
Jeffrey S BarrettCritical Path Institute, Tucson, AZ, United States.
Jane P F BaiOffice of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, United States.
Sean T McQuadeCenter for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States.
Nathaniel J MerrillCenter for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States.
Benedetto PiccoliDepartment of Mathematical Sciences and Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States.
Susana Neves-ZaphTranslational Disease Modeling, Data and Data Science, Sanofi, Bridgewater, NJ, United States.
Luca MarchettiFondazione the Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
Rosario LombardoFondazione the Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
Silvia ParoloFondazione the Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
Selva Rupa Christinal ImmanuelInstitute for Systems Biology, Seattle, WA, United States.
Nitin S BaligaInstitute for Systems Biology, Seattle, WA, United States.

Funding

Technology CoreU19AI106761 · NIAID · SEATTLE BIOMEDICAL RESEARCH INSTITUTE · PI SHERMAN, DAVID R, ZAK, DANIEL E · 2013 to 2017
$18.9M
Technology CoreU19AI135976 · NIAID · SEATTLE CHILDREN'S HOSPITAL · PI ADEREM, ALAN A · 2018 to 2022
$17.0M
A systems analysis of drug tolerance in Mycobacterium tuberculosisR01AI128215 · NIAID · INSTITUTE FOR SYSTEMS BIOLOGY · PI Nitin S Baliga · 2017 to 2026
$8.8M
Site Specific Immunophenotyping Assays of COVID19 Patients to Align with NIAID National StudyR01AI141953 · NIAID · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2019 to 2023
$5.7M
NIAID NIH HHS R01 AI128215NIAID NIH HHS R01 AI141953NIAID NIH HHS U19 AI106761NIAID NIH HHS U19 AI135976
6 · The paper itself

Abstract

Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.

Indexed as

bioinformaticscomputational biologydata sciencedrug developmentQSP modelingsystems biologysystems pharmacology

Identifiers

PMID33841175
PMCPMC8027332

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.