Evidence map›Paper›PMID 31087533›Full record

ReviewCPT: pharmacometrics & systems pharmacology2019

Quantitative Systems Pharmacology: An Exemplar Model-Building Workflow With Applications in Cardiovascular, Metabolic, and Oncology Drug Development.

Gabriel Helmlinger, Victor Sokolov, Kirill Peskov, Karen M Hallow, Yuri Kosinsky, Veronika Voronova, Lulu Chu, Tatiana Yakovleva, Ivan Azarov, Daniel Kaschek and 4 more

Abstract readReview
In one paragraph

Review in CPT: pharmacometrics & systems pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

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

  1. Pooled it
  2. Trial
  3. Review
  4. New approach methodologies (NAMs) for preclinical and translational evaluation of mRNA-lipid nanoparticle (LNP) therapeutics.Journal of controlled release : official journal of the Controlled Release Society · 2026
    Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Review
  17. A Framework for Quantitative Systems Pharmacology Model Execution.Handbook of experimental pharmacology · 2025
    Review
  18. Article
  19. Towards a comprehensive assessment of QSP models: what would it take?Journal of pharmacokinetics and pharmacodynamics · 2024
    Review
  20. Assessing the performance of QSP models: biology as the driver for validation.Journal of pharmacokinetics and pharmacodynamics · 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

14 authors.

Gabriel HelmlingerQuantitative Clinical Pharmacology, Early Clinical Development, IMED Biotech Unit, AstraZeneca Pharmaceuticals, Boston, Massachusetts, USA.
Victor SokolovM&S Decisions LLC, Moscow, Russia.
Kirill PeskovM&S Decisions LLC, Moscow, Russia.
Karen M HallowSchool of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, Georgia, USA.
Yuri KosinskyM&S Decisions LLC, Moscow, Russia.
Veronika VoronovaM&S Decisions LLC, Moscow, Russia.
Lulu ChuQuantitative Clinical Pharmacology, Early Clinical Development, IMED Biotech Unit, AstraZeneca Pharmaceuticals, Boston, Massachusetts, USA.
Tatiana YakovlevaM&S Decisions LLC, Moscow, Russia.
Ivan AzarovM&S Decisions LLC, Moscow, Russia.
Daniel KaschekIntiQuan GmbH, Basel, Switzerland.
Artem DolgunM&S Decisions LLC, Moscow, Russia.
Henning SchmidtIntiQuan GmbH, Basel, Switzerland.
David W BoultonQuantitative Clinical Pharmacology, Early Clinical Development, IMED Biotech Unit, AstraZeneca Pharmaceuticals, Gaithersburg, Maryland, USA.
Robert C PenlandQuantitative Clinical Pharmacology, Early Clinical Development, IMED Biotech Unit, AstraZeneca Pharmaceuticals, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative systems pharmacology (QSP), a mechanistically oriented form of drug and disease modeling, seeks to address a diverse set of problems in the discovery and development of therapies. These problems bring a considerable amount of variability and uncertainty inherent in the nonclinical and clinical data. Likewise, the available modeling techniques and related software tools are manifold. Appropriately, the development, qualification, application, and impact of QSP models have been similarly varied. In this review, we describe the progressive maturation of a QSP modeling workflow: a necessary step for the efficient, reproducible development and qualification of QSP models, which themselves are highly iterative and evolutive. Furthermore, we describe three applications of QSP to impact drug development; one supporting new indications for an approved antidiabetic clinical asset through mechanistic hypothesis generation, one highlighting efficacy and safety differentiation within the sodium-glucose cotransporter-2 inhibitor drug class, and one enabling rational selection of immuno-oncology drug combinations.

Indexed as

Drug DevelopmentHumansHypoglycemic AgentsPharmacology, ClinicalSodium-Glucose Transporter 2 InhibitorsSoftwareSystems BiologyWorkflowHypoglycemic AgentsSodium-Glucose Transporter 2 Inhibitors

Identifiers

PMID31087533
PMCPMC6617832

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.