Evidence map›Paper›PMID 30417600›Full record

ArticleCPT: pharmacometrics & systems pharmacology2019

A Survey of Software Tool Utilization and Capabilities for Quantitative Systems Pharmacology: What We Have and What We Need.

Sergey Ermakov, Brian J Schmidt, Cynthia J Musante, Craig J Thalhauser

Open access · goldAbstract read
In one paragraph

Article 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 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 10% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Towards a comprehensive assessment of QSP models: what would it take?Journal of pharmacokinetics and pharmacodynamics · 2024
    Review
  6. Current practices for QSP model assessment: an IQ consortium survey.Journal of pharmacokinetics and pharmacodynamics · 2024
    Article
  7. Making PBPK models more reproducible in practice.Briefings in bioinformatics · 2024
    Article
  8. In Silico Clinical Trials: Is It Possible?Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  9. Article
  10. Article
  11. Perspectives on training quantitative systems pharmacologists.CPT: pharmacometrics & systems pharmacology · 2022
    Article
  12. Evaluation framework for systems models.CPT: pharmacometrics & systems pharmacology · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Pharmacometrics and/or Systems Pharmacology.CPT: pharmacometrics & systems pharmacology · 2019
    Article
  18. Quantitative Systems Pharmacology: A Regulatory Perspective on Translation.CPT: pharmacometrics & systems pharmacology · 2019
    Article
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

4 authors at 3 institutions in 1 country.

Sergey ErmakovAmgen Inc., South San Francisco, California, USA.
Brian J SchmidtBristol-Myers Squibb, Princeton, New Jersey, USA.
Cynthia J MusantePfizer Inc., Cambridge, Massachusetts, USA.
Craig J ThalhauserBristol-Myers Squibb, Princeton, New Jersey, USA.
Bristol-Myers Squibb (United States) · USAmgen (United States) · USPfizer (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative systems pharmacology (QSP) is a rapidly emerging discipline with application across a spectrum of challenges facing the pharmaceutical industry, including mechanistically informed prioritization of target pathways and combinations in discovery, target population, and dose expansion decisions early in clinical development, and analyses for regulatory authorities late in clinical development. QSP's development has influences from physiologic modeling, systems biology, physiologically-based pharmacokinetic modeling, and pharmacometrics. Given a varied scientific heritage, a variety of tools to accomplish the demands of model development, application, and model-based analysis of available data have been developed. We report the outcome from a community survey and resulting analysis of how modelers view the impact and growth of QSP, how they utilize existing tools, and capabilities they need improved to further accelerate their impact on drug development. These results serve as a benchmark and roadmap for advancements to the QSP tool set.

Indexed as

BenchmarkingDrug DesignDrug DiscoveryHumansInternetSoftwareSurveys and QuestionnairesSystems Biology

Identifiers

PMID30417600
PMCPMC6389347
OpenAlexW2901130774

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.