Evidence map›Paper›PMID 33719204›Full record

ReviewCPT: pharmacometrics & systems pharmacology2021

Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies.

Peter Bloomingdale, Tatiana Karelina, Murat Cirit, Sarah F Muldoon, Justin Baker, William J McCarty, Hugo Geerts, Sreeraj Macha

Abstract readReview
In one paragraph

Review in CPT: pharmacometrics & systems pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Hallmarks of neurodegenerative disease: A systems pharmacology perspective.CPT: pharmacometrics & systems pharmacology · 2022
    Review
  7. Review
  8. Article
  9. 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

8 authors.

Peter BloomingdaleQuantitative Pharmacology and Pharmacometrics, Merck & Co. Inc, Kenilworth, New Jersey, USA.
Tatiana KarelinaInSysBio, Moscow, Russia.
Murat CiritJavelin Biotech, Inc, Woburn, Massachusetts, USA.
Sarah F MuldoonMathematics Department, CDSE Program, Neuroscience Program, University at Buffalo, SUNY, Buffalo, New York, USA.
Justin BakerHarvard Medical School, Boston, Massachusetts, USA.
William J McCartySkyhawk Therapeutics, Waltham, Massachusetts, USA.
Hugo GeertsCertara, QSP, Berwyn, Pennsylvania, USA.
Sreeraj MachaQuantitative Pharmacology, Sanofi, Bridgewater, New Jersey, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development and application of quantitative systems pharmacology models in neuroscience have been modest relative to other fields, such as oncology and immunology, which may reflect the complexity of the brain. Technological and methodological advancements have enhanced the quantitative understanding of brain physiology and pathophysiology and the effects of pharmacological interventions. To maximize the knowledge gained from these novel data types, pharmacometrics modelers may need to expand their toolbox to include additional mathematical and statistical frameworks. A session was held at the 10th annual American Conference on Pharmacometrics (ACoP10) to highlight several recent advancements in quantitative and systems neuroscience. In this mini-review, we provide a brief overview of technological and methodological advancements in the neuroscience therapeutic area that were discussed during the session and how these can be leveraged with quantitative systems pharmacology modeling to enhance our understanding of neurological diseases. Microphysiological systems using human induced pluripotent stem cells (IPSCs), digital biomarkers, and large-scale imaging offer more clinically relevant experimental datasets, enhanced granularity, and a plethora of data to potentially improve the preclinical-to-clinical translation of therapeutics. Network neuroscience methodologies combined with quantitative systems models of neurodegenerative disease could help bridge the gap between cellular and molecular alterations and clinical end points through the integration of information on neural connectomics. Additional topics, such as the neuroimmune system, microbiome, single-cell transcriptomic technologies, and digital device biomarkers, are discussed in brief.

Indexed as

Drug DiscoveryModels, BiologicalNetwork PharmacologyBrainCongresses as TopicHumansNeurodegenerative Diseases

Identifiers

PMID33719204
PMCPMC8129713

What OpenQuestion holds

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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.