Evidence map›Paper›PMID 24578187›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2014

Preclinical PK/PD modeling and human efficacious dose projection for a glucokinase activator in the treatment of diabetes.

Michael G Zager, Kirk Kozminski, Bernadette Pascual, Kathleen M Ogilvie, Shaoxian Sun

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In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 2 institutions in 3 countries.

Michael G ZagerPharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, 10646 Science Center Drive, San Diego, CA, USA, mgzager@gmail.com.
Kirk Kozminski
Bernadette Pascual
Kathleen M Ogilvie
Shaoxian Sun
Pfizer (United States) · USJohnson & Johnson (Sweden) · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human Hexokinase IV, or glucokinase (GK), is a regulator of glucose concentrations in the body. It plays a key role in pancreatic insulin secretion as well as glucose biotransformation in the liver, making it a potentially viable target for treatment of Type 2 diabetes. Allosteric activators of GK have been shown to decrease blood glucose concentrations in both animals and humans. Here, the development of a mathematical model is presented that describes glucose modulation in an ob/ob mouse model via administration of a potent GK activator, with the goal of projecting a human efficacious dose and plasma exposure. The model accounts for the allosteric interaction between GK, the activator, and glucose using a modified Hill function. Based on model simulations using data from the ob/ob mouse and in vitro studies, human projections of glucose response to the GK activator are presented, along with dose and regimen predictions to maintain clinically significant decreases in blood glucose in a Type 2 diabetic patient. This effort serves as a basis to build a detailed mechanistic understanding of GK and its role as a therapeutic target for Type 2 diabetes, and it highlights the benefits of using such an approach in a drug discovery setting.

Indexed as

Models, BiologicalAnimalsAzetidinesBenzofuransBlood GlucoseDiabetes Mellitus, Type 2Enzyme ActivatorsGlucokinaseHumansHypoglycemic AgentsMaleMiceMice, ObeseAzetidinesBenzofuransBlood GlucoseEnzyme ActivatorsGlucokinaseHypoglycemic AgentsPF-04279405

Identifiers

PMID24578187
OpenAlexW2018073268

What OpenQuestion holds

Textmetadata
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.