Evidence map›Paper›PMID 33076517›Full record

ArticlePharmaceutics2020

Physiologically-Based Pharmacokinetic/Pharmacodynamic Model of MBQ-167 to Predict Tumor Growth Inhibition in Mice.

Javier Reig-López, María Del Mar Maldonado, Matilde Merino-Sanjuan, Ailed M Cruz-Collazo, Jean F Ruiz-Calderón, Victor Mangas-Sanjuán, Suranganie Dharmawardhane, Jorge Duconge

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Identification of nanoparticle infiltration in human breast milk: Chemical profiles and trajectory pathways.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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 at 2 institutions in 2 countries.

Javier Reig-LópezDepartment of Pharmacy and Pharmaceutical Technology and Parasitology, Faculty of Pharmacy, University of Valencia, 46100 Burjassot, Valencia, Spain.ORCID 0000-0002-6007-3055
María Del Mar MaldonadoDepartment of Biochemistry, School of Medicine, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA.
Matilde Merino-SanjuanDepartment of Pharmacy and Pharmaceutical Technology and Parasitology, Faculty of Pharmacy, University of Valencia, 46100 Burjassot, Valencia, Spain.ORCID 0000-0003-4956-0247
Ailed M Cruz-CollazoDepartment of Biochemistry, School of Medicine, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA.
Jean F Ruiz-CalderónDepartment of Biochemistry, School of Medicine, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA.
Victor Mangas-SanjuánDepartment of Pharmacy and Pharmaceutical Technology and Parasitology, Faculty of Pharmacy, University of Valencia, 46100 Burjassot, Valencia, Spain.ORCID 0000-0002-3388-5023
Suranganie DharmawardhaneDepartment of Biochemistry, School of Medicine, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA.ORCID 0000-0001-7127-1180
Jorge DucongeSchool of Pharmacy, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA.ORCID 0000-0002-5955-3449
University of Puerto Rico, Medical Sciences Campus · PRUniversitat de València · ES

Funding

Upstream Regulation and Downstream effectors of c-MYC in Ovarian CancerU54MD007600 · NIMHD · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI Carmen M Velez Vega · 2017 to 2026
$35.8M
RISE Option III: MBRS RISE at the UPR Medical Sciences CampusR25GM061838 · NIGMS · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI CADILLA, CARMEN LYDIA · 2000 to 2021
$25.5M
Targeting breast cancer progressionSC3GM084824 · NIGMS · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI DHARMAWARDHANE, SURANGANIE · 2008 to 2021
$1.6M
National Institute of General Medical Sciences at National Institutes of Health #SC3 GM084824National Institute on Minority Health and Health Disparities at National Institutes of Health #R25 GM06183National Institute on Minority Health and Health Disparities at the National Institutes of Health #U54 MD007600-31NIGMS NIH HHS R25 GM061838NIGMS NIH HHS SC3 GM084824Susan G Komen for the Cure #OG170023
6 · The paper itself

Abstract

MBQ-167 is a dual inhibitor of the Rho GTPases Rac and Cdc42 that has shown promising results as an anti-cancer therapeutic at the preclinical stage. This drug has been tested in vitro and in vivo in metastatic breast cancer mouse models. The aim of this study is to develop a physiologically based pharmacokinetic/pharmacodynamic (PBPK-PD) model of MBQ-167 to predict tumor growth inhibition following intraperitoneal (IP) administration in mice bearing Triple Negative and HER2+ mammary tumors. PBPK and Simeoni tumor growth inhibition (TGI) models were developed using the Simcyp V19 Animal Simulator. Our developed PBPK framework adequately describes the time course of MBQ-167 in each of the mouse tissues (e.g., lungs, heart, liver, kidneys, spleen, plasma) and tumor, since the predicted results were consistent with the experimental data. The developed PBPK-PD model successfully predicts tumor shrinkage in HER2+ and triple-negative breast tumors after the intraperitoneal administration of 1 and 10 mg/kg body weight (BW) dose level of MBQ-167 three times a week. The findings from this study suggest that MBQ-167 has a higher net effect and potency inhibiting Triple Negative mammary tumor growth compared to HER2+ and that liver metabolism is the major route of elimination of this drug.

Indexed as

breast cancerMBQ-167physiologically based pharmacokinetic modelingRac inhibitor

Identifiers

PMID33076517
PMCPMC7602742
OpenAlexW3093283176

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.