Evidence map›Paper›PMID 31178753›Full record

ArticleFrontiers in physiology2019

Leveraging Mathematical Modeling to Quantify Pharmacokinetic and Pharmacodynamic Pathways: Equivalent Dose Metric.

Matthew T McKenna, Jared A Weis, Vito Quaranta, Thomas E Yankeelov

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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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

4 authors at 3 institutions in 1 country.

Matthew T McKennaVanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States.
Jared A WeisDepartment of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC, United States.
Vito QuarantaDepartment of Cancer Biology, Vanderbilt University School of Medicine, Vanderbilt University, Nashville, TN, United States.
Thomas E YankeelovDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX, United States.
Vanderbilt University · USAtrium Health Wake Forest Baptist · USLivestrong Foundation · US

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007347 · NIGMS · VANDERBILT UNIVERSITY · PI WILLIAMS, CHRISTOPHER S. · 1985 to 2023
$26.3M
Quantitative Multiscale Imaging to Optimize Cancer Treatment StrategiesR01CA186193 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO, RERICHA, ERIN C · 2014 to 2019
$3.1M
Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast CancerU01CA174706 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO, YANKEELOV, THOMAS E · 2013 to 2018
$2.5M
Evaluation and Validation of Imaging Biomarkers of Tumor Response to TreatmentR01CA138599 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MCINTYRE, JAMES OLIVER · 2010 to 2015
$2.2M
Multi-Scale Biomechanical Modeling of Tumor Growth and Response in Breast CancerK25CA204599 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WEIS, JARED ANTHONY · 2016 to 2020
$747k
A Computational Model-Enhanced Approach for Tumor Localization During LumpectomyR21EB022380 · NIBIB · VANDERBILT UNIVERSITY · PI MESZOELY, INGRID M, MIGA, MICHAEL IAN · 2016 to 2017
$411k
Development and Validation of a Predictive Model of Chemotherapy in Breast CancerF30CA203220 · NCI · VANDERBILT UNIVERSITY · PI MCKENNA, MATTHEW T. · 2016 to 2019
$134k
NCI NIH HHS F30 CA203220NCI NIH HHS K25 CA204599NCI NIH HHS R01 CA138599NCI NIH HHS R01 CA186193NCI NIH HHS U01 CA174706NIBIB NIH HHS R21 EB022380NIGMS NIH HHS T32 GM007347
6 · The paper itself

Abstract

Treatment response assays are often summarized by sigmoidal functions comparing cell survival at a single timepoint to applied drug concentration. This approach has a limited biophysical basis, thereby reducing the biological insight gained from such analysis. In particular, drug pharmacokinetic and pharmacodynamic (PK/PD) properties are overlooked in developing treatment response assays, and the accompanying summary statistics conflate these processes. Here, we utilize mathematical modeling to decouple and quantify PK/PD pathways. We experimentally modulate specific pathways with small molecule inhibitors and filter the results with mechanistic mathematical models to obtain quantitative measures of those pathways. Specifically, we investigate the response of cells to time-varying doxorubicin treatments, modulating doxorubicin pharmacology with small molecules that inhibit doxorubicin efflux from cells and DNA repair pathways. We highlight the practical utility of this approach through proposal of the "equivalent dose metric." This metric, derived from a mechanistic PK/PD model, provides a biophysically-based measure of drug effect. We define equivalent dose as the functional concentration of drug that is bound to the nucleus following therapy. This metric can be used to quantify drivers of treatment response and potentially guide dosing of combination therapies. We leverage the equivalent dose metric to quantify the specific intracellular effects of these small molecule inhibitors using population-scale measurements, and to compare treatment response in cell lines differing in expression of drug efflux pumps. More generally, this approach can be leveraged to quantify the effects of various pharmaceutical and biologic perturbations on treatment response.

Indexed as

breast cancerdoxorubicinmathematical modelingpharmacodynamicspharmacokinetic modelingtreatment response

Identifiers

PMID31178753
PMCPMC6538812
OpenAlexW2946017501

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.