Evidence map›Paper›PMID 34435271›Full record

ArticleThe AAPS journal2021

Is It Time to Use Modeling of Cellular Transporter Homeostasis to Inform Drug-Drug Interaction Studies: Theoretical Considerations.

Roberto A Abbiati, M Guillaume Wientjes, Jessie L-S Au

Open access · greenAbstract read
In one paragraph

Article in The AAPS journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 53% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Review
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

3 authors at 2 institutions in 1 country.

Roberto A AbbiatiInstitute of Quantitative Systems Pharmacology, Carlsbad, California, 92008, USA.
M Guillaume WientjesInstitute of Quantitative Systems Pharmacology, Carlsbad, California, 92008, USA.
Jessie L-S AuInstitute of Quantitative Systems Pharmacology, Carlsbad, California, 92008, USA. jau@i-qsp.org.
University of Oklahoma · USOptimum Therapeutics (United States) · US

Funding

Targeting multiple signaling steps to achieve synergyR01CA163015 · NCI · OPTIMUM THERAPEUTICS, LLC · PI AU, JESSIE L.-S., WIENTJES, M GUILLAUME · 2012 to 2017
$1.9M
Capturing dynamic and inter-dependent biointerfaces in nanotechnology designsR01EB015253 · NIBIB · OPTIMUM THERAPEUTICS, LLC · PI AU, JESSIE L.-S., WIENTJES, M GUILLAUME · 2011 to 2014
$1.1M
NCI NIH HHS R01 CA163015NIBIB NIH HHS R01 EB015253
6 · The paper itself

Abstract

Mathematical modeling has been an important tool in pharmaceutical research for 50 + years and there is increased emphasis over the last decade on using modeling to improve the efficiency and effectiveness of drug development. In an earlier commentary, we applied a multiscale model linking 6 scales (whole body, tumor, vasculature, cell, spatial location, time), together with literature data on nanoparticle and tumor properties, to demonstrate the effects of nanoparticle particles on systemic disposition. The current commentary used a 4-scale model (cell membrane, intracellular organelles, spatial location, time) together with literature data on the intracellular processing of membrane receptors and transporters to demonstrate disruption of transporter homeostasis can lead to drug-drug interaction (DDI) between victim drug (VD) and perpetrator drug (PD), including changes in the area-under-concentration-time-curve of VD in cells that are considered significant by the US Food and Drug Administration (FDA). The model comprised 3 computational components: (a) intracellular transporter homeostasis, (b) pharmacokinetics of extracellular and intracellular VD/PD concentrations, and (c) pharmacodynamics of PD-induced stimulation or inhibition of an intracellular kinetic process. Model-based simulations showed that (a) among the five major endocytic processes, perturbation of transporter internalization or recycling led to the highest incidence and most extensive DDI, with minor DDI for perturbing transporter synthesis and early-to-late endosome and no DDI for perturbing transporter degradation and (b) three experimental conditions (spatial transporter distribution in cells, VD/PD co-incubation time, extracellular PD concentrations) were determinants of DDI detection. We propose modeling is a useful tool for hypothesis generation and for designing experiments to identify potential DDI; its application further aligns with the model-informed drug development paradigm advocated by FDA.

Indexed as

Drug InteractionsModels, BiologicalArea Under CurveComputer SimulationDrug DevelopmentHepatocytesHomeostasisHumansLiver-Specific Organic Anion Transporter 1Solute Carrier Organic Anion Transporter Family Member 1B3Liver-Specific Organic Anion Transporter 1SLCO1B1 protein, humanSLCO1B3 protein, humanSolute Carrier Organic Anion Transporter Family Member 1B3model-informed drug developmentmultiscale modelOATPquantitative pharmacologytransporter homeostasis

Identifiers

PMID34435271
PMCPMC11048728
OpenAlexW3195148533

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.