Evidence map›Paper›PMID 36376611›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2023

Pharmacometric model of agalsidase-migalastat interaction in human: a novel mechanistic model of drug-drug interaction between a therapeutic protein and a small molecule.

Thanh Bach, Nan Wu, Guohua An

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In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Thanh Bach *Division of Pharmaceutics and Translational Therapeutics, College of Pharmacy, University of Iowa, Iowa City, IA, USA.
Nan Wu *Division of Pharmaceutics and Translational Therapeutics, College of Pharmacy, University of Iowa, Iowa City, IA, USA.
Guohua AnDivision of Pharmaceutics and Translational Therapeutics, College of Pharmacy, University of Iowa, Iowa City, IA, USA. guohua-an@uiowa.edu.
University of Iowa · USTranslational Therapeutics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, a new mechanism of drug-drug interaction (DDI) was reported between agalsidase, a therapeutic protein, and migalastat, a small molecule, both of which are treatment options of Fabry disease. Migalastat is a pharmacological chaperone that stabilizes the native form of both endogenous and exogenous agalsidase. In Fabry patients co-administrated with agalsidase and migalastat, the increase in active agalsidase exposure is considered a pharmacokinetic effect of agalsidase infusion but a pharmacodynamic effect of migalastat administration, which makes this new DDI mechanism even more interesting. To quantitatively characterize the interaction between agalsidase and migalastat in human, a pharmacometric DDI model was developed using literature reported concentration-time data. The final model includes three components: a 1-compartment linear model component for migalastat; a 2-compartment linear model component for agalsidase; and a DDI component where the agalsidase-migalastat complex is formed via second order association constant k

Indexed as

1-Deoxynojirimycinalpha-GalactosidaseDrug InteractionsHumansMutation1-Deoxynojirimycinalpha-GalactosidasemigalastatAgalsidase–Migalastat interactionDDI modelFabry diseaseMechanistic modelNovel mechanistic DDI modelPharmacometric modeling

Identifiers

PMID36376611
OpenAlexW4309028451

What OpenQuestion holds

Textmetadata
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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.