Evidence map›Paper›PMID 30905037›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2019

Accounting for inter-correlation between enzyme abundance: a simulation study to assess implications on global sensitivity analysis within physiologically-based pharmacokinetics.

Nicola Melillo, Adam S Darwich, Paolo Magni, Amin Rostami-Hodjegan

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2019. 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
2.0field-weighted citation impact, top 15% 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, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Role of Glucuronidation Pathway in Quetiapine Metabolism: AnSaudi journal of medicine & medical sciences
    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

4 authors at 2 institutions in 2 countries.

Nicola MelilloLaboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Via Ferrata 5, Pavia, 27100, Italy. nicola.melillo01@universitadipavia.it.ORCID http://orcid.org/0000-0002-5229-5416
Adam S DarwichCentre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, The University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
Paolo MagniLaboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Via Ferrata 5, Pavia, 27100, Italy.
Amin Rostami-HodjeganCentre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, The University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
University of Manchester · GBUniversity of Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physiologically based pharmacokinetic (PBPK) models often include several sets of correlated parameters, such as organ volumes and blood flows. Because of recent advances in proteomics, it has been demonstrated that correlations are also present between abundances of drug-metabolising enzymes in the liver. As the focus of population PBPK has shifted the emphasis from the average individual to theoretically conceivable extremes, reliable estimation of the extreme cases has become paramount. We performed a simulation study to assess the impact of the correlation between the abundances of two enzymes on the pharmacokinetics of drugs that are substrate of both, under assumptions of presence or lack of such correlations. We considered three semi-physiological models representing the cases of: (1) intravenously administered drugs metabolised by two enzymes expressed in the liver; (2) orally administered drugs metabolised by CYP3A4 expressed in the liver and gut wall; (3) intravenously administered drugs that are substrates of CYP3A4 and OATP1B1 in the liver. Finally, the impact of considering or ignoring correlation between enzymatic abundances on global sensitivity analysis (GSA) was investigated using variance based GSA on a reduced PBPK model for repaglinide, substrate of CYP3A4 and CYP2C8. Implementing such correlations can increase the confidence interval for population pharmacokinetic parameters (e.g., AUC, bioavailability) and impact the GSA results. Ignoring these correlations could lead to the generation of implausible parameters combinations and to an incorrect estimation of pharmacokinetic related parameters. Thus, known correlations should always be considered in building population PBPK models.

Indexed as

Biological AvailabilityCarbamatesComputer SimulationCytochrome P-450 CYP2C8Cytochrome P-450 CYP3AHumansInactivation, MetabolicLiverLiver-Specific Organic Anion Transporter 1Models, BiologicalPharmaceutical PreparationsPharmacokineticsPiperidinesCarbamatesCytochrome P-450 CYP2C8Cytochrome P-450 CYP3ALiver-Specific Organic Anion Transporter 1Pharmaceutical PreparationsPiperidinesrepaglinideCorrelationEnzymesGlobal sensitivity analysisPhysiologically based pharmacokineticsSimulation

Identifiers

PMID30905037
OpenAlexW2942152025

What OpenQuestion holds

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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.