Evidence map›Paper›PMID 32862303›Full record

ArticleThe AAPS journal2020

Inter-compound and Intra-compound Global Sensitivity Analysis of a Physiological Model for Pulmonary Absorption of Inhaled Compounds.

Nicola Melillo, Silvia Grandoni, Nicola Cesari, Giandomenico Brogin, Paola Puccini, Paolo Magni

Open access · hybridAbstract readEvaluation Study
In one paragraph

Article in The AAPS journal, 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
1.3field-weighted citation impact, top 17% 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, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Bayesian PBPK modeling using R/Stan/Torsten and Julia/SciML/Turing.Jl.CPT: pharmacometrics & systems pharmacology · 2023
    Article
  4. Review
  5. Article
  6. 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

6 authors at 2 institutions in 1 country.

Nicola MelilloLaboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Via Ferrata 5, I-27100, Pavia, Italy.
Silvia GrandoniLaboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Via Ferrata 5, I-27100, Pavia, Italy.
Nicola CesariPharmacokinetics, Biochemistry and Metabolism Department, Chiesi Farmaceutici S.p.A., Parma, Italy.
Giandomenico BroginPharmacokinetics, Biochemistry and Metabolism Department, Chiesi Farmaceutici S.p.A., Parma, Italy.
Paola PucciniPharmacokinetics, Biochemistry and Metabolism Department, Chiesi Farmaceutici S.p.A., Parma, Italy.
Paolo MagniLaboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Via Ferrata 5, I-27100, Pavia, Italy. paolo.magni@unipv.it.ORCID 0000-0002-8931-4676
Chiesi (Italy) · ITUniversity of Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, global sensitivity analysis (GSA) has gained interest in physiologically based pharmacokinetics (PBPK) modelling and simulation from pharmaceutical industry, regulatory authorities, and academia. With the case study of an in-house PBPK model for inhaled compounds in rats, the aim of this work is to show how GSA can contribute in PBPK model development and daily use. We identified two types of GSA that differ in the aims and, thus, in the parameter variability: inter-compound and intra-compound GSA. The inter-compound GSA aims to understand which are the parameters that mostly influence the variability of the metrics of interest in the whole space of the drugs' properties, and thus, it is useful during the model development. On the other hand, the intra-compound GSA aims to highlight how much the uncertainty associated with the parameters of a given drug impacts the uncertainty in the model prediction and so, it is useful during routine PBPK use. In this work, inter-compound GSA highlighted that dissolution- and formulation-related parameters were mostly important for the prediction of the fraction absorbed, while the permeability is the most important parameter for lung AUC and MRT. Intra-compound GSA highlighted that, for all the considered compounds, the permeability was one of the most important parameters for lung AUC, MRT and plasma MRT, while the extraction ratio and the dose for the plasma AUC. GSA is a crucial instrument for the quality assessment of model-based inference; for this reason, we suggest its use during both PBPK model development and use.

Indexed as

Models, TheoreticalRespiratory Tract AbsorptionAdministration, InhalationAnimalsRatsglobal sensitivity analysisinter-compoundintra-compoundmodel assessmentmodel buildingPBPKpulmonary absorption model

Identifiers

PMID32862303
PMCPMC7456635
OpenAlexW3082872974

What OpenQuestion holds

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LicenceCC BY
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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.