Evidence map›Paper›PMID 36537068›Full record

ArticleCPT: pharmacometrics & systems pharmacology2023

Interspecies and in vitro-in vivo scaling for quantitative modeling of whole-body drug pharmacokinetics in patients: Application to the anticancer drug oxaliplatin.

Simona Catozzi, Roger Hill, Xiao-Mei Li, Sandrine Dulong, Elodie Collard, Annabelle Ballesta

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Article in CPT: pharmacometrics & systems pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Simona CatozziInstitut Curie, Inserm U900, MINES ParisTech, CBIO - Centre for Computational Biology, PSL Research University, Saint-Cloud, France.ORCID 0000-0001-6132-5712
Roger HillEPSRC and MRC Centre for Doctoral Training in Mathematics for Real-World Systems, University of Warwick, Coventry, UK.
Xiao-Mei LiUPR "Chronotherapy, Cancers and Transplantation," Faculty of Medicine, Université Paris-Saclay, Villejuif, France.
Sandrine DulongInstitut Curie, Inserm U900, MINES ParisTech, CBIO - Centre for Computational Biology, PSL Research University, Saint-Cloud, France.
Elodie CollardCEA, CNRS, NIMBE, Université Paris-Saclay, Gif-sur-Yvette, France.
Annabelle BallestaInstitut Curie, Inserm U900, MINES ParisTech, CBIO - Centre for Computational Biology, PSL Research University, Saint-Cloud, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative systems pharmacology holds the promises of integrating results from laboratory animals or in vitro human systems into the design of human pharmacokinetic/pharmacodynamic (PK/PD) models allowing for precision and personalized medicine. However, reliable and general in vitro-to-in vivo extrapolation and interspecies scaling methods are still lacking. Here, we developed a translational strategy for the anticancer drug oxaliplatin. Using ex vivo PK data in the whole blood of the mouse, rat, and human, a model representing the amount of platinum (Pt) in the plasma and in the red blood cells was designed and could faithfully fit each dataset independently. A "purely physiologically-based (PB)" scaling approach solely based on preclinical data failed to reproduce human observations, which were then included in the calibration. Investigating approaches in which one parameter was set as species-specific, whereas the others were computed by PB scaling laws, we concluded that allowing the Pt binding rate to plasma proteins to be species-specific permitted to closely fit all data, and guaranteed parameter identifiability. Such a strategy presenting the drawback of including all clinical datasets, we further identified a minimal subset of human data ensuring accurate model calibration. Next, a "whole body" model of oxaliplatin human PK was inferred from the ex vivo study. Its three remaining parameters were estimated, using one third of the available patient data. Remarkably, the model achieved a good fit to the training dataset and successfully reproduced the unseen observations. Such validation endorsed the legitimacy of our scaling methodology calling for its testing with other drugs.

Indexed as

Antineoplastic AgentsAnimalsHumansMiceModels, BiologicalOxaliplatinPharmacokineticsRatsAntineoplastic AgentsOxaliplatin

Identifiers

PMID36537068
PMCPMC9931436

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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.