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Record W2502973876 · doi:10.18433/j3c89j

Microdialysis-directed Intra-tumor Pharmacokinetic Modeling of Methotrexate in Mice and Humans

2016· article· en· W2502973876 on OpenAlexvenueno aff
Helal H. Alsulimani, Jong‐Han Kim, Shabnam N. Sani

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2016
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced organ toxicity mitigation
Canadian institutionsnot available
FundersWestern New England University
KeywordsPharmacokineticsMicrodialysisMethotrexateChemistryInterstitial fluidPharmacologyPathologyInternal medicineMedicineBiochemistryExtracellular

Abstract

fetched live from OpenAlex

PURPOSE: To develop a quantitative pharmacokinetic model to characterize the disposition of methotrexate (MTX) at tumor site in tumor-bearing mice and to predict MTX concentrations in the human tumor. METHODS: The plasma profiles of MTX were obtained from normal mice, while microdialysis technique was employed to characterize the time course of MTX in tumor from breast tumor-bearing mice. Disposition profiles of plasma and tumor were analyzed by a hybrid physiologically-based pharmacokinetic (hPBPK) model that incorporates physiologically-relevant parameters such as tumor blood flow and volume, while plasma concentrations were used as a forcing input into the vascular-interstitial spaces of the tumor. The plasma profiles were initially described by a biexponential decay model to obtain a forcing function that enters into the vascular-interstitial spaces in the tumor. Using a defined forcing function, the tumor free concentrations were fitted to the hPBPK model. Based on the model developed, sensitivity analysis was conducted with a perturbation of PK parameters to predict different scenarios of intratumoral MTX transport. The relevant physiological PK parameters from the mouse model were then scaled-up and utilized to simulate human tumor concentrations. RESULTS: The mouse hPBPK model adequately characterized the concentration-time profiles of MTX in both plasma and tumor and produced various transfer rate constants between plasma and tumor. Our model was also able to reasonably predict MTX concentrations in the human tumor when human physiological data were utilized. CONCLUSIONS: The hPBPK model was able to quantitatively characterize the atypical transport of MTX in the tumor, supporting the idea that microdialysis is a valuable tool to study tumor biodistribution of drugs and to predict tumor concentrations in humans based on the pre-clinical data. This information can ultimately aid in the development of anticancer drugs with improved PK profiles. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.398
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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