Evidence map›Paper›PMID 39084881›Full record

ArticleDrug metabolism and disposition: the biological fate of chemicals2024

Predicting Clearance with Simple and Permeability-Limited Physiologically Based Pharmacokinetic Frameworks: Comparison of Well-Stirred, Dispersion, and Parallel-Tube Liver Models.

Swati Nagar, Rachel Parise, Ken Korzekwa

Abstract readComparative Study
In one paragraph

Article in Drug metabolism and disposition: the biological fate of chemicals, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Swati NagarDepartment of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania korzekwa@temple.edu swati.nagar@temple.edu.ORCID 0000-0003-2667-7063
Rachel PariseDepartment of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania.
Ken KorzekwaDepartment of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania korzekwa@temple.edu swati.nagar@temple.edu.

Funding

Predicting Intracellular Drug Concentrations In The Presence Of TransportersR01GM104178 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI Kenneth Ray Korzekwa, Swati Nagar · 2013 to 2026
$4.0M
Improving prediction of drug interactions mediated by time-dependent inhibitorsR01GM114369 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI KORZEKWA, KENNETH RAY, NAGAR, SWATI · 2016 to 2023
$3.2M
NIGMS NIH HHS R01 GM104178NIGMS NIH HHS R01 GM114369
6 · The paper itself

Abstract

One-compartment (1C) and permeability-limited models were used to evaluate the ability of microsomal and hepatocyte intrinsic clearances to predict hepatic clearance. Well-stirred (WSM), parallel-tube (PTM), and dispersion (DM) models were evaluated within the liver as well as within whole-body physiologically based pharmacokinetic frameworks. It was shown that a linear combination of well-stirred and parallel-tube average liver blood concentrations accurately approximates dispersion model blood concentrations. Using a flow/permeability-limited model, a large systematic error was observed for acids and no systematic error for bases. A scaling factor that reduced interstitial fluid (ISF) plasma protein binding could greatly decrease the absolute average fold error (AAFE) for acids. Using a 1C model, a scalar to reduce plasma protein binding decreased the microsomal clearance AAFE for both acids and bases. With a permeability-limited model, only acids required this scalar. The mechanism of the apparent increased cytosolic concentrations for acids remains unknown. We also show that for hepatocyte intrinsic clearance in vitro-in vivo correlations (IVIVCs), a 1C model is mechanistically appropriate since hepatocyte clearance should represent the net clearance from ISF to elimination. A relationship was derived that uses microsomal and hepatocyte intrinsic clearance to solve for an active hepatic uptake clearance, but the results were inconclusive. Finally, the PTM model generally performed better than the WSM or DM models, with no clear advantage between microsomes and hepatocytes. SIGNIFICANCE STATEMENT: Prediction of drug clearance from microsomes or hepatocytes remains challenging. Various liver models (e.g., well-stirred, parallel-tube, and dispersion) have been mathematically incorporated into liver as well as whole-body physiologically based pharmacokinetic frameworks. Although the resulting models allow incorporation of pH partitioning, permeability, and active uptake for prediction of drug clearance, including these processes did not improve clearance predictions for both microsomes and hepatocytes.

Indexed as

HepatocytesLiverMetabolic Clearance RateMicrosomes, LiverModels, BiologicalPermeabilityAnimalsHumansPharmaceutical PreparationsPharmacokineticsProtein BindingPharmaceutical Preparations

Identifiers

PMID39084881
PMCPMC11409860

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.