Evidence map›Paper›PMID 27161439›Full record

ArticleArchives of toxicology2017

Model-based contextualization of in vitro toxicity data quantitatively predicts in vivo drug response in patients.

Christoph Thiel, Henrik Cordes, Isabel Conde, José Vicente Castell, Lars Mathias Blank, Lars Kuepfer

Open access · hybridAbstract readCase Reports
In one paragraph

Article in Archives of toxicology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.1field-weighted citation impact, top 6% 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

12 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
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  3. Quantitative systems pharmacology of the eye: Tools and data for ocular QSP.CPT: pharmacometrics & systems pharmacology · 2023
    Review
  4. Article
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  12. Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model.CPT: pharmacometrics & systems pharmacology · 2016
    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

6 authors at 2 institutions in 2 countries.

Christoph ThieliAMB - Institute of Applied Microbiology, ABBt - Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074, Aachen, Germany.
Henrik CordesiAMB - Institute of Applied Microbiology, ABBt - Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074, Aachen, Germany.
Isabel CondeUnidad de Hepatología Experimental y Trasplante Hepático, Instituto de Investigación Sanitaria La Fe, 46026, Valencia, Spain.
José Vicente CastellUnidad de Hepatología Experimental y Trasplante Hepático, Instituto de Investigación Sanitaria La Fe, 46026, Valencia, Spain.
Lars Mathias BlankiAMB - Institute of Applied Microbiology, ABBt - Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074, Aachen, Germany.
Lars KuepferiAMB - Institute of Applied Microbiology, ABBt - Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074, Aachen, Germany. lars.kuepfer@rwth-aachen.de.
RWTH Aachen University · DEInstituto de Investigación Sanitaria La Fe · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding central mechanisms underlying drug-induced toxicity plays a crucial role in drug development and drug safety. However, a translation of cellular in vitro findings to an actual in vivo context remains challenging. Here, physiologically based pharmacokinetic (PBPK) modeling was used for in vivo contextualization of in vitro toxicity data (PICD) to quantitatively predict in vivo drug response over time by integrating multiple levels of biological organization. Explicitly, in vitro toxicity data at the cellular level were integrated into whole-body PBPK models at the organism level by coupling in vitro drug exposure with in vivo drug concentration-time profiles simulated in the extracellular environment within the organ. PICD was exemplarily applied on the hepatotoxicant azathioprine to quantitatively predict in vivo drug response of perturbed biological pathways and cellular processes in rats and humans. The predictive accuracy of PICD was assessed by comparing in vivo drug response predicted for rats with observed in vivo measurements. To demonstrate clinical applicability of PICD, in vivo drug responses of a critical toxicity-related pathway were predicted for eight patients following acute azathioprine overdoses. Moreover, acute liver failure after multiple dosing of azathioprine was investigated in a patient case study by use of own clinical data. Simulated pharmacokinetic profiles were therefore related to in vivo drug response predicted for genes associated with observed clinical symptoms and to clinical biomarkers measured in vivo. PICD provides a generic platform to investigate drug-induced toxicity at a patient level and thus may facilitate individualized risk assessment during drug development.

Indexed as

Drug-Related Side Effects and Adverse ReactionsModels, TheoreticalPharmacokineticsAdultAnimalsAzathioprineChemical and Drug Induced Liver InjuryDrug OverdoseHumansMaleRatsReproducibility of ResultsToxicity TestsToxicity Tests, AcuteAzathioprineClinical translationDrug-induced liver injuryMultiscale modelingPBPKPharmacokinetic modelingQuantitative systems pharmacologyTranscriptomics

Identifiers

PMID27161439
PMCPMC5306109
OpenAlexW2346104824

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.