ArticleCPT: pharmacometrics & systems pharmacology2015
Integration of Physiologically-Based Pharmacokinetic Modeling into Early Clinical Development: An Investigation of the Pharmacokinetic Nonlinearity.
Article in CPT: pharmacometrics & systems pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BMS-911543, a promising anticancer agent, exhibited time-dependent and dose-dependent nonlinear pharmacokinetics (PKs) in its first-in-human (FIH) study. Initial physiologically based pharmacokinetic (PBPK) modeling efforts using CYP1A2-mediated clearance kinetics were unsuccessful; however, further model analysis revealed that CYP1A2 time-dependent inhibition (TDI) and perhaps other factors could be keys to the nonlinearity. Subsequent experiments in human liver microsomes showed that the compound was a time-dependent inhibitor of CYP1A2 and were used to determine the enzyme inactivation parameter values. In addition, a rat tissue distribution study was conducted and human plasma samples were profiled to support the refinement of the PBPK model. It was concluded that the interplay between four BMS-911543 properties, namely, low solubility, saturation of the metabolizing enzyme CYP1A2, CYP1A2 TDI, and CYP1A2 induction likely resulted in the time-dependent and dose-dependent nonlinear PKs. The methodology of PBPK model-guided unmasking of compound properties can serve as a general practice for mechanistic understanding of a new compound's disposition.
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Registered trials
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