Evidence map›Paper›PMID 34196005›Full record

ArticleJournal of clinical pharmacology2021

Physiologically Based Pharmacokinetic Modeling for Selumetinib to Evaluate Drug-Drug Interactions and Pediatric Dose Regimens.

Sarit Cohen-Rabbie, Li Zhou, Karthick Vishwanathan, Martin Wild, Sherrie Xu, Tomoko Freshwater, Lokesh Jain, Stein Schalkwijk, Helen Tomkinson, Diansong Zhou

Abstract read
In one paragraph

Article in Journal of clinical pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
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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

10 authors.

Sarit Cohen-RabbieClinical Pharmacology & Quantitative Pharmacology, Clinical Pharmacology and Safety Science, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Li ZhouClinical Pharmacology & Quantitative Pharmacology, Clinical Pharmacology and Safety Science, BioPharmaceuticals R&D, AstraZeneca, Boston, Massachusetts, USA.
Karthick VishwanathanClinical Pharmacology & Quantitative Pharmacology, Clinical Pharmacology and Safety Science, BioPharmaceuticals R&D, AstraZeneca, Boston, Massachusetts, USA.ORCID 0000-0002-6555-8131
Martin WildDMPK, Oncology AstraZeneca, Cambridge, UK.
Sherrie XuPharmacokinetics, Pharmacodynamics and Drug Metabolism (PPDM), Merck & Co., Inc., Kenilworth, New Jersey, USA.
Tomoko FreshwaterQuantitative Pharmacology & Pharmacometrics (QP2) Pharmacokinetics, Pharmacodynamics and Drug Metabolism (PPDM), Merck & Co., Inc., Kenilworth, New Jersey, USA.
Lokesh JainQuantitative Pharmacology & Pharmacometrics (QP2) Pharmacokinetics, Pharmacodynamics and Drug Metabolism (PPDM), Merck & Co., Inc., Kenilworth, New Jersey, USA.
Stein SchalkwijkClinical Pharmacology & Quantitative Pharmacology, Clinical Pharmacology and Safety Science, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Helen TomkinsonClinical Pharmacology & Quantitative Pharmacology, Clinical Pharmacology and Safety Science, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Diansong ZhouClinical Pharmacology & Quantitative Pharmacology, Clinical Pharmacology and Safety Science, BioPharmaceuticals R&D, AstraZeneca, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Selumetinib (ARRY-142886), an oral, potent and highly selective allosteric mitogen-activated protein kinase kinase 1/2 inhibitor, is approved by the US Food and Drug Administration for the treatment of pediatric patients aged ≥2 years with neurofibromatosis type 1 with symptomatic, inoperable plexiform neurofibromas. A physiologically based pharmacokinetic (PBPK) model was constructed to predict plasma concentration-time profiles of selumetinib, and to evaluate the impact of coadministering moderate cytochrome P450 (CYP) 3A4/2C19 inhibitors/inducers. The model was also used to extrapolate pharmacokinetic exposures from older children with different body surface area to guide dosing in younger children. This model was built based on physiochemical data and clinical in vivo drug-drug interaction (DDI) studies with itraconazole and fluconazole, and verified against data from an in vivo rifampicin DDI study and an absolute bioavailability study. The pediatric model was updated by changing system-specific input parameters using the Simcyp pediatric module. The model captured the observed selumetinib pharmacokinetic profiles and the interactions with CYP inhibitors/inducers. The predictions from the PBPK model showed a DDI effect of 30% to 40% increase or decrease in selumetinib exposure when coadministered with moderate CYP inhibitors or inducers, respectively, which was used to inform dose management and adjustments. The pediatric PBPK model was applied to simulate exposures in specific body surface area brackets that matched those achieved with a 25 mg/m

Indexed as

AdolescentAge FactorsArea Under CurveBenzimidazolesBody Surface AreaChildChild, PreschoolCytochrome P-450 Enzyme InducersCytochrome P-450 Enzyme InhibitorsDrug Dosage CalculationsDrug InteractionsFluconazoleHumansItraconazoleMetabolic Clearance RateMitogen-Activated Protein Kinase KinasesAZD 6244BenzimidazolesCytochrome P-450 Enzyme InducersCytochrome P-450 Enzyme InhibitorsFluconazoleItraconazoleMitogen-Activated Protein Kinase KinasesProtein Kinase InhibitorsRifampindrug-drug interactionsMEK inhibitorneurofibromatosis type 1PBPKpediatricprediction and simulationselumetinib

Identifiers

PMID34196005
PMCPMC9290801

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Registered trials

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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.