Evidence map›Paper›PMID 33958900›Full record

ArticleClinical pharmacology : advances and applications2021

Population Pharmacokinetics of CC-122.

Yiming Cheng, Jian Chen, Michael Pourdehnad, Simon Zhou, Yan Li

Open access · goldAbstract read
In one paragraph

Article in Clinical pharmacology : advances and applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 38% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 1 institution in 1 country.

Yiming ChengClinical Pharmacology & Pharmacometrics, Bristol Myers Squibb, Summit, NJ, USA.
Jian ChenNon-Clinical Research & Development, Bristol Myers Squibb, Summit, NJ, USA.
Michael PourdehnadEarly Clinical Development, Bristol Myers Squibb, San Francisco, CA, USA.ORCID 0000-0001-8701-930X
Simon ZhouClinical Pharmacology & Pharmacometrics, Bristol Myers Squibb, Summit, NJ, USA.
Yan LiClinical Pharmacology & Pharmacometrics, Bristol Myers Squibb, Summit, NJ, USA.
Bristol-Myers Squibb (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCC-122 is a cereblon-modulating agent that exerts direct cell-autonomous activity against malignant B cells and immunomodulatory effects. Herein, a population pharmacokinetic (popPK) model of CC-122 was developed and the influence of demographic and disease-related covariates on population pharmacokinetic parameters was assessed based on data from three clinical studies of CC-122 (dose range, 0.5-15 mg) in healthy subjects and cancer patients.

methodsNonlinear mixed effects modeling was employed in developing a population pharmacokinetic model of CC-122 based on 298 patients from 3 clinical studies.

resultsThe PK of CC-122 was adequately described with a two-compartment model with first-order absorption and elimination. Tumor types were found to be significantly correlated with apparent clearance (CL/F) and apparent volume of distribution of the central compartment. Creatinine clearance was identified as a statistically significant covariate of CL/F. Sex and body weight were statistically but not clinically relevant on V2/F.

conclusionIn conclusion, the two-compartment model built can be used to adequately describe the time course of the population pharmacokinetics of CC-122 and should serve as the basis for dose adjustment decision-making of CC-122.

Indexed as

CC-122population pharmacokineticsrenal impairment

Identifiers

PMID33958900
PMCPMC8093142
OpenAlexW3157905247

What OpenQuestion holds

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LicenceCC BY-NC
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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.