Evidence map›Paper›PMID 32575566›Full record

ArticlePharmaceutics2020

A Population Pharmacokinetic and Pharmacodynamic Model of CKD-519.

Choon Ok Kim, Sangil Jeon, Seunghoon Han, Min Soo Park, Dong-Seok Yim

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 94% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 1 country.

Choon Ok KimDepartment of Clinical Pharmacology, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0002-2319-1108
Sangil JeonQfitter Inc., Seoul 06578, Korea.
Seunghoon HanQfitter Inc., Seoul 06578, Korea.ORCID 0000-0002-9976-5120
Min Soo ParkDepartment of Clinical Pharmacology, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Korea.
Dong-Seok YimQfitter Inc., Seoul 06578, Korea.ORCID 0000-0003-2754-7500
The Catholic University of Korea Seoul St. Mary's Hospital · KRYonsei University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CKD-519 is a selective and potent cholesteryl ester transfer protein (CETP) inhibitor that is being developed for dyslipidemia. Even though CKD-519 has shown potent CETP inhibition, the exposure of CKD-519 was highly varied, depending on food and dose. For highly variable exposure drugs, it is crucial to use modeling and simulation to plan proper dose selection. This study aimed to develop population pharmacokinetic (PK) and pharmacodynamics (PD) models of CKD-519 and to predict the proper dose of CKD-519 to achieve target levels for HDL-C and LDL-C using results from multiple dosing study of CKD-519 with a standard meal for two weeks in healthy subjects. The results showed that a 3-compartment with Erlang's distribution, followed by the first-order absorption, adequately described CKD-519 PK, and the bioavailability, which decreased by dose and time was incorporated into the model (NONMEM version 7.3). After the PK model development, the CETP activity and cholesterol (HDL-C and LDL-C) levels were sequentially modeled using the turnover model, including the placebo effect. According to PK-PD simulation results, 200 to 400 mg of CKD-519 showing a 40% change in HDL-C and LDL-C from baselines was recommended for proof of concept studies in patients with dyslipidemia.

Indexed as

CETP activityCETP inhibitorCKD-519HDL-Cpopulation PK-PD modeling

Identifiers

PMID32575566
PMCPMC7356970
OpenAlexW3036039687

What OpenQuestion holds

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LicenceCC BY
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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.