Evidence map›Paper›PMID 30309203›Full record

ArticleGenomics & informatics2018

Utility of Integrated Analysis of Pharmacogenomics and Pharmacometabolomics in Early Phase Clinical Trial: A Case Study of a New Molecular Entity.

Jaeseong Oh, Sojeong Yi, Namyi Gu, Dongseong Shin, Kyung-Sang Yu, Seo Hyun Yoon, Joo-Youn Cho, In-Jin Jang

Open access · diamondAbstract read
In one paragraph

Article in Genomics & informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
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

8 authors at 4 institutions in 2 countries.

Jaeseong OhDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080, Korea.
Sojeong YiOffice of Clinical Pharmacology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 10903, USA.
Namyi GuDepartment of Clinical Pharmacology and Therapeutics, Clinical Trial Center, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang 10326, Korea.
Dongseong ShinClinical Trials Center, Gachon University Gil Medical Center, Incheon 21565, Korea.
Kyung-Sang YuDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080, Korea.
Seo Hyun YoonDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080, Korea.
Joo-Youn ChoDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080, Korea.
In-Jin JangDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080, Korea.
Seoul National University Hospital · KRDongguk University Ilsan Hospital · KRGachon University Gil Medical Center · KRUnited States Food and Drug Administration · US

Funding

Korea Health Industry Development InstituteMinistry of Health and Welfare HI15C1543
6 · The paper itself

Abstract

In this report, we present a case study of how pharmacogenomics and pharmacometabolomics can be useful to characterize safety and pharmacokinetic profiles in early phase new drug development clinical trials. During conducting a first-in-human trial for a new molecular entity, we were able to determine the mechanism of dichotomized variability in plasma drug concentrations, which appeared closely related to adverse drug reactions (ADRs) through integrated omics analysis. The pharmacogenomics screening was performed from whole blood samples using the Affymetrix DMET (Drug-Metabolizing Enzymes and Transporters) Plus microarray, and confirmation of genetic variants was performed using real-time polymerase chain reaction. Metabolomics profiling was performed from plasma samples using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. A GSTM1 null polymorphism was identified in pharmacogenomics test and the drug concentrations was higher in GSTM1 null subjects than GSTM1 functional subjects. The apparent drug clearance was 13-fold lower in GSTM1 null subjects than GSTM1 functional subjects (p < 0.001). By metabolomics analysis, we identified that the study drug was metabolized by cysteinylglycine conjugation in GSTM functional subjects but those not in GSTM1 null subjects. The incidence rate and the severity of ADRs were higher in the GSTM1 null subjects than the GSTM1 functional subjects. Through the integrated omics analysis, we could understand the mechanism of inter-individual variability in drug exposure and in adverse response. In conclusion, integrated multi-omics analysis can be useful for elucidating the various characteristics of new drug candidates in early phase clinical trials.

Indexed as

clinical trialmetabolomicsnew drug developmentpharmacogenomics

Identifiers

PMID30309203
PMCPMC6187817
OpenAlexW2896629973

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.