Cho, Sung Kweon
Welcome to the lab!
Uric Acid-Related Genes and Transporters
New Drug Development
Uric Acid and Its Relation to
Clinical and Risk Factors
Cost-Benefit Analysis for Current
Available COVID-19 Drugs and Vaccines
Our lab builds models
exploring the urate dynamics in
a purine metabolic pathway.
We understand uric acid as an agent
reflecting the dynamic equilibrium of
the purine metabolic pathway.
Our lab identifies uric acid-related genes
and transporters. Each gene is good target for Urate lowering therapy (ULT).
We’re dedicating to develop the next generation ULT! It is coming and new future is near.
Our goal is to investigate whether
uric acid-related genes and transporters
are related to chronic diseases, especially
chronic kidney disease (CKD)
We use next-generation sequencing
for rare variants in the genomic detection
of inherited rare diseases.
Screening of just two ethnic-specific variants (p.Trp258* and p.Arg90His) identified 87.7% (71/81) of Korean patients with monogenic hypouricemia.
–Scientific Reports 2019
A rare, nonsense variant SLC22A12 p.W258X showed the most significant association with reduced SUA levels, and PRSs of common variants associated with SUA levels were significant in multiple Korean cohorts.
–Scientific Reports 2020
We found the uric acid lowering gene (URAT1 and GLUT9) using WES and GWAS.
Variants-of-interest are validated
by the functional analysis.
Our lab has contributed to
clinical pharmacology and
is passionate about new
We design and conduct phase 1
clinical trial, bridging study, and
Clarelli, Fabrizio, et al. “Multi-scale modeling of drug binding kinetics to predict drug efficacy.” Cellular and Molecular Life Sciences 77.3 (2020): 381-394.
We consult the investigational
new drug (IND) application
and eventually submit a new drug
Our lab examines uric acid and its relation to
clinical and risk factors in human health.
We build a prediction model with the data-driven
hypotheses, ultimately identifying not-yet-known
causal factors for chronic diseases.
The prediction model is built with
top-notch statistical models
using artificial intelligence,
big data, and machine learning
Our current research goal is to
find the Real-World Evidence (RWE)
using the Real-World-Ready Datasets (RWD).
Snyder, J. M., Pawloski, J. A., & Poisson, L. M. (2020). Developing Real-world Evidence-Ready Datasets: Time for Clinician Engagement. Current oncology reports, 22(5), 1-8.
A kind of RWD, the Observational Medical Outcomes Partnership of the Common Data Model (OMOP-CDM), is a product of harmonizing data collected for a different purpose (i.e., Electronic Medical Records (EMR) and administrative claims data).
OMOP-CDM consists of standardized data and information, including terminologies,
vocabularies, and coding schemes.
OMOP-CDM allows researchers to minimize information loss using standardized formats and perform systematic analyses using standardized analytic routines.
We acknowledge the COVID-19 vaccine and drug support disparity, especially for people in developing countries. Those underserved populations do not benefit much from the medical service. Such a fact may contribute to the emergence of a variety of COVID-19. As emerging new variants of the COVID-19 continued, the pandemic has been extended.
Our goal is to take a cost-benefit analysis
for current available COVID-19 drugs and
vaccines from the perspective of
The research would promote increasing
the quality of life in underserved populations.