채동우 교수
Dongwoo Chae
연세대학교 약리학과 · 의학
연구실 소개
채동우 교수의 연구실은 암호학적 기반의 신약 개발과 유전자 기반 생물 통제 기술을 핵심으로 삼고 있습니다. 특히, 수면유도제인 레미마졸람과 세보플루란의 라봇 식도절제술에서의 혈역학적 안정성 비교, CRISPR 기반 유전자 드라이브의 화학적 제어 기술 개발 등 고도화된 의학적 응용을 연구하고 있습니다. 또한, 마이크로바이옴, 약물 동태학, 인공지능 기반 예측 모델링을 접목해 정밀의료와 약물 개발의 혁신을 도모하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15Remimazolam has been suggested to improve the maintenance of hemodynamic stability when compared with other agents used for general anesthesia. This study aimed to compare the effects of remimazolam and sevoflurane anesthesia on hemodynamic stability in patients undergoing robotic gastrectomy. We retrospectively reviewed the electronic medical records of 199 patients who underwent robotic gastrectomy with sevoflurane (n = 135) or remimazolam (n = 64) anesthesia from January to November 2021. Pro
Gene drive systems that propagate transgenes via super-Mendelian inheritance can potentially control insect-borne diseases and agricultural pests. However, concerns have been raised regarding unforeseen ecological consequences, and methods that prevent undesirable gene drive effects have been proposed. Here, we report a chemical-induced control of gene drive. We prepared a CRISPR-based gene drive system that can be removed by a site-specific recombinase, Rippase, the expression of which is induc
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods that are largely inference-based, ML is geared more towards making accurate predictions. ML is a field of artificial intelligence concerned with developing algorithms and models to perform prediction tasks in the absence of explicit instructions. Most ML applications, despite being highly variable in the topics that they deal with, generally follow a common workflow. For classification tasks, a re
Postoperative nausea and vomiting is the most common side-effect of opioid-based intravenous patient-controlled analgesia. Apfel's simplified risk score is popular but it has some limitations. We developed and validated a dynamic predictive model for nausea or vomiting up to 48 postoperative hours, available as an online web application. Fentanyl was used by 22,144 adult patients for analgesia after non-cardiac surgery under general anaesthesia: we randomly divided them into development (80%) an
Phage therapy is progressively being recognized as a viable alternative to conventional antibiotic treatments, particularly in the context of multi-drug resistant bacterial challenges. However, the intricacies of the pharmacokinetics and pharmacodynamics (PKPD) pertaining to phages remain inadequately elucidated. A salient characteristic of phage PKPD is the inherent ability of phages to undergo replication. In this review, I proffer mathematical models that delineate the intricate dynamics enco
The incidence of major hemorrhage and transfusion during liver transplantation has decreased significantly over the past decade, but major bleeding remains a common expectation. Massive intraoperative hemorrhage during liver transplantation can lead to mortality or reoperation. This study aimed to develop machine learning models for the prediction of massive hemorrhage and a scoring system which is applicable to new patients. Data were retrospectively collected from patients aged >18 years who h
Item response theory (IRT) has been recently adopted to successfully characterize the progression of Parkinson's disease using serial Unified Parkinson's Disease Rating Scale (UPDRS) measurements. However, it has yet to be applied in predicting the longitudinal changes of levodopa dose requirements in the real-world setting. Here we use IRT to extract two latent variables that represent tremor and non-tremor-related symptoms from baseline assessments of UPDRS Part III scores. We show that relati
BACKGROUND: Several predictive factors for chronic kidney disease (CKD) following radical nephrectomy (RN) or partial nephrectomy (PN) have been identified. However, early postoperative laboratory values were infrequently considered as potential predictors. Therefore, this study aimed to develop predictive models for CKD 1 year after RN or PN using early postoperative laboratory values, including serum creatinine (SCr) levels, in addition to preoperative and intraoperative factors. Moreover, the
The early detection of graft failure in pediatric liver transplantation is crucial for appropriate intervention. Graft failure is associated with numerous perioperative risk factors. This study aimed to develop an individualized predictive model for 90-days graft failure in pediatric liver transplantation using machine learning methods. We conducted a single-center retrospective cohort study. A total of 87 liver transplantation cases performed in patients aged < 12 years at the Severance Hospita
We aimed to develop a risk scoring system for 1-week and 1-month mortality after major non-cardiac surgery, and assess the impact of postoperative factors on 1-week and 1-month mortality using machine learning algorithms. We retrospectively reviewed the medical records of 21,510 patients who were transfused with red blood cells during non-cardiac surgery and collected pre-, intra-, and postoperative features. We derived two patient cohorts to predict 1-week and 1-month mortality and randomly spl
Our findings suggest that the telmisartan/rosuvastatin FDC is bioequivalent to coadministration of separate tablets, and both treatments were safe and well tolerated. Administration of this FDC tablet is expected to improve patient compliance.
Quantitative systems pharmacology (QSP) can be regarded as a hybrid of pharmacometrics and systems biology. Here, we introduce the basic concepts related to dynamical systems theory that are fundamental to the analysis of systems biology models. Determination of the fixed points and their local stabilities constitute the most important step. Illustration of a phase portrait further helps investigate multistability and bifurcation behavior. As a motivating example, we examine a cell circuit model
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