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For more details on the courses, please refer to the Course Catalog

Code Course Title Credit Learning Time Division Degree Grade Note Language Availability
BHR5001 Introduction to Biostatistics 3 6 Major Master/Doctor Biohealth Regulatory Science - No
This course will introduce biostatistics in the pharmaceutical field to evaluate drug effectiveness and/or safety. First, statistical concepts, including probability and probability distribution, will be introduced. Moreover, the estimation and hypothesis test will be handled to understand various statistical analysis. All statistical analyses will be introduced as basic concepts with practical exercises using a statistical package.
BHR5003 Introduction to Healthcare Big Data Analysis 3 6 Major Master/Doctor Biohealth Regulatory Science - No
This course aims to learn the basics of SAS programming, an essential for research using healthcare big data, and to understand data sources mainly used for healthcare big data research including nationwide health insurance data(HIRA/NHIS), and adverse event reporting database(KAERS). Also, learn basic languages of SAS including data step, procedure step, SQL, and Macro through practice, and cultivate ability that take into account the structure of each healthcare big data and the characteristics of their variables.
BHR5004 Methods on Assessing RWD-based Drug Effectiveness 3 6 Major Master/Doctor Biohealth Regulatory Science Korean Yes
This course will cover methodological approaches (epidemiological, statistical, clinical) and considerations when conducting clinical research to investigate the effectiveness of a drug by using real-world data (RWD), that includes health insurance claims and electronic medical records. This course will nurture basic knowledge in conducting an effectiveness study that uses RWD, along with details in study design, analysis, and interpretation of results, to potentially aid in regulatory or clinical decision-making.
BHR5006 Introduction to Pharmacoepidemiology 3 6 Major Master/Doctor Biohealth Regulatory Science Korean Yes
This course is aimed to provide a basic concept of pharmacoepidemiology which is utilized in evaluating the effectiveness and/or safety of drug. Fundamental epidemiological indicators and study desing in pharamcoepidemiology will be introduced with examples of previous studies. Practical exercise will be provide including calculation of prevalence and incidence or standardization with age and sex.
BHR5007 Big Data Analysis using R 3 6 Major Master/Doctor Biohealth Regulatory Science - No
R is no longer just a statistical program, but a platform that includes the entire process of data analysis. This lecture deals with big data management focusing on data.table/fst packages, and statistical methods commonly used with jskm/jstable/jsmodule packages, and how to organize analysis results in various forms (documents, slides, web apps) with rmarkdown/shiny. All examples use data from HIRA/KNHIS/KNHANES so students can start analyzing the big data right away. By managing the code in the Github repository, I expect them to become familiar with open source and even be able to create R packages.
BHR5010 Intermediate Pharmacoepidemiology Methods 3 6 Major Master/Doctor Biohealth Regulatory Science Korean Yes
This course will cover diverse study designs commonly used to investigate the effectiveness of a drug, including cohort, case-control, case-only(case-crossover, case-time-control, case-case-time-control, self-controlled case-series). Moreover, this course will also cover important biases(eg, selection, information, confounding, time-related) and methodologies(eg, propensity score matching, weighting, stratification) to adjust or minimize them.
BHR5011 Advanced Pharmacoepidemiology Methods 3 6 Major Master/Doctor Biohealth Regulatory Science - No
This practical, hands-on course will cover methodologies on how to search and decide on a research question/topic, and how to actually draft a research protocol (accompanied with a SAP) through continued feedback and discussions. This course will cover the essential elements of a SAP (including sample size estimation, exposure and outcome definition), sensitivity analyses (eg, estimating the E-value), and multinational analyses using CDM to apply such to his/her research protocol.
BHR5012 Data Science Research Project 3 6 Major Master/Doctor Biohealth Regulatory Science - No
This course aims to learn the overall research project progress from write a protocol-based dummy table to estimate result of research using healthcare big data. Also, experience writing dummy table, selecting study subjects, defining study factors (exposure, confounder, outcome, etc.) using SAS programming, and learn both of various bias and ways to overcome it.
BHR5013 RWD-based Paper Writing 3 6 Major Master/Doctor Biohealth Regulatory Science English Yes
This course will focus on strategies and considerations when drafting a manuscript on clinical or epidemiological research that investigated the association between a drug and an outcome by using real-world data sources. This course will involve continued interactions between the lecturer and the student, to polish and refine the manuscript throughout the course, with the aim of submitting the finalized manuscript to a peer-reviewed SCI journal for publication.
BHR5021 Regulatory Science Internship 3 6 Major Master/Doctor Biohealth Regulatory Science - No
This course is for students who are planning to participate in an internship program. It is intended (1) to understand how theories and principles of regulatory science are applied in industry or government agencies and (2) to acquire experiences to apply the knowledge of regulatory science learned in school to the evaluation of drug effectiveness in the field.
BHR5022 Special topics in advanced pharmacology 3 6 Major Master/Doctor Biohealth Regulatory Science - No
This course is aimed (1) to understand the absorption, distribution, metabolism, excretion of drugs and (2) to study the effects and adverse effects of a drug on biological systems (3) to study the targets that acts, mechanisms and clinical uses of drugs.
BHR5024 Advanced cell and gene therapy 3 6 Major Master/Doctor Biohealth Regulatory Science - No
Introduces the latest gene therapy and it’s development process. In addition, This course will provide the development status and core technology of stem cell-based cell therapeutics. In this course, basic research findings and advanced technology essential for the development of the latest gene/cell therapeutics will be introduced, and how these discoveries lead to drug development will be discussed.
BHR5025 Biomarker-based efficacy evaluation 3 6 Major Master/Doctor Biohealth Regulatory Science - No
In the era of the Fourth Industrial Revolution, there is huge paradigm shift from traditional medicines to new biopharmaceuticals. Since these innovative biopharmaceuticals have a completely different mechanism and form from existing drugs, it is difficult to adequately evaluate them using the existing evaluation criteria. This course will Introduce the development trends of the latest biomarker-based efficacy evaluation technology that can be secured for the efficacy and safety of innovative biopharmaceuticals.
BHR5026 Introduction to computational omics(Intoduction to bioinformatics) 3 6 Major Master/Doctor Biohealth Regulatory Science - No
Computational omics is driving the collection and analysis of biomedical big data. This course is designed for the graduate students majoring in bioscience and provides a hands-on introduction to the computer-based analysis of genomic and biomolecular data. Students who are interested in taking Advanced computational omics are required to take this course. Major topics include: - Genomic and biomolecular bioinformatic resources - UNIX for bioinformatics - R for Bioinformatics data analysis - Genome informatics - Transcriptomics Students completing this course will be able to evaluate new genomic and biomolecular information using existing software and gain experience in combining bioinformatic approaches to answer specific biological questions.
BHR5027 Advanced computational omics(Advanced bioinformatics) 3 6 Major Master/Doctor Biohealth Regulatory Science - No
This course introduces basic concepts and skills that can help you tackle biomedical omics data analysis with R. It covers basic concepts from probability, statistical inference, linear algebra and machine learning and their applications in biomedical omics data analysis. It also helps you develop skills such as R programming, data wrangling, data visualization, algorithm building, file organization with UNIX/Linux shell, and reproducible document preparation. Some background in programming (i.e. R, python, matlab, and so on) is required. Students are expected to have taken undergraduate-level biology and probability course or to be familiar with basic biomedical concepts. Prerequisite: Introduction to computational omics or its equivalent.