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  • CRP 248: Clinical Trials

    2.00 Credits
    Duke University

    Fundamental concepts in the design and analysis of clinical trials are examined. Topics include protocol management, sample size calculations, determination of study duration, randomization procedures, multiple endpoints, study monitoring, and early termination. Prerequisite: CRP 245. Credits: 2.
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  • CRP 252: Principles Of Clinical Pharmacology I

    2.00 Credits
    Duke University

    This course provides a basis for understanding the scientific principles of rational drug therapy and contemporary drug development, with emphasis on pharmacokinetics, methods for drug analysis, drug metabolism and pharmacogenetics. Topics include the physiologic and pathophysiologic factors involved in drug absorption, distribution, metabolism and elimination, determinants of variability in drug responses, inter- and intra-patient variability in pharmacokinetics/pharmacodynamics, and drug interactions. This course also provides an introduction to common pharmacokinetic and pharmacodynamic modeling approaches. Prerequisites: CRP 241, CRP 242 and calculus. Credits: 2.
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  • CRP 256: Statistical Analysis Of Gene Expression Data

    2.00 Credits
    Duke University

    The focus is on concepts in the design and data analysis of gene expression (microarray and serial analysis of gene expression) experiments. Statistical concepts include issues that arise when there are many more variables than samples, sources of variation (systematic and random), replication, scope of inference, experimental design, data processing, multiple testing, and validation. Methods that address the general objectives of identification of class differences, class prediction, and class discovery are covered. Prerequisites: CRP 243 and CRP254. Co-requisite: CRP 255. Credit: 2.
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  • CRP 257: Proteomics And Protein Biology In Medicine

    2.00 Credits
    Duke University

    Platform technologies and computational methodologies for protein profiling and interaction analysis are introduced. The platform technologies covered include mass spectroscopy, 2D gel electrophoresis, surface plasmon resonance, protein arrays and flow cytometry. Structural biology and high-throughput screening methods are also discussed. Credits: 2.
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  • CRP 258: Principles Of Clinical Pharmacology Ii

    2.00 Credits
    Duke University

    As a continuation of CRP 252, this course includes the topics of drug transport mechanisms and their relevance on pharmacokinetics and drug metabolism, dose response and concentration response analysis, biological markers of drug effect, and adverse drug reactions. In addition, emphasis is given to optimizing and evaluating the clinical use of drugs, as well as drug therapy in special populations (children, elderly adults, pregnant and nursing women). A special course module focuses on the processes of drug discovery and development, and the regulatory role of the FDA. Prerequisite: CRP 252. Credit: 2.
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  • CRP 259: Decision Sciences In Clinical Research

    2.00 Credits
    Duke University

    Modeling the potential impact of a health intervention on disease outcomes can be extremely useful in gaining an understanding of the underlying biology or epidemiology of a disease, in designing research studies, and in assessing whether an intervention is economically feasible. This course focuses on basic modeling techniques, with an emphasis on decision analysis and cost-effectiveness analysis, and the application of these techniques to the student's own research. Topics covered include basic decision theory, basic principles of economic analysis in health care, decision trees, Markov models, infectious disease models, and economic analysis of clinical trials, how to review a decision/cost-effectiveness analysis, and the application of models for research and policy analysis. Prerequisite: CRP 242. Credit: 2.
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  • CRP 261: Sas Programming For Data Management

    1.00 Credits
    Duke University

    This course is an introduction to the use of SAS for data management. The primary goal is to empower the student to restructure, clean and otherwise prepare data sets for subsequent analysis using SAS. This is accomplished through directed exercises in which fundamental programming and documentation tools are emphasized. Prerequisite: CRP-241.Credit 1
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  • CRP 262: Systemic Reviews And Meta Analysis

    1.00 Credits
    Duke University

    This course provides a practical foundation for systematic reviews involving quantitative synthesis (quantitative meta analysis). Through directed exercises, students learn when and how to perform quantitative synthesis using freely available software. Topics include: computing effect sizes, computing a combined effect, fixed effect vs. random effects analyses, heterogeneity in effect sizes, and methods to detect publication bias. Prerequisite CRP 242. Corequisite CRP-245. Credit: 1.
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  • CRP 263: Longitudinal Data Analysis

    2.00 Credits
    Duke University

    Longitudinal methods are required in the analysis of two types of study designs, those that involve questions about systematic change over time and those that involve questions about whether and when events occur. The first type is characterized by repeated observations of the same variables over time, allowing the analysis of temporal changes. In the second type, commonly referred to as time-to-event designs, the outcome of interest is the time to an event such as death or hospitalization. The course covers the design, analysis and interpretation of these types of studies. Various models, methodological issues and methods of analysis are discussed and demonstrated using SAS and Enterprise Guide. Lectures are supplemented with readings from texts and journal articles. Prerequisite: CRP 245. Credit 2.
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  • CRP 264: Introduction To Immunology In Clinical Research

    2.00 Credits
    Duke University

    This course provides an introduction to basic concepts of immunology, clinical assessment of immune function, and the fundamental importance of immune mechanisms in human disease. Topics include innate and adaptive immunity, regulatory mechanisms, and inflammation. Translational techniques used in immune assessment are described in the context of relevant clinical examples. Emphasis is placed on the application of basic immunology to human diseases in oncology, infections, autoimmunity, and transplantation. Credit: 2.
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