Experiential Learning in Clinical Research (Minimum of 4 units required):
Qualitative Research - 2 units - CLRE-232
Winter
This course provides skills in designing and carrying out a qualitative study useful for program management (planning, monitoring and evaluation) and ensuring quality in healthcare delivery. The methods included in the course are a sample of commonly used qualitative methods: structured and unstructured interviews, participatory learning methods, group and individual methods.
Translational Regenerative Medicine - 2 units - CLRE-237
Winter
This course covers the basics of regenerative medicine for understanding what is a stem cell targeted therapy and what are the principles for taking a cell-based product from pre-clinical to first-in-human clinical studies. Topics covered include the regulatory, ethical, and study design considerations for developing stem cell targeted therapies. Students will grasp the complexities of stem cell targeted therapies and be able to understand the framework for developing new products. This course provides a good overview for those entering a field that may deliver stem cell therapies, stem cell targeted treatments, or other cellular based therapies (e.g., car-t-cell).
Applied Translational Research - 2 units - CLRE-238
TBD
Students will gain a comprehensive and integrative operational understanding of an entire life science innovation cycle, from drug idea to market and back, through case studies done by mining publicly disclosed information in teams mentored by biopharmaceutical professionals. Prerequisites: Translational Research Fundamentals (CLRE 236) or consent of department.
Applied Translational Research II - 2 units - CLRE-239
TBD
Building upon the case studies laid out in Applied Translational Research (CLRE 238), this course will analyze in depth specific issue(s) by emulating the biomedical industry modus operandi. Mentored student teams will analyze publicly available information, develop a business case, and defend it in front of a jury of biomedical industry research and development (R&D) leaders. In the process, students will learn and apply teamwork and brainstorming techniques and tools. Prerequisites: Applied Translational Research (CLRE 238) or consent of department.
Experiential Learning in Clinical Research - 2 units - CLRE-270
TBD
This course is designed to complement and apply certain fundamental principles in the CLRE Scientific Communication course by providing a deep-dive into processes, strategies, and activities associated with publishing in the peer-review literature. Specifically, the course will provide instruction on key topics including research topic formulation, journal content types, how to draft specific manuscript elements, targeting journals and the submission process, navigating the peer-review process, types of research tools and software, how to conduct academic presentations, and strategies for translation and dissemination. In total, students will be taken through the full journey of publishing in the peer-review and also taught skills on how to ensure their research is impactful.
Advanced Statistics Electives (Minimum of 4 units required):
Longitudinal Data Analysis - 2 units - CLRE-263
Winter
This class will introduce you to the statistical methods and techniques for analyzing medical data from longitudinal studies using PASW/SPSS software. You will gain an understanding of the challenges and statistical issues for designing and analyzing longitudinal studies, recognizing and using longitudinal data analysis methods, and performing analysis. Prerequisites: Biostatistics I & II (CLRE 253 & CLRE 254) or consent of department.
Clinical Decision Analysis - 2 units - CLRE-264
TBD
This course will provide you with an introduction to the use of decision sciences in health care. You will gain skills to be able to construct and evaluate an appropriate decision analysis probability tree, value health outcomes, use sensitivity analysis, and understand how to conduct a cost-effectiveness analysis.
Advanced Regression Methods - 2 units - CLRE-265
Fall
This course will expose and familiarize you with important advanced statistical methods such as methods for numeric outcomes (Linear regression), non-linear regression, binary outcomes (Logistic regression), counts (Poisson regression), and categorical outcomes (Log-linear models.) Prerequisite: Biostatistics I (CLRE 253). Corequisite: Biostatistics II (CLRE 254) or consent of department.
Advanced Statistics Using R - 2 units - CLRE-267
Spring
This course introduces biostatistical methods used in more advanced clinical research work, including longitudinal data analysis, meta-analysis, predictive modeling (LASSO, random forests, neural networks), competing risks survival analysis. Uses the R statistical package. Prerequisite: Biostatistics I (CLRE 253). Corequisite: Biostatistics II (CLRE 254) or consent of department.
General Electives (Minimum of 2 units are required):
Current Trends in Biomedical Informatics - 1 units - MED-262
Weekly talks by researchers introduce students to current research topics within BMI. Speakers are drawn from academia, health care organizations, industry, and government. This is a required course for the Biomedical Informatics track, and an elective for the Bioinformatics and Systems Biology track.
Bioinformatics Applications to Human Disease - 4 units - MED-263
Students learn background knowledge and practical skills for investigating the biological basis for human disease. Using bioinformatics applications, they: (1) query biological and genetic sequence databases relevant to human health, (2) manipulate sequence data for alignment, recombination, selection, and phylogenetic analysis, (3) normalize microarray data and identify differentially expressed genes and biomarkers between patient groups, (4) annotate protein data and visualize protein structure, and (5) search the human genome and annotate genes relevant to human diseases.
Principles of Biomedical Informatics - 4 units - MED-264
Students will understand the main challenges of computing with phenotypes, how to integrate molecular data into electronic medical records and clinical trial records. They will get an introduction to medical decision making, consisting of introduction to decision theory, clinical decision support systems, clinical predictive models, as well as biomedical ontologies, standards, and data repositories. Students will know how to structure and query clinical data sets, and how the most commonly used privacy technologies can be used to avoid confidentiality breaches in de-identified disclosed datasets.
CER/Comparative Effectiveness Research - 2 units - CLRE-266
Spring
CER is the conduct and synthesis of research comparing the benefits and harms of different interventions and strategies to prevent, diagnose, treat and monitor health conditions. This course will provide you with an update on CER methods and a review of the critical literature in this emerging field.
Modeling Clinical Data/Knowledge for Computation - 2 units - MED-267
This course will describe existing methods for representing and communicating biomedical knowledge. The class will describe existing health care standards and modeling principles required for implementing data standards, including biomedical ontologies, standardized terminologies and knowledge resources.
Behavioral Science Research - 2 units - CLRE-268
TBD
The objective of this course is to provide you with instruction in contemporary methods and statistical analyses in behavioral science research. This course will teach you hands-on practical skills in developing and validating assessment measures, designing and evaluating clinical trials in behavioral sciences, dissemination and implementation methods, and translational research. By the end of the course, you should be better able to critique behavioral science research and develop research projects and grant proposals that may include behavioral aspects.
Statistics Concepts for Biomedical Research - 4 units - MED-268
This course focuses on standard statistical methods and experimental design as well as predictive modeling, natural language processing and information retrieval. The course also provides in-depth coverage of evaluation methods and design of experiments for machine learning and statistical learning methods. Students perform statistical analyses using R statistics software and critique statistical results in published research.
Cultural Perceptions about Health/Disease - 4 units - FPM-270
The U.S. is characterized by significant ethnic and cultural diversity due to historic and ongoing immigration. The purpose of this course is to examine issues related to ethnic and cultural diversity and how culture may impact health beliefs, health status, and utilization of health services. The course examines issues faced by health providers and researchers who work with diverse populations in domestic or international settings. We will also explore the concept of cultural competence and how it may be achieved. Relevant socio-cultural theories will also be addressed. We will employ several strategies to accomplish these objectives including didactic studies, student-centered learning, and case studies. Students will prepare a final paper and present findings to colleagues and invited instructors.
Introduction to Biomedical Natural Language Processing - 4 units - MED-277
Biomedical Natural Language Processing (BioNLP) is an essential tool in both biomedical research and clinical applications. Students taking this course will learn how to process free text data and their integration with other types of biomedical data with BioNLP.
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