This course aims to teach the fundamentals of clinical trial design through lectures, discussions, and development of clinical trial protocols. Classroom lectures will cover clinical trial phases, choosing appropriate endpoints, commonly used clinical trial designs in oncology, randomization, interim analyses, and novel trial methods, such as basket trials and master protocols. We will also cover patient reported outcomes, integrative medicine, and imaging studies. Scholars will also learn about using real world data, barriers to accrual, and presenting trials to the DSMB/DSMC. Discussions will incorporate lecture themes. The scholars will choose a clinical trial to develop and then methodically develop their own protocol during the protocol development segment of the course. Protocols will be presented to the class.
- Teacher: Sean M. Devlin
- Teacher: Katherine S. Panageas
- Teacher: Charlie White
Introductory Biostatistics will begin by defining populations, samples and parameters. Students will then learn to use the information in the sample to make inferences about population parameters. Data types will be introduced (continuous, categorical, censored) and common methods of visualization and exploratory data analyses will be described. Three methods of inference will be discussed: point estimation, interval estimation and hypothesis testing. Interpretation of estimates will be discussed thoroughly. Hypothesis testing will receive special attention, with definitions of Type I and II errors. Students will learn what p-values are, how they are interpreted, and their appropriate and inappropriate uses. Thresholding variables to create categories will be discussed with correct and commonly-used incorrect methods as well as a critical review of the advantages and disadvantages of using thresholds. Two lectures will focus on censored data, a common occurrence in cancer studies, highlighting why it happens, how one can tell and what can be done with such data. Students will also learn non-parametric statistical methods and exact methods. The last lecture will cover statistical concepts for diagnostic studies, which are widely useful and will re-appear in Advanced Biostatistics (M305).
- Teacher: Mithat Gonen
- Teacher: Charlie White
- Teacher: Charlie White
One of the main goals of the Master’s in Clinical and Translational Cancer Research is to train researchers to apply their understanding of biomedical science and analytical and critical thinking skills to solve challenging clinical problems. However, these skills are not sufficient to conduct successful clinical cancer research. Clinical scientists must also possess thorough knowledge of the management, regulatory, and compliance practices necessary to implement clinical research projects. This course aims to fulfil these training needs by focusing on the practical aspects of executing clinical trials in a Good Clinical Practice (GCP) and Human Subject Research (HSR) regulatory compliant fashion. Topics include conducting clinical trials in accordance with GCP; regulations established by state, federal, and international regulatory bodies; managing relationships with external academic and industry partners, and the roles and responsibilities of investigators, sponsors, monitors, and auditors. The course will also provide an overview of regulatory affairs in relation to three key areas of therapeutic development: drugs, biologics, and medical devices. Throughout the course, practical issues facing researchers as they work with the FDA and other international regulatory bodies to secure and keep product approval will be addressed. Through expert advice and groups discussions, this course will enhance the foundational knowledge that students gain during the CITI online modules and allow them to provide these lessons to their own research.