Students completing this course will learn appropriate statistical techniques associated with the major end points for clinical trials. You will study the domain (what is a clinical trial?), principles of experiment design, and how to develop a statistical analysis plan including trial objectives, hypotheses, and choice of techniques.
- Identify the phases in clinical trials and their scope (new drugs, devices, etc)
- Describe the different possible endpoints for a study (binary, measured data, etc.)
- List the principles of good trial design
- Specify designs for case studies with different endpoints
- Conduct analysis for several different endpoint designs
Who Should Take This Course
Those contemplating a career in the pharmaceutical industry; analysts and scientists at pharmaceutical companies and other health research organizations who want to become involved in the design, monitoring or analysis of clinical trials.
- What is a clinical trial?
- Historical remarks, some diseases and discoveries
- Steps(phases)in drug development
- Scope of clinical trials: new drugs, generics, devices, psychiatric therapy, alternative medicine.
- Role of statistics
Planning a Clinical Trial – Statistician’s Inputs
- Principles of design of experiments (replication, local control, randomization)
- Power and sample size
- Bias reduction (blinding)
- Commonly used designs
Statistical Analysis Plan (SAP) of Clinical Trial
- Trial objectives, hypotheses, choice of techniques, nature of endpoints (illustrated with live cases)
- End point Binary: A Randomizated Evaluation of First-Dollar Coverage for Post-MI Secondary Preventive Therapies (Post-MI FREEE)
- End point – Normal: accuracy study of SoftTouch (a non-invasive device for measurement of peripheral blood biomarkers)
- End point – count data: Pediatric Asthma Alert Intervention for Minority Children With Asthma (PAAL)
- End point – non-Normal: TBTC Study 27/28 PK: Moxifloxacin Pharmacokinetics During TB Treatment
Illustrative Statistical Analysis of Clinical Trial Data
- One sample problem – reduction in blood pressure
- Two sample problem – anorexia
- K-sample problem – drowsiness due to antihistamines
- Cochrane’s Q test – allergic response
- Analysis of Time-concentration data in pharmacokinetic study
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Homework in this course consists of short answer questions to test concepts.
In addition to assigned readings, this course also has supplemental readings available online, and an end of course data modeling project.
The required text is Fundamentals of Clinical Trials by Friedman, Furberg, and DeMets. The book is available here.
No specific software is required.
Any standard statistical software package should be able to handle the illustrations and exercises; SAS is the most widely used software in the field of clinical trials. EXCEL and MINITAB will be used for illustrations during the course. It is possible to download free trial version of MINITAB for 30 days.
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