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Adaptive Designs for Clinical Trials


Brief Description:

This course will teach you how to design, monitor and analyze clinical trials using statistically sound principles that incorporate interim looks at the data, possible early stopping, and sample size re-estimation at interim. It covers group sequential designs, adaptive dose finding (escalation) designs, and two-stage (e.g., phase I/II) adaptive designs. In addition, the impact of protocol amendments on clinical outcomes will also be studied.

Instructor(s):
Level: Intermediate/Advanced

Who Should Take This Course:

Statisticians with responsibility for designing, analyzing and reporting clinical trials.

Dates:
March 23, 2012 to April 20, 2012
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Adaptive Designs for Clinical Trials

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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

Register Online -$499
Register Online -$399 (you must be affiliated with a college, university or high school)

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Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise. Multiple course registrations may be entitled to tuition discounts; read more.


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Adaptive Designs for Clinical Trials



Aim of Course:

This course will introduce the adaptive design theory and the hands-on techniques for planning, designing, monitoring, and analyzing adaptive trials. We will summarize the major statistical methods for adaptive trials with an emphasis on the relationships among them. You will learn different adaptive trial designs such as sample-size re-estimation, drop-loser, biomarker-adaptive design, and response-adaptive randomization designs through trial examples and the programming tools provided (SAS and R). Challenges of adaptive trial implementations will be discussed and recommendations are provided. Ultimately, the attendees are expected to walk away with the right knowledge, skill, and tools for designing and managing adaptive trials.

Prerequisite(s):

Course Program:

SESSION 1:

  • General Concept
  • Fundamental Theory
  • Group Sequential Design
  • Adaptive Interim Analysis in Clinical Trials
SESSION 2
  • Adaptive Dose Finding Design
  • Enrichment Design for Target Clinical Trials
SESSION 3
  • Two-Stage Adaptive Design
  • Sample size estimation/allocation
SESSION 4:
  • Protocol Amendments
  • Clinical Trial Simulation
  • Efficiency of Adaptive Design
  • Case Studies

Organization of the Course:

This course takes place over the internet, at statistics.com for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and you will receive individual feedback on your homework answers.


Credit:
Students come to The Institute for a variety of reasons:
  1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. You may be enrolled in PASS (Program in Advanced Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).

As you begin the class, you will be asked to specify your category.

This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a record of course completion will be issued by Statistics.com, upon request.


Course Text:

The following texts will be used during the course:

Pong, A.P. and Chow, S.C. (2010). Handbook of Adaptive Designs in Pharmaceutical and Clinical Development. Chapman and Hall/CRC, Taylor & Franics, New York, New York.  If you would like to receive a 25% discount from the publisher, please use this form.

FDA Draft Guidance on Adaptive Design Clinical Trials for Drugs and Biologics, The U.S. Food and Drug Administration, Rockville, Maryland, February, 2010, which can be downloaded here.

Software:

Students will have access to EaSt software, which implements some of statistical methods for the adaptive clinical trial designs described in the text book.  Illustrations and demos will be provided for students to work through on their own.

Register Now

Yes, I want to register for:

Adaptive Designs for Clinical Trials

Instructor(s):
Dates:
March 23, 2012 to April 20, 2012
Course Fee: $499
Academic Discounted Rate: $399

Before registering, please read the syllabus tab, noting the prerequisites, text and software requirements. When you click the register button, you will be taken to our secure transaction page.

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What our students say:

"I found the course to be a valuable introduction to resampling and bootstrapping methods. I am recommending this course to colleagues. Thanks for an engaging and informative course."
J. Thomas
Pacific University
"The course was an interesting and delightful excursion into data mining techniques; I thoroughly enjoyed seeing the concepts come to life in the examples. It was a great course."
B. Griffin
University of South Dakota
"The course was very good and well presented. The material in the notes was self-explanatory for a non-technical person, and the supplementary book provided good reading for the person who is interested in more technical details."
Gichangi
Dept. of Statistics, Univ. of Southern Denmark (doctoral student)
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