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Introduction to Statistical Issues in Clinical Trials

Introduction to Statistical Issues in Clinical Trials

This course will teach you the basic statistical principles in the design and analysis of randomized controlled trials.

Overview

This course, designed for anyone contemplating a career in the pharmaceutical industry or health research, covers the basic statistical principles in the design and analysis of randomized controlled trials. Students will learn about the role of statistics in clinical trials, how to plan and design experiments, and how to analyze statistical outcomes. You will also be introduced to pharmacokinetics and the study of drug concentration data.

  • Introductory
  • 4 Weeks
  • Expert Instructor
  • Tuiton-Back Guarantee
  • 100% Online
  • TA Support

Learning Outcomes

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.

Our Instructors

Dr. Nand Kishore Rawat

Dr. Nand Kishore Rawat

Dr. Nand Kishore Rawat is a Portfolio Director of Clinical Research Services at Cytel Statistical Software & Services. With his expertise in planning, designing and analysing clinical trial projects, and his experience in clinical trial development at Bristol-Myers Squibb, Novartis, and also noted contract research organizations (CRO’s), he brings a valuable practical perspective to the classroom and gives his students an insightful window into the pharmaceutical clinical trial world. Dr. Nand Kishore Rawat has expertise in planning, designing and analysing clinical trial projects. 

Course Syllabus

Week 1

The Domain

  • 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

Week 2

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

Week 3

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

Week 4

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

Class Dates

2024

06/07/2024 to 07/05/2024
Instructors: Dr. Nand Kishore Rawat
11/22/2024 to 12/20/2024
Instructors: Dr. Nand Kishore Rawat

2025

06/06/2025 to 07/04/2025
Instructors: Dr. Nand Kishore Rawat
11/21/2025 to 12/19/2025
Instructors:

Prerequisites

Karolis Urbonas
Susan Kamp
Stephen McAllister
Amir Aminimanizani
Elena Rose
Leonardo Nagata
Richard Jackson

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Introduction to Statistical Issues in Clinical Trials

Additional Information

Organization of Course

This course takes place online at The Institute 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.

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 at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

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.

Course Text

The required text is Fundamentals of Clinical Trials by Friedman, Furberg, and DeMets. The book is available here.

Software

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.

Course Fee & Information

Enrollment
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.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

Supplemental Information

Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

 

Chrome

 

Firefox

 

Safari

  • Navidys (for colorblindness, dyslexia, and reading difficulties)
  • HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

Miscellaneous

There is no additional information for this course.

Register For This Course

Introduction to Statistical Issues in Clinical Trials