15. November 2018 - 9:00
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Introduction to Adaptive Design for Clinical Trials, Philadelphia (NTZ) A | Philadelphia | Thursday, 15. November 2018

Introduction to Adaptive Design for Clinical Trials


This 2-day seminar includes an overview of Adaptive Design, and an emphasis in group sequential design, sample size re-estimation, and Phase II/III Adaptive Seamless Designs.
The role of statistics in clinical trials incorporates the tools used to develop a robust study, minimize bias, and assess efficacy of new treatments as relates to comparison to competing therapies.
Randomized clinical trials remain the standard for clinical research. However, the cost of a traditional randomized controlled trial especially in large sample sizes and long study duration, are limiting factors of innovation in the pharmaceutical and medical device arenas. A trial with an adaptive design can often result in lower costs and more efficiency by making use of interim analyses with data accumulated during the course of a trial to modify a study, without compromising validity and integrity. Adaptive designs also allow for checking trial assumptions and progress before the conclusion of the study. Studies can be adapted for dose response, patient accrual, and early stopping for futility or patient safety concerns.
However, there are special considerations in the planning and execution of a adaptive design to control Type I error rates and ensure consistency of treatment. In additional to protocol considerations, the FDA and regulatory agencies also require particular assurances that an adaptive design will incorporate flexibility at the expense of sacrificing study validity and patient safety.
The objective of the seminar is to provide information that can be used immediately by personnel involved in the design and analysis of clinical trials. The presentation involves use of statistical techniques and a basic understanding of statistical theory and the framework of randomized controlled trials is desired. However, presentation of statistical theory and application will be limited to only what is needed by the attendees to understand and implement adaptive trial design and analysis.
R statistical software will be used to demonstrate analyses and simulation studies within the adaptive design framework. So bring your laptop computer!

Why should you attend:
Clinical trials are expensive, time consuming, and labor-intensive. And in the traditional sense, study designs are inflexible.
Adaptive study designs allow for flexibility during a clinical trial. Options can be built into a study to use data collected that has accumulated at interim time points to:

Adjust sample sizes in treatment arms or reduce patient recruitment.
Drop treatment arms entirely (treatment pruning)
Adjust randomization schema
Combine Phase II and Phase III (adaptive seamless design)
Early stopping of a study for futility or success.

The U.S. Food and Drug Administration (FDA) and other regulatory agencies require the minimization of bias in study design and analysis. In order to minimize bias, particular steps and safeguards, using regulatory guidance and sound statistical principles, must be put into place to assure validity of an clinical.
Therefore a number of considerations must be made in the design of an adaptive trial to enhance flexibility while minimizing bias, and ensuring statistically valid and well-informed decisions. Problems can arise in an adaptive design due to selection bias, interim analysis "look-sies", and when merging dose selection and confirmation phases into one trial.
The benefits of a clinical trial with an adaptive design include savings in both time and dollars, to the desired end of bringing useful drug treatments and devices to patients more quickly.

Areas Covered in the Session:

Overview of Applications for Adaptive Design in Clinical Trials
Statistical Techniques of Adaptive Design
Practical Considerations for implementation of an Adaptive Design
Regulatory Aspects of an Adaptive Design
When an Adaptive Design is, and is not, Appropriate
Examples of Clinical Trials that Incorporated Adaptive Design
Computer Code in R Statistical Software for Simulation Studies

Who will benefit:

Trial Sponsors
Principal Investigators
Clinical Investigators
Clinical Research Statisticians
Clinical Research Coordinators
Clinical Research Nurse Coordinators
Clinical Research Associates/Assistants
Clinical Project Managers/Leaders
Study Managers
Regulatory Professionals/Coordinators
Medical Writers who need to interpret statistical reports


 Day 1 Schedule

Lecture 1 (90 Mins): Introduction

The What, Why, and When of Adaptive Design
Logic and Terminology of Adaptive Design

Rules of Allocation, Sampling, Stopping, Decisions
Flexible aspects of Adaptive design

Overview of Types of Adaptive Designs

Investigate phases
Confirmatory phases

Lecture 2 (90 Mins): Group Sequential Design

Interim Analysis considerations
Prematurely stopping a trial due to:

Safety concerns
efficacy or futility

Lecture 3 (90 Mins): Statistical Methods for Group Sequential Designs

Maximum information and information fractions
Pocock and O’Brien Fleming boundaries
Alpha spending
Covariate Adjustments
Enrichment Design

Lecture 4 (90 Mins): Sample Size Re-Estimation (SSR)

Why would we want to re-assess the sample size?

Uncertainty in Assumptions and/or available information
Underpowered Study

Protecting the Study Blind
Statistical Considerations of SSR

Adaptation Rules: Effect Size Ratio
Adaptation Rules: Conditional Power
Adjustment of point estimates, confidence intervals, p-value

Day 2 Schedule

Lecture 1 (90 Mins): Phase II/III Adaptive Seamless Designs: Overview and Applications

Why an Adaptive Seamless Design?
Terms and Reasoning

Dose Selection
Treatment Pruning

When and When Not to Use Adaptive Seamless Design
Special Considerations for Adaptive Seamless Design

Lecture 2 (90 Mins): Phase II/III Adaptive Seamless Designs: Statistical Methods

Closed Testing Approach
Simes procedure to control multiplicity
Inverse Normal Method
Simulation Testing for Power Comparison

Lecture 3 (90 Mins): Practical Procedural and Regulatory Issues of Adaptive Design

Concerns of Validity, Bias, Robustness of the Study
Planning for an Adaptive Study
Working with Regulatory Agencies
Concerns and Controls for Repeated Testing (Multiplicity)
Monitoring and Decision Making in an Adaptive Study

Lecture 4 (90 Mins): Case Study and Protocol Examples, Q&A/Discussion

An open review and discussion of adaptive trials in which researchers incorporated the four adaptive design rules.
Examples of protocol and statistical analysis plan sections using an adaptive trial framework
Question and Answer Session


Elaine Eisenbeisz
Owner and Principal Statistician, Omega Statistics
Elaine Eisenbeisz, is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California. Elaine has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations, to start-up companies and individual researchers.
In addition to her technical expertise, Elaine possesses a talent for conveying statistical concepts and results in a way that people can intuitively understand.
Elaine's love of numbers began in elementary school where she placed in regional and statewide mathematics competitions. She attended University of California, Riverside, as a National Science Foundation scholar, where she earned a B.S. in Statistics with a minor in Quantitative Management, Accounting. Elaine received her Master's Certification in Applied Statistcs from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology. Elaine is a member in good standing with the American Statistical Association as well as many other professional organizations. She is also a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.
Elaine has designed the methodology for numerous studies in the clinical, biotech, and health care fields. She currently is an investigator on approximately 10 proton therapy clinical trials for Proton Collaborative Group, based in Illinois. She also designs and analyzes studies as a contract statistician for nutriceutical and fitness studies with QPS, a CRO based in Delaware. Elaine has also worked as a contract statistician with numerous private researchers and biotech start-ups as well as with larger companies such as Allergan and Rio Tinto Minerals. Not only is Elaine well versed in statistical methodology and analysis, she works well with project teams. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals. Please visit the Omega Statistics website at to learn more about Elaine and Omega Statistics.

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