Introduction to Adaptive Design for Clinical Trials (Philadelphia, PA, United States - November 15-16, 2018)

  • ID: 4594490
  • Conference
  • Location: Philadelphia, PA, United States
  • 2 Days
  • NetZealous LLC
  • Conference Dates: November 15-16, 2018
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Course "Introduction to Adaptive Design for Clinical Trials" has been pre-approved by RAPS as eligible for up to 12 credits towards a participant's RAC recertification upon full completion.

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
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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
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  • Elaine Eisenbeisz Elaine Eisenbeisz,
    Owner and Principal Statistician ,
    Omega Statistics

    Elaine Eisenbeisz is a private practice consultant based in Southern California. She has over 20 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 completed her graduate certification in Applied Statistics with Texas A & M University. Gig ‘em Aggies! Currently, she is finishing her graduate work in Applied Statistics at Rochester Institute of Technology.

    Elaine is a member of The American Statistical Association as well as many other professional organizations. She is also a member of the Mensa High IQ Society. Elaine is also a member in good standing with the Better Business Bureau.

    Current areas of interest include Bayesian inference, simulation and bootstrapping techniques, and predictive modeling.

    When she isn’t crunching numbers you can find Elaine digging in her garden, playing her violin, cooking, or playing board games with friends.

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  • 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
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Philadelphia, PA
United States

Venue to be announced shortly.

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