6-Hour Virtual Seminar on Adaptive Design for Clinical Trials

Duration: 6 Hours
Presenter: Elaine Eisenbeisz

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.

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. 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.

Areas Covered in the Seminar:

  • Overview of Applications for Adaptive Design in Clinical Trials
  • Statistical Techniques of Adaptive Design
  • Practical Considerations for implementation of an Adaptive Design
  • Sample Size Re-Estimation (SSR)
  • 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 Should Attend:

  • 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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Elaine Eisenbeisz

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.

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 www.OmegaStatistics.com to learn more about Elaine and Omega Statistics.

Duration: 6 Hours
Presenter: Elaine Eisenbeisz

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  • Login Information with Password to join the session, 24 hours prior to the webinar
  • Presentation Handout in .pdf format
  • Presentation from the Speaker
  • Feedback form
  • Certificate of Attendance
  • Recording access Information with Password to view the webinar, will be sent 24 hours after the completion of the Live webinar.
  • Presentation Handout in .pdf format
  • Certificate of Attendance