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San Diego Convention Center

2024 年 06 月 11 日 1:00 下午 - 2024 年 06 月 11 日 4:00 下午

111 W Harbor Drive, , San Diego, CA 92101 , USA

Protocol Development Best Practices using Estimand Thinking

This is a virtual pre-meeting Short Course in conjunction with the DIA Global Annual Meeting.

概览

Pre-registration required and is an additional fee.

*Please note: Short Courses are stand-alone events. Registration for the main conference, forum, etc. are not mandatory.

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This Short Course will be offered virtually – Join from anywhere! This short course will review current protocol templates in the public domain to share best practices in optimizing protocol design. The course will also summarize key elements from ICH guidances including ICH E9R1 to apply Estimand thinking for selecting the appropriate components of Estimands and strategies for handling of intercurrent events. Select examples of Phase 2 and 3 study protocols in the public domain that appropriately used Estimand thinking will be assessed, in addition to review protocols from recent approvals and failures for drugs and biologics to learn how to increase likelihood of success in your trials.

Register for two or more Short Courses and receive $50 off each Short Course! Purchases must be made at the same time to receive the discount. Discounts will be reflected on the last page of the cart.


Registered attendees for this virtual Short Course will receive access to the course recording for 2 full months post-course! This allows you to remain flexible with your schedule and not worry if you need to step out momentarily. Have a conflict with the dates of the course, but are interested in the content? Register anyway and you will receive access to the recording!


谁应该参加?

Clinicians, Medical Writers, Statisticians and anyone involved in designing Phase 2 or 3 clinical trials.

学习目标

At the conclusion of this short course, participants should be able to:
  • Recognize standard protocol templates for Phase 2 and 3 studies
  • Demonstrate Estimand thinking for designing protocols for high likelihood for detecting treatment effects
  • Apply recent approvals and failures for drugs and biologics to optimize protocol design

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